Peter Stone's Selected Publications
      
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         NSF
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         AFOSR
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         AFRL
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         ARL
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         ARO
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         FLI
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         ONR
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         IBM
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         DARPA
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         FHWA
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         TXDOT
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         Fulbright
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         Guggenheim
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         Intel
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         Raytheon
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         Lockheed Martin
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         Toyota
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         ATT
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         Bosch
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         GM
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         Good Systems
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         Unspecified
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      NSF
      
      
         - L3M+P: Lifelong Planning with Large Language Models.
 Krish Agarwal, Yuqian Jiang,
            Jiaheng Hu, Bo Liu, and Peter
            Stone.
 In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
- Proto Successor Measure: Representing the Behavior Space of an RL Agent.
 Siddhant Agarwal, Harshit Sikchi, Peter
            Stone, and Amy Zhang.
 In International Conference on Machine Learning, June 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (911.1kB
               )
- The Essentials of AI for Life and Society: An AI Literacy Course for the University Community.
 Joydeep
            Biswas, Don Fussell, Peter Stone, Kristin Patterson, Kristen Procko, Lea
            Sabatini, and Zifan Xu.
 In Proceedings of the AAAI Conference on Artificial Intelligence,
            pp. 28973–8, April 2025.
 Official published
            version
 Appeared in Symposium on Educational Advances in Artificial Intelligence
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (262.3kB
               )
                [slides.pdf]
               (1.7MB
               )
- Deadlock-free, Safe, and Decentralized Multi-Robot Navigation in Social Mini-Games via Discrete-Time Control Barrier Functions.
 Rohan Chandra, Vrushabh Zinage, Efstathios Bakolas, Peter
            Stone, and Joydeep Biswas.
 Autonomous Robots, 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.5MB
               )
                [poster.pdf]
               (1.7MB
               )
- Multi-Agent Inverse Reinforcement Learning in Real World Unstructured Pedestrian Crowds.
 Rohan
            Chandra, Haresh Karnan, Negar Mehr, Peter
            Stone, and Joydeep Biswas.
 In IEEE/RSJ International Conference on Intelligent
            Robots and Systems (IROS), October 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (695.7kB
               )
- MEReQ: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Intervention.
 Yuxin
            Chen, Chen Tang, Jianglan Wei, Chenran Li, Ran
            Tian, Xiang Zhang, Wei Zhan, Peter Stone, and Masayoshi Tomizuka.
 In
            Conference on Robot Learning (CoRL), September 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (18.9MB
               )
- Dyna-LfLH: Learning Agile Navigation in Dynamic Environments from Learned Hallucination.
 Saad Abdul Ghani, Zizhao
            Wang, Peter Stone, and and Xuesu
            Xiao.
 In International Conference  on Intelligent Robots and Systems, October 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- FLaRe: Achieving Masterful and Adaptive Robot Policies with Large-Scale Reinforcement Learning Fine-Tuning.
 Jiaheng
            Hu, Rose Hendrix, Ali Farhadi, Aniruddha Kembhavi, Roberto Martín-Martín, Peter
            Stone, Kuo-Hao Zeng, and Kiana Ehsani.
 In ICRA, May 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.2MB
               )
- Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks.
 Viraj Joshi, Zifan
            Xu, Bo Liu, Peter Stone, and
            Amy Zhang.
 In Reinforcement Learning Conference (RLC), August 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.5MB
               )
- Reinforcement Learning within the Classical Robotics Stack: A Case Study in Robot Soccer.
 Adam Labiosa, Zhihan Wang,
            Siddhant Agarwal, William Cong, Geethika Hemkumar, Abhinav Narayan Harish, Benjamin Hong, Josh Kelle, Chen Li, Yuhao Li, Zisen
            Shao, Peter Stone, and Josiah
            Hanna.
 In International Conference on Robotics and Automation (ICRA), May 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
- Hyperspherical Normalization for Scalable Deep Reinforcement Learning.
 Hojoon
            Lee, Youngdo Lee, Takuma Seno, Donghu Kim, Peter
            Stone, and Jaegul Choo.
 In International Conference on Machine Learning, June 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.9MB
               )
- Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory.
 Alexander Levine, Peter
            Stone, and Amy Zhang.
 In International Conference on Learning Representations, April 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pdf]
               (1.6MB
               )
                [poster.pdf]
               (3.4MB
               )
- PACER: Preference-conditioned All-terrain Costmap Generation.
 Luisa Mao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 Robotics
            and Automation Letters, 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.2MB
               )
                [slides.pptx]
               (28.0MB
               )
- ProtoCRL: Prototype-based Network for Continual Reinforcement Learning.
 Michela Proietti, Peter
            R. Wurman, Peter Stone, and Roberto Capobianco.
 In Reinforcement
            Learning Conference, August 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- PRESTO: Fast Motion Planning Using Diffusion Models Based on Key-Configuration Environment Representation.
 Mingyo
            Seo, Yoonyoung Cho, Yoonchang Sung, Peter
            Stone, Yuke Zhu, and Beomjoon Kim.
 In IEEE International Conference
            on Robotics and Automation (ICRA), May 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pdf]
               (2.1MB
               )
                [poster.pdf]
               (1.3MB
               )
- Artificial Intelligence: Looking Forward 15 Years.
 Peter Stone.
 IEEE
            Intelligent Systems, 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (517.0kB
               )
- Dyn-O: Building Structured World Models with Object-Centric Representations.
 Zizhao
            Wang, Kaixin Wang, Li Zhao, Peter Stone, and Jiang Bian.
 In Annual
            Conference on Neural Information Processing Systems, December 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (22.9MB
               )
- GACL: Grounded Adaptive Curriculum Learning with Active Task and Performance Monitoring.
 Linji Wang, Zifan
            Xu, Peter Stone, and Xuesu Xiao.
 In
            IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
- LLM-GROP: Visually grounded robot task and motion planning with large language models.
 Xiaohan Zhang, Yan Ding,
            Yohei Hayamizu, Zainab Altaweel, Yifeng Zhu, Yuke
            Zhu, Peter Stone, Chris Paxton, and Shiqi
            Zhang.
 The International Journal of Robotics Research, 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.5MB
               )
- Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning.
 Caleb Chuck, Carl Qi, Michael J. Munje, Shuozhe Li, Max Rudolph, Chang Shi, Siddhant Agarwal, Harshit Sikchi,
            Abhinav Peri, Sarthak Dayal, Evan Kuo, Kavan Mehta, Anthony Wang, Peter Stone,
            Amy Zhang, and Scott Niekum.
 In ICRA Workshop on Manipulation Skills,
            May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (19.7MB
               )
- Learning to Look: Seeking Information for Decision Making via Policy Factorization.
 Shivin Dass, Jiaheng
            Hu, Ben Abbatematteo, Peter Stone, and Roberto Martín-Martín.
 In Conference
            on Robot Learning (CoRL), November 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.8MB
               )
- Telemoma: A Modular and Versatile Teleoperation System for Mobile Manipulation.
 Shivin Dass, Wensi Ai, Yuqian
            Jiang, Samik Singh, Jiaheng Hu,
            Ruohan Zhang, Peter Stone,
            Ben Abbatematteo, and Roberto Martin-Martin.
 In ICRA Workshop on Mobile Manipulation and Embodied Intelligence,
            May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.9MB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            P. Hanna, Yash Chandak, Philip S. Thomas, Martha White,
            Peter Stone, and Scott Niekum.
 Journal
            of Machine Learning Research, 2024.
 Official version on publisher's
            website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.7MB
               )
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
 Haresh,
            Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
 In
            International Conference on Robotics and Automation, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.3MB
               )
- Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning.
 Jiaheng
            Hu, Zizhao Wang, Roberto Martín-Martín, and Peter
            Stone.
 In Conference on Neural Information Parocessing Systems (NeurIPS), December 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.7MB
               )
- Learning Optimal Advantage from Preferences and Mistaking it for Reward.
 W. Bradley
            Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter
            Stone, and Scott Niekum.
 In The 38th Annual AAAI Conference on Artificial
            Intelligence (AAAI), February 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.6MB
               )
                [slides.pdf]
               (3.9MB
               )
                [poster.pdf]
               (2.9MB
               )
- Multistep Inverse Is Not All You Need.
 Alexander Levine, Peter Stone,
            and Amy Zhang.
 Reinforcement Learning Conference, 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
                [slides.pdf]
               (4.8MB
               )
                [poster.pdf]
               (2.7MB
               )
- Conflict Avoidance in Social Navigation --- a Survey.
 Reuth
            Mirsky, Xuesu Xiao, Justin Hart, and
            Peter Stone.
 ACM Transactions on Human-Robot Interaction, 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
 Amir Hossain Raj, Zichao
            Hu, Haresh Karnan, Rohan Chandra,
            Amirreza Payandeh, Luisa Mao, Peter Stone, Joydeep
            Biswas, and and Xuesu Xiao.
 In International Conference on Robotics
            and Automation, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
- The Human in the Loop: Perspectives and Challenges for RoboCup 2050.
 Alessandra Rossi, Maike Paetzel-Prüsmann,
            Merel Keijsers, Michael Anderson, Susan Leigh Anderson, Daniel Barry, Jan Gutsche, Justin
            Hart, Luca Iocchi, Ainse Kokkelmans, Wouter Kuijpers, Yun Liu, Daniel
            Polani, Caleb Roscon, Marcus Scheunemann, Peter Stone, Florian Vahl, René
            van de Molengraft, and Oskar von Stryk.
 Autonomous
            Robots, May 2024.
 Official version on publisher's website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- Relaxed Exploration Constrained Reinforcement Learning.
 Shahaf S. Shperberg, Bo
            Liu, and Peter Stone.
 In Conference on Autonomous Agents and Multiagent
            Systems, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
- Dobby: A Conversational Service Robot Driven by GPT-4.
 Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
            Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
            Hart.
 In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (863.8kB
               )
                [poster.pdf]
               (892.0kB
               )
- Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning.
 Yoonchang
            Sung, Rahul Shome, and Peter Stone.
 In IEEE International Conference
            on Robotics and Automation (ICRA), March 2024.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (482.7kB
               )
- Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes.
 Chen
            Tang, Ben Abbatematteo, Jiaheng Hu, Rohan
            Chandra, Roberto Martín-Martín, and Peter Stone.
 Annual Review
            of Control, Robotics, and Autonomous Systems (ARCRAS), 8:153–88, 2024.
 Presented in Senior member track at
            AAAI 2025
 Official
            version on publisher's website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.3MB
               )
                [slides.pdf]
               (2.9MB
               )
                [poster.pdf]
               (604.3kB
               )
- SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions.
 Zizhao
            Wang, Jiaheng Hu, Caleb Chuck, Stephen
            Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- N-Agent Ad Hoc Teamwork.
 Caroline Wang, Arrasy
            Rahman, Ishan Durugkar, Elad
            Liebman, and Peter Stone.
 In Conference on Neural Information Processing
            Systems (NeurIPS), December 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
                [slides.pdf]
               (1.3MB
               )
                [poster.pdf]
               (1.7MB
               )
- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
 Zizhao
            Wang, Caroline Wang, Xuesu
            Xiao, Yuke Zhu, and Peter Stone.
 In
            AAAI Conference on Artificial Intelligence, February 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.5MB
               )
- LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning.
 Zifan Xu, Haozhu
            Wang, Dmitriy Bespalov, Xian Wu, Peter Stone, and Yanjun Qi.
 In Findings
            of Empirical Methods in Natural Language Processing, November 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks.
 Ziping Xu, Zifan
            Xu, Runxuan Jiang, Peter Stone, and Ambuj
            Tewari.
 In International Conference on Learning Representations (ICLR), May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
- Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning.
 Zifan
            Xu, Amir Hossain Raj, Xuesu Xiao, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
- t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making.
 William Yue,
            Bo Liu, and Peter Stone.
 In
            Conference on Lifelong Learning Agents (CoLLAs), July 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (599.7kB
               )
                [poster.pdf]
               (709.1kB
               )
- iCORPP: Interleaved commonsense reasoning and probabilistic planning on robots.
 Shiqi
            Zhang, Piyush Khandelwal, and Peter
            Stone.
 Robotics and Autonomous Systems, 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
- f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences.
 Siddhant Agarwal, Ishan
            Durugkar, Peter Stone, and Amy Zhang.
 In Conference on Neural Information
            Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (13.6MB
               )
                [poster.pdf]
               (1.8MB
               )
- Task Phasing: Automated Curriculum Learning from Demonstrations.
 Vaibhav Bajaj, Guni
            Sharon, and Peter Stone.
 In Proceedings of the 33rd International
            Conference on Automated Planning and Scheduling (ICAPS 2023), July 2023.
 Accompanying code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (416.0kB
               )
- MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection.
 Jiaxun
            Cui, Xiaomeng Yang, Mulong Luo, Geunbae
            Lee, Peter Stone, Hsien-Hsin
            S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, and
            Yuandong Tian.
 In The Eleventh International Conference on Learning
            Representations (ICLR), May 2023.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (769.8kB
               )
                [slides.pdf]
               (2.1MB
               )
                [poster.pdf]
               (1.8MB
               )
- Kinematic coordinations capture learning during human-exoskeleton interaction.
 Keya
            Ghonasgi, Reuth Mirsky, Nisha Bhargava, Adrian M Haith, Peter
            Stone, and Ashish D Deshpande.
 Scientific Reports, 13:10322, June 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.9MB
               )
- A Novel Control Law for Multi-joint Human-Robot Interaction Tasks While Maintaining Postural Coordination.
 Keya
            Ghonasgi, Reuth Mirsky, Adrian M Haith, Peter
            Stone, and Ashish D Deshpande.
 In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
            October 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
- "What's That Robot Doing Here?": Factors Influencing Perceptions Of Incidental Encounters With Autonomous Quadruped Robots.
 Elliott
            Hauser, Yao-Cheng Chan, Geethika Hemkumar, Daksh Dua, Parth Chonkar, Efren Mendoza Enriquez, Tiffany Kao, Shikhar Gupta, Huihai
            Wang, Justin Hart, Reuth Mirsky,
            Joydeep Biswas, Junfeng Jiao, and Peter
            Stone.
 In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23), pp.
            1–15, July 2023.
 Available online at https://dl.acm.org/doi/10.1145/3597512.3599707
 Details
                  
               BibTeX
                  
            Download: 
            
            (unavailable)
- Causal Policy Gradient for Whole-Body Mobile Manipulation.
 Jiaheng Hu,
            Peter Stone, and Roberto Martin-Martin.
 In Robotics: Science and Systems
            (RSS), July 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
- VaryNote: A Method to Automatically Vary the Number of Notes in           Symbolic Music.
 Juan M. Huerta, Bo
            Liu, and Peter Stone.
 In The 16th International Symposium on Computer
            Music Multidisciplinary Research, (CMMR), Springer, November 2023.
 the
            conference presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pdf]
               (2.3MB
               )
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
 Haresh
            Karnan, Elvin Yang, Daniel Farkash, Garrett
            Warnell, Joydeep Biswas, and Peter
            Stone.
 In The Conference on Robot Learning (CoRL), November 2023.
 Poster,
            Video, Project Website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (25.7MB
               )
- Models of human preference for learning reward functions.
 W. Bradley Knox,
            Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
            Stone, and Alessandro Allievi.
 Transactions on Machine Learning Research (TMLR), 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.7MB
               )
                [slides.pdf]
               (13.4MB
               )
- Reward (Mis)design for Autonomous Driving.
 W. Bradley Knox, Alessandro Allievi,
            Holger Banzhaf, Felix Schmitt, and Peter Stone.
 Artificial Intelligence,
            316:103829, 2023.
 Paper webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (696.3kB
               )
                [ps]
               (5.6MB
               )
- FAMO: Fast Adaptive Multitask Optimization.
 Bo Liu, Yihao Feng, Peter Stone, and Qiang Liu.
 In Neural Information Processing Systems Foundation,
            July 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.0MB
               )
- LIBERO: Benchmarking Knowledge Transfer in Lifelong Robot Learning.
 Bo
            Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke
            Zhu, and Peter Stone.
 In 37th Conference on Neural Information Processing
            Systems (NeurIPS 2023) Track on Datasets and Benchmarks, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (37.6MB
               )
                [poster.pdf]
               (2.6MB
               )
- Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning.
 Bo
            Liu, Yihao Feng, Qiang Liu, and Peter Stone.
 In Thirty-Seventh AAAI
            Conference on Artificial Intelligence (AAAI), Februray 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
- Exploring the Cost of Interruptions in Human-Robot Teaming.
 Swathi Mannem, William
            Macke, Peter Stone, and Reuth
            Mirsky.
 In IEEE-RAS Humanoids, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (921.5kB
               )
                [poster.pdf]
               (294.3kB
               )
- Towards a Real-Time, Low-Resource, End-to-end Object Detection Pipeline for Robot Soccer.
 Sai Kiran Narayanaswami,
            Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit
            Narvekar, and Peter Stone.
 In Amy Eguchi, Nuno Lau, Maike Paetzel-Prussman,
            and Thanapat Wanichanon, editors, RoboCup 2022: Robot World Cup XXV, pp. 62–74, Springer International Publishing,
            2023.
 The book
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (572.2kB
               )
- Program Embeddings for Rapid Mechanism Evaluation.
 Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
            and Peter Stone.
 In ICRA Workshop on Multi-Robot Learning, May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.3MB
               )
                [poster.pdf]
               (916.2kB
               )
- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
 Jinsoo Park, Xuesu
            Xiao, Garrett Warnell, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 6-minute video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.6MB
               )
                [slides.pptx]
               (21.3MB
               )
                [poster.pdf]
               (1.1MB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
- Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search.
 Yoonchang
            Sung and Peter Stone.
 In Robotics: Science and Systems (RSS2023),
            July 2023.
 Video presentation
 Details
                  
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            Download: 
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               (6.9MB
               )
                [slides.pdf]
               (8.1MB
               )
                [poster.pdf]
               (6.9MB
               )
- ELDEN: Exploration via Local Dependencies.
 Zizhao Wang, Jiaheng
            Hu, Peter Stone, and Roberto Martín-Martín.
 In Conference on Neural
            Information Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.2MB
               )
                [slides.pptx]
               (22.4MB
               )
                [poster.pdf]
               (856.5kB
               )
- D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning.
 Caroline
            Wang, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
                [slides.pdf]
               (2.4MB
               )
                [poster.pdf]
               (1.4MB
               )
- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
 Caroline
            Wang, Ishan Durugkar, Elad Liebman,
            and Peter Stone.
 In Proceedings of the 37th AAAI Conference on Artificial
            Intelligence (AAAI-23), February 2023.
 Details
                  
               BibTeX
                  
            Download: 
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               (801.2kB
               )
                [slides.pdf]
               (3.7MB
               )
                [poster.pdf]
               (1.4MB
               )
- Model-Based Meta Automatic Curriculum Learning.
 Zifan Xu, Yulin
            Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian
            Jiang, Bo Liu, and Peter Stone.
 In
            The Second Conference on Lifelong Learning Agents (CoLLAs), August 2023.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
                [slides.pptx]
               (6.6MB
               )
- Benchmarking Reinforcement Learning Techniques for Autonomous Navigation.
 Zifan
            Xu, Bo Liu, Xuesu Xiao, Anirudh
            Nair, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
- Learning Real-world Autonomous Navigation by Self-Supervised Environment Synthesis.
 Zifan
            Xu, Anirudh Nair, Xuesu Xiao, and Peter
            Stone.
 In IROS Workshop on Photorealistic Image and Environment Synthesis for Robotics (PIES-Rob) , January
            2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.3MB
               )
- Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.
 Xiaohan Zhang, Saeid Amiri,
            Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
 Autonomous
            Robots, March 2023.
 Official version
            on publisher's website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.6MB
               )
- Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu,
            Peter Stone, and Shiqi Zhang.
 In
            International Conference on Intelligent Robots and Systems (IROS), October 2023.
 Project
            website (includes poster and 5-minute video presentation)
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
                [slides.pdf]
               (6.6MB
               )
- Learning Generalizable Manipulation Policies with Object-Centric 3D Representations.
 Yifeng
            Zhu, Zhenyu Jiang, Peter Stone, and Yuke
            Zhu.
 In Conference on Robot Learning (CoRL), November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (7.3MB
               )
                [poster.pdf]
               (5.2MB
               )
- Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles.
 Jiaxun
            Cui, Hang Qiu, Dian Chen, Peter
            Stone, and Yuke Zhu.
 In IEEE/CVF Conference on Computer Vision and
            Pattern Recognition (CVPR), June 2022.
 Project website
 Details
                  
               BibTeX
                  
            Download: 
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               (3.5MB
               )
- Quantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System.
 Keya
            Ghonasgi, Reuth Mirsky, Adrian M Haith, Peter
            Stone, and Ashish D Deshpande.
 In Proceedings of the 35th International Conference on Intelligent Robots and Systems
            (IROS), October 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.4MB
               )
- Quantifying Human Rationality in Ad-hoc Teamwork.
 Yair Hanina, Reuth
            Mirsky, William Macke, and Peter
            Stone.
 In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (404.2kB
               )
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
 Eddy Hudson, Garrett
            Warnell, Faraz Torabi, and Peter
            Stone.
 In International Conference on Robotics and Automation (ICRA), May 2022.
 Presentation
            Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.5MB
               )
- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
 Haresh Karnan, Anirudh Nair, Xuesu Xiao,
            Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
            Hart, Joydeep Biswas, and Peter Stone.
 Robotics
            and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
 Dataset;
            Poster; Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
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               (4.2MB
               )
- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
 Haresh
            Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 In
            International Conference on Intelligent Robots and Systems, 2022, October 2022.
 Details
                  
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            Download: 
            [pdf]
               (3.0MB
               )
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
 Haresh
            Karnan, Garrett Warnell, Xuesu
            Xiao, and Peter Stone.
 In International Conference on Robotics and
            Automation, 2022, May 2022.
 Poster,
            Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
- Adversarial Imitation Learning from Video using a State Observer.
 Haresh
            Karnan, Garrett Warnell, Faraz
            Torabi, and Peter Stone.
 In International Conference on Robotics
            and Automation, 2022, May 2022.
 Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (933.2kB
               )
- Effective Mutation Rate Adaptation through Group Elite Selection.
 Akarsh Kumar, Bo
            Liu, Risto Miikkulainen, and Peter
            Stone.
 In Proceedings of the Genetic and Evolutionary Computation Conference, July 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.7MB
               )
- BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.
 Bo
            Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu.
 In Conference
            on Neural Information Processing Systems, 2022, December 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (1.6MB
               )
                [poster.pdf]
               (885.6kB
               )
- Continual Learning and Private Unlearning.
 Bo Liu, Qiang Liu, and Peter Stone.
 In Proceedings of the 1st Conference on Lifelong Learning Agents
            (CoLLA), August 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (440.4kB
               )
                [slides.pdf]
               (710.5kB
               )
- UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions.
 Patrick
            MacAlpine, Bo Liu, William Macke,
            Caroline Wang, and Peter Stone.
 In
            Rachid Alami, Joydeep Biswas, Maya
            Cakmak, and Oliver Obst, editors, RoboCup 2021: Robot World Cup XXIV, pp. 314–26, Springer International
            Publishing, 2022.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021
 Details
                  
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               (2.5MB
               )
- Value Function Decomposition for Iterative Design of Reinforcement Learning Agents.
 James MacGlashan, Evan Archer,
            Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2022.
 5-minute
            Video Presentation; the
            slides
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (11.6MB
               )
- A Survey of Ad Hoc Teamwork Research.
 Reuth Mirsky, Ignacio
            Carlucho, Arrasy Rahman, Eliott Fosong, William
            Macke, Mohan Sridharan, Peter
            Stone, and Stefano Albrecht.
 In Baumeister, Dorothea and Rothe, Jörg, editors,
            Multi-Agent Systems, pp. 275–93, Springer International Publishing, Cham, 2022.
 Details
                  
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            Download: 
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               (198.8kB
               )
- Task Factorization in Curriculum Learning.
 Reuth Mirsky,
            Shahaf S. Shperberg, Yulin Zhang, Zifan
            Xu, Yuqian Jiang, Jiaxun Cui, and Peter
            Stone.
 In ICML workshop on Decision Awareness in Reinforcement Learning (DARL), July 2022.
 recorded
            presentation
 Details
                  
               BibTeX
                  
            Download: 
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               (1011.6kB
               )
- Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings.
 Kingsley Nweye, Bo
            Liu, Nagy Zoltan, and Peter Stone.
 Journal of Energy and AI, 2022,
            September 2022.
 Details
                  
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            Download: 
            [pdf]
               (5.9MB
               )
- A Rule-based Shield: Accumulating Safety Rules from Catastrophic Action Effects.
 Shahaf Shperberg, Bo
            Liu, Allessandro Allievi, and Peter Stone.
 In Proceedings of the
            1st Conference on Lifelong Learning Agents (CoLLA), August 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (8.9MB
               )
- Dynamic Sparse Training for Deep Reinforcement Learning.
 Ghada Sokar, Elena
            Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy,
            and Peter Stone.
 In Proceedings of the 31st International Joint Conference
            on Artificial Intelligence, July 2022.
 arXiv version with the appendix
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.7MB
               )
                [slides.pptx]
               (16.7MB
               )
- Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning.
 Yoonchang
            Sung, Zizhao Wang, and Peter Stone.
 In
            Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Details
                  
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            Download: 
            [pdf]
               (742.0kB
               )
                [poster.pdf]
               (5.7MB
               )
- Causal Dynamics Learning for Task-Independent State Abstraction.
 Zizhao
            Wang, Xuesu Xiao, Zifan Xu, Yuke
            Zhu, and Peter Stone.
 In Proceedings of the 39th International Conference
            on Machine Learning (ICML2022), July 2022.
 recorded presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (4.0MB
               )
                [poster.pdf]
               (1.6MB
               )
- Visually Grounded Task and Motion Planning for Mobile Manipulation.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuke Zhu, Peter
            Stone, and Shiqi Zhang.
 In International Conference on Robotics
            and Automation (ICRA), May 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
- Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation.
 Yifeng
            Zhu, Peter Stone, and Yuke
            Zhu.
 IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.3MB
               )
- VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors.
 Yifeng
            Zhu, Abhishek Joshi, Peter Stone, and Yuke
            Zhu.
 In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.4MB
               )
- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
 Michael
            Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
 Operations
            Research, March 2021.
 Details
                  
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               (692.5kB
               )
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
 Roberto Capobianco, Varun Kompella, James
            Ault, Guni Sharon, Stacy
            Jong, Spencer Fox, Lauren
            Meyers, Peter R. Wurman, and Peter
            Stone.
 The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
 Contains
            material that was previously published in an AAMAS
            2021 paper and a AAAI 2020 Fall
            Symposium paper.
 Article available from  JAIR website.
 Simulator
            source code.
 Details
                  
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               (1.6MB
               )
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
 Jiaxun
            Cui, William Macke, Harel
            Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
            Stone.
 In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2021.
 Project page, with videos
 Details
                  
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            Download: 
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               (1.4MB
               )
                [slides.pptx]
               (1.5MB
               )
- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
 Yunshu Du, Garrett
            Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
            E. Taylor.
 Neural Computing and Applications, May 2021.
 Details
                  
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            Download: 
            [pdf]
               (2.2MB
               )
- Adversarial Intrinsic Motivation for Reinforcement Learning.
 Ishan Durugkar,
            Mauricio Tec, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
            December 2021.
 slides and video presentation
 Details
                  
               BibTeX
                  
            Download: 
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               (5.1MB
               )
- Capturing Skill State in Curriculum Learning for Human Skill Acquisition.
 Keya
            Ghonasgi, Reuth Mirsky, Sanmit
            Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D.
            Deshpande.
 In International Conference on Intelligent Robots and Systems (IROS), September 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Machine versus Human Attention in Deep Reinforcement Learning Tasks.
 Sihang Guo, Ruohan
            Zhang, Bo Liu, Yifeng Zhu,
            Mary Hayhoe, Dana Ballard, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2021.
 Details
                  
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            Download: 
            [pdf]
               (1.6MB
               )
- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
 Josiah
            P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
            Warnell, and Peter Stone.
 Special Issue on Reinforcement Learning
            for Real Life, Machine Learning, 2021, May 2021.
 Details
                  
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            Download: 
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               (3.0MB
               )
- Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy.
 Josiah
            P. Hanna, Scott Niekum, and Peter
            Stone.
 Machine Learning (MLJ), 110:1267–1317, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.7MB
               )
- Incorporating Gaze into Social Navigation.
 Justin Hart, Reuth
            Mirsky, Xuesu Xiao, and Peter
            Stone.
 In RSS Workshop on Social Robot Navigation, July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
                [slides.pdf]
               (3.5MB
               )
- Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation.
 Blake Holman, Abrar
            Anwar, Akash Singh, Mauricio Tec, Justin
            Hart, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.7MB
               )
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
 Eddy Hudson, Garrett
            Warnell, and Peter Stone.
 In Autonomous Robots and Multirobot Systems
            Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (393.0kB
               )
- Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle.
 Yu-Sian Jiang, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the 35th AAAI Conference
            on Artificial Intelligence (AAAI), Feb 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (911.3kB
               )
                [poster.pdf]
               (1.1MB
               )
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
 Yuqian
            Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
 In
            Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
                [slides.pdf]
               (1.8MB
               )
- A Lifelong Learning Approach to Mobile Robot Navigation.
 Bo Liu, Xuesu Xiao, and Peter Stone.
 IEEE
            Robotics and Automation Letters (RA-L), 6(2), April 2021.
 Presented at IEEE International Conference on Robotics
            and Automation (ICRA),
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.6MB
               )
- Conflict-Averse Gradient Descent for Multi-task learning.
 Bo Liu, Xingchao
            Liu, Xiaojie Jin, Peter Stone, and Qiang Liu.
 In Conference on Neural
            Information Processing Systems (NeurIPS), 2021, December 2021.
 slides
            and 9-minute presentation
 github repository
 Details
                  
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            Download: 
            [pdf]
               (9.7MB
               )
- Team  Orienteering  Coverage  Planning  with  Uncertain  Reward.
 Bo Liu,
            Xuesu Xiao, and Peter Stone.
 In
            International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.9MB
               )
- Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition.
 Bo
            Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke
            Zhu, and Animashree Anandkumar.
 In Proceedings of the 38th International Conference on Machine Learning, PMLR 139,
            2021 (ICML), July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
                [poster.pdf]
               (1.1MB
               )
- Expected Value of Communication for Planning in Ad Hoc Teamwork.
 William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (869.9kB
               )
                [slides.pdf]
               (2.3MB
               )
                [poster.pdf]
               (1.8MB
               )
- Is the Cerebellum a Model-Based Reinforcement Learning Agent?.
 Bharath Masetty, Reuth
            Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter
            Stone.
 In Adaptive and Learning Agents Workshop at AAMAS, May 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (594.9kB
               )
                [slides.pdf]
               (1.5MB
               )
- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
 Reuth
            Mirsky and Peter Stone.
 In ICSR workshop on Adaptive Social Interaction
            and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
 Details
                  
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            Download: 
            [pdf]
               (194.4kB
               )
- The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care.
 Reuth
            Mirsky and Peter Stone.
 In Proceedings of the 20th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
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            Download: 
            [pdf]
               (679.2kB
               )
- Reasoning about Human Behavior in Ad Hoc Teamwork.
 Jennifer Suriadinata, William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
 Video
            Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (926.2kB
               )
- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (742.7kB
               )
- APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback.
 Zizhao
            Wang, Xuesu Xiao, Bo Liu,
            Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), October 2021.
 5-minute
            Video Presentation;  15-minute Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pdf]
               (2.7MB
               )
- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
 Zizhao
            Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
            Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
 In Proceedings
            of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
 1-minute
            Video Summary;   15-minute Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.9MB
               )
                [slides.pdf]
               (2.7MB
               )
- APPLI: Adaptive Planner Parameter Learning From Interventions.
 Zizhao Wang,
            Xuesu Xiao, Bo Liu, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
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            Download: 
            [pdf]
               (4.2MB
               )
- APPLR: Adaptive Planner Parameter Learning from Reinforcement.
 Zifan Xu,
            Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett
            Warnell, Bo Liu, Zizhao Wang,
            and Peter Stone.
 In Proceedings of the 2021 IEEE International Conference
            on Robotics and Automation (ICRA 2021), June 2021.
 Video
            presentation
 Project webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (27.4MB
               )
- Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning.
 Zifan
            Xu, Xuesu Xiao, Garrett
            Warnell, Anirudh Nair, and Peter Stone.
 In Proceedings of the 2021
            IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), October 2021.
 Video
            presentation
 Details
                  
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            Download: 
            [pdf]
               (4.5MB
               )
- A Scavenger Hunt for Service Robots.
 Harel Yedidsion,
            Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
            Stone.
 In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
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- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
 Harel
            Yedidsion, Shani Alkoby, and Peter
            Stone.
 Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
 arXiv
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               (478.9kB
               )
- Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks.
 Ruohan
            Zhang, Faraz Torabi, Garrett
            Warnell, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems,
            35(31), June 2021.
 official online version
 Details
                  
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               (3.8MB
               )
- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
 Siddarth Desai, Ishan
            Durugkar, Haresh Karnan, Garrett
            Warnell, Josiah Hanna, and Peter
            Stone.
 In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
            December 2020.
 Poster
 Details
                  
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               )
- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
 Siddharth Desai, Haresh
            Karnan, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 11-minute video
            presentation.
 Details
                  
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               (1.9MB
               )
- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
 Ishan
            Durugkar, Elad Liebman, and Peter
            Stone.
 In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
            2020.
 Details
                  
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               (3.9MB
               )
- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
 Justin Hart,
            Reuth Mirsky, Xuesu Xiao,
            Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
            Stone.
 In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
 Video presentation
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               (3.2MB
               )
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
 Haresh
            Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 14-minute video
            presentation.
 Details
                  
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               (506.6kB
               )
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
 Shih-Yun Lo, Shiqi
            Zhang, and Peter Stone.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, October 2020.
 Contains material that was previously published in an AAMAS-18
            paper (awarded the Best Robotics Paper Award at AAMAS 2018)
 Also
            available from  JAIR website
 Details
                  
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               (4.0MB
               )
- Learning and Reasoning for Robot Dialog and Navigation Tasks.
 Keting Lu, Shiqi
            Zhang, Peter Stone, and Xiaoping
            Chen.
 In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
            107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
 Official version from ACL
            Digital Library, including a link to the conference presentation
 Details
                  
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               )
- A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork.
 Reuth
            Mirsky, William Macke, Andy Wang, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 29th International
            Joint Conference on Artificial Intelligence, July 2020.
 15-minute
            presentation
 Details
                  
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               (1.2MB
               )
                [slides.pdf]
               (1.4MB
               )
- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
 Sanmit
            Narvekar, Bei Peng, Matteo Leonetti, Jivko
            Sinapov, Matthew E. Taylor, and Peter
            Stone.
 Journal of Machine Learning Research, 21(181):1–50, 2020.
 Details
                  
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               (1.4MB
               )
- Generalizing Curricula for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In 4th Lifelong Learning Workshop at the International
            Conference on Machine Learning (ICML 2020), July 2020.
 Details
                  
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            Download: 
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               (330.4kB
               )
                [slides.pdf]
               (3.8MB
               )
- Learning to Improve Multi-Robot Hallway Navigation.
 Jin-Soo Park, Brian Tsang, Harel
            Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
 In Proceedings of the 4th Conference on Robot Learning (CoRL),
            November 2020.
 Video presentation
 Details
                  
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               (1.3MB
               )
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
 Brahma
            Pavse, Faraz Torabi, Josiah
            Hanna, Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
 Video
            of the experiments; 13-minute video presentation.
 Details
                  
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               (405.1kB
               )
                [slides.pptx]
               (115.4MB
               )
- Reducing Sampling Error in Batch Temporal Difference Learning.
 Brahma Pavse,
            Ishan Durugkar, Josiah Hanna,
            and Peter Stone.
 In Proceedings of the 37th International Conference
            on Machine Learning (ICML), July 2020.
 The paper and talk is available from the ICML
            2020 virtual conference page.
 Details
                  
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               (738.4kB
               )
                [slides.pdf]
               (5.2MB
               )
- On Sampling Error in Batch Action-Value Prediction Algorithms.
 Brahma S. Pavse,
            Josiah P. Hanna, Ishan Durugkar,
            and Peter Stone.
 In In the Offline Reinforcement Learning Workshop at
            Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
 5-minute
            Video Presentation
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               )
- Deep R-Learning for Continual Area Sweeping.
 Rishi Shah, Yuqian Jiang, Justin
            Hart, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
 1-minute
            video demonstration; 13-minute Video
            presentation.
 Details
                  
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               (374.2kB
               )
                [slides.pdf]
               (1.1MB
               )
- Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond J. Mooney.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, February 2020.
 Details
                  
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               (4.0MB
               )
- Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks.
 Lemeng Wu, Bo
            Liu, Peter Stone, and Qiang Liu.
 In Advances in Neural Information
            Processing Systems 34 (2020), December 2020.
 Details
                  
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               (8.1MB
               )
                [slides.pdf]
               (744.8kB
               )
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
 Xuesu
            Xiao, Bo Liu, Garrett
            Warnell, Jonathan Fink, and Peter Stone.
 IEEE Robotics and Automation
            Letters (RA-L), June 2020.
 Presented at International Conference on Intelligent Robots and Systems ({IROS})\\  
             5-minute Video presentation; 15-minute
            Video presentation
 Project webpage
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               (2.2MB
               )
                [slides.pdf]
               (21.1MB
               )
- Ad hoc Teamwork with Behavior Switching Agents.
 Manish Ravula, Shani Alkobi and Peter
            Stone.
 In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (350.4kB
               )
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
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               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Reducing Sampling Error in Policy Gradient Learning.
 Josiah Hanna
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 This paper contains material that was previously
            presented at the 2018 NeurIPS Deep Reinforcement Learning Workshop.
 Details
                  
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               )
                [slides.pdf]
               (3.1MB
               )
- Selecting Compliant Agents for Opt-in Micro-Tolling.
 Josiah Hanna,
            Guni Sharon, Stephen
            Boyles, and Peter Stone.
 In Proceedings of the 33rd AAAI Conference
            on Artificial Intelligence (AAAI), January 2019.
 Details
                  
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               (2.2MB
               )
- Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems.
 Yuqian
            Jiang, Shiqi Zhang, Piyush
            Khandelwal, and Peter Stone.
 Frontiers of Information Technology
            and Electronic Engineering, 20(3):363–373, Springer, March 2019.
 Official version from Publisher's
            Webpage
 Details
                  
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               (412.1kB
               )
- Multi-Robot Planning with Conflicts and Synergies.
 Yuqian Jiang, Harel
            Yedidsion, Shiqi Zhang, Guni
            Sharon, and Peter Stone.
 Autonomous Robots, Springer, March 2019.
 Official version from Publisher's Webpage
 Details
                  
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               (2.0MB
               )
- Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
 Yuqian
            Jiang, Fangkai Yang, Shiqi
            Zhang, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
 Details
                  
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               (925.2kB
               )
- Open-World Reasoning for Service Robots.
 Yuqian Jiang, Nick
            Walker, Justin Hart, and Peter Stone.
 In
            Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
 Accompanying video
 Details
                  
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               (813.5kB
               )
- The right music at the right time: adaptive personalized playlists based on sequence modeling.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone Peter Stone.
 Management Information Systems Quarterly, 43(3):765–786, Society for Information Management
            and The Management Information Systems Research Center, 2019.
 Available from publisher's
            website.
 Details
                  
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               (4.0MB
               )
- UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions.
 Patrick
            MacAlpine, Faraz Torabi, Brahma
            Pavse, and Peter Stone.
 In Stephan Chalup, Tim Niemueller, Jackrit Suthakorn,
            and Mary-Anne Williams, editors, RoboCup 2019: Robot World Cup XXIII, Lecture Notes in Artificial Intelligence, pp.
            540–52, Springer, 2019.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2019
 Details
                  
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               (233.2kB
               )
                [ps]
               (3.8MB
               )
- UT Austin Villa: RoboCup 2018 3D Simulation League Champions.
 Patrick
            MacAlpine, Faraz Torabi, Brahma
            Pavse, John Sigmon, and Peter Stone.
 In Dirk Holz, Katie
            Genter, Maarouf Saad, and Oskar von Stryk, editors,
            RoboCup 2018: Robot Soccer World Cup XXII, Lecture Notes in Artificial Intelligence, pp. 462–75, Springer, 2019.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2018
 Details
                  
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               (486.2kB
               )
                [ps]
               (6.0MB
               )
- Learning Curriculum Policies for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 Details
                  
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            Download: 
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               (953.0kB
               )
                [slides.pdf]
               (5.6MB
               )
- Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report.
 Rishi Shah, Yuqian
            Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta,
            Rachel Schlossman, Marika Murphy, Justin Hart, Luis
            Sentis, and Peter Stone.
 In AAAI Fall Symposium on Artificial Intelligence
            and Human-Robot Interaction for Service Robots in Human Environments (AI-HRI 2019), November 2019.
 Details
                  
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               (4.5MB
               )
- Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks.
 Guni
            Sharon, Stephen D. Boyles, Shani
            Alkoby, and Peter Stone.
 In Proceedings of the 18th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS-19), May 2019.
 Details
                  
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               (1.7MB
               )
                [slides.pptx]
               (6.5MB
               )
- Agents teaching agents: a survey on inter-agent transfer learning.
 Felipe Leno
            Da Silva, Garrett Warnell, Anna
            Helena Reali Costa, and Peter Stone.
 Autonomous Agents and Multi-Agent
            Systems, Dec 2019.
 Official version from JAAMAS
 Details
                  
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               (572.4kB
               )
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
 Felipe
            Leno Da Silva, Anna Helena Reali Costa, and Peter
            Stone.
 In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
 Details
                  
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               (1.6MB
               )
- Improving Grounded Natural Language Understanding through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond Mooney.
 In Proceedings of the International Conference on
            Robotics and Automation (ICRA 2019), May 2019.
 Details
                  
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               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
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               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
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               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (6.1MB
               )
- Desiderata for Planning Systems in General-Purpose Service Robots.
 Nick Walker,
            Yuqian Jiang, Maya Cakmak, and
            Peter Stone.
 In Proceedings of the ICAPS Workshop on Planning and Robotics
            (PlanRob 2019), July 2019.
 Details
                  
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               (651.5kB
               )
- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
 Harel
            Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
            Stone, and Raymond Mooney.
 In International Conference on Social
            Robotics (ICSR), pp. 133–143, November 2019.
 Details
                  
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               (958.6kB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems.
 Stefano
            Albrecht and Peter Stone.
 Artificial Intelligence, 258:66–95,
            Elsevier, 2018.
 Available from the publisher's webpage and
            arXiv
 Details
                  
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               (670.7kB
               )
- Multi-modal Predicate Identification using Dynamically Learned Robot Controllers.
 Saeid Amiri, Suhua Wei, Shiqi
            Zhang, Jivko Sinapov, Jesse Thomason,
            and Peter Stone.
 In Proceedings of the 27th International Joint Conference
            on Artificial Intelligence (IJCAI-18), July 2018.
 Details
                  
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               (2.5MB
               )
- DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
 Haipeng
            Chen, Bo An, Guni Sharon, Josiah
            P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
 In Proceedings
            of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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               (2.4MB
               )
                [ps]
               (5.9MB
               )
- Passive Demonstrations of Light-Based Robot Signals for Improved Human Interpretability.
 Rolando Fernandez, Nathan
            John, Sean Kirmani, Justin Hart, Jivko
            Sinapov, and Peter Stone.
 In Proceedings of the 27th IEEE International
            Symposium on Robot and Human Interactive Communication (RO-MAN), August 2018.
 Details
                  
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               (8.5MB
               )
                [slides.pdf]
               (983.4kB
               )
- Towards a Data Efficient Off-Policy Policy Gradient.
 Josiah Hanna
            and Peter Stone.
 In AAAI Spring Symposium on Data Efficient Reinforcement
            Learning, March 2018.
 Details
                  
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               (345.4kB
               )
- PRISM:  Pose  Registration  for  Integrated  Semantic  Mapping.
 Justin W. Hart,
            Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter
            Stone.
 In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
            October 2018.
 Details
                  
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               (4.4MB
               )
- Inferring User Intention using Gaze in Vehicles.
 Yu-Sian Jiang, Garrett
            Warnell, and Peter Stone.
 In The 20th ACM International Conference
            on Multimodal Interaction (ICMI), October 2018.
 Based on an earlier version presented at the AAAI
            PAIR workshop
 Details
                  
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               (2.6MB
               )
- A Study of Human-Robot Copilot Systems for En-Route Destination Changing.
 Yu-Sian Jiang, Garrett
            Warnell, Eduardo Munera, and Peter Stone.
 In Proceedings of the 27th
            IEEE International Conference on Robot and Human Interactive Communication (RO-MAN2018), August 2018.
 Available
            from RO-MAN
 Details
                  
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               (5.8MB
               )
                [slides.pptx]
               (32.7MB
               )
- Bringing Smart Transport to Texans:  Ensuring the Benefits of a	Connected and Autonomous Transport System in Texas ---
            Final Report.
 Kara Kockelman, Stephen Boyles, Purser
            Sturgeon, Christian Claudel, Lisa Loftus-Otway, Wendy Wagner, Duncan Stewart, Guni
            Sharon, Michael Albert, Peter
            Stone, Josiah Hanna, Yantao Huang, Krishna Murthy Gurumurthy, Dongxu
            He, Abduallah Mohamed, Rahul Patel, Tian Lei, Michele Simoni, and Sadegh Yarmohammadisatri.
 Technical Report 0-6838-3,
            The University of Texas at Austin Center for Transportation Research, 2018.
 Available
            online
 Details
                  
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            (unavailable)
- A Stitch in Time - Autonomous Model Management via Reinforcement Learning.
 Elad
            Liebman, Eric Zavesky, and Peter Stone.
 In Proceedings of the 17th
            International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018.
 Details
                  
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               (1.7MB
               )
- On the Impact of Music on Decision Making in Cooperative Tasks.
 Elad
            Liebman, Corey N. White, and Peter
            Stone.
 In 19th International Society for Music Information retrieval Conference (ISMIR), September 2018.
 Details
                  
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               (258.5kB
               )
- Overlapping Layered Learning.
 Patrick MacAlpine and Peter
            Stone.
 Artificial Intelligence, 254:21–43, Elsevier, January 2018.
 Official version from Publisher's
            Webpage
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/overlappingLayeredLearning.html
 Details
                  
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               (1.2MB
               )
                [ps]
               (3.8MB
               )
- UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions.
 Patrick
            MacAlpine and Peter Stone.
 In Claude Sammut, Oliver Obst, Flavio Tonidandel,
            and Hidehisa Akyama, editors, RoboCup 2017: Robot Soccer World Cup XXI, Lecture Notes in Artificial Intelligence, pp.
            473–85, Springer, 2018.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2017
 Details
                  
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               (973.5kB
               )
                [ps]
               (19.4MB
               )
- State Abstraction Synthesis for Discrete Models of Continuous Domains.
 Jacob
            Menashe and Peter Stone.
 In Data Efficient Reinforcement Learning
            Workshop at AAAI Spring Symposium, March 2018.
 Details
                  
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               (538.3kB
               )
                [ps]
               (5.3MB
               )
- Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science.
 Decebal Constantin Mocanu, Elena
            Mocanu, Peter Stone, Phuong
            H. Nguyen, Madeleine Gibescu, and Antonio
            Liotta.
 Nature Communications, 9(2383), June 2018.
 Official version from Publisher's
            Webpage.
 Details
                  
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               (1.5MB
               )
- Deterministic Implementations for Reproducibility in Deep Reinforcement Learning.
 Prabhat Nagarajan, Garrett
            Warnell, and Peter Stone.
 In 2nd Reproducibility in Machine Learning
            Workshop at ICML 2018, July 2018.
 Details
                  
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               (6.6MB
               )
- Variety Wins: Soccer-Playing Robots and Infant Walking.
 Ori Ossmy, Justine E. Hoch, Patrick
            MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph.
 Frontiers
            in Neurorobotics, 12:19, 2018.
 Available from the publisher's
            webpage
 Details
                  
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               (2.9MB
               )
- Learning a Policy for Opportunistic Active Learning.
 Aishwarya Padmakumar, Peter
            Stone, and Raymond J. Mooney.
 In Proceedings of the Conference on
            Empirical Methods in Natural Language Processing (EMNLP-18), Brussels, Belgium, November 2018.
 Details
                  
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               (394.3kB
               )
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
 Tarun
            Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
            and Peter Stone.
 Transportation Research Part B: Methodological,
            110:104–21, 2018.
 Official version from Publisher's
            Webpage
 Details
                  
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               )
- Traffic Optimization For a Mixture of Self-interested and Compliant Agents.
 Guni
            Sharon, Michael Albert, Tarun
            Rambha, Stephen Boyles, and Peter
            Stone.
 In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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               (1002.7kB
               )
                [ps]
               (5.2MB
               )
                [slides.pptx]
               (11.1MB
               )
- Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions.
 Jesse
            Thomason, Jivko Sinapov, Raymond
            J. Mooney, and Peter Stone.
 In Proceedings of the 32nd Conference
            on Artificial Intelligence (AAAI), February 2018.
 Details
                  
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               (1.4MB
               )
- Deep TAMER: Interactive agent shaping in high-dimensional state spaces.
 Garrett
            Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone.
 In Proceedings
            of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2018.
 Details
                  
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               (1.6MB
               )
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               (16.2MB
               )
- Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?.
 Michael
            Albert, Vincent Conitzer, and Peter Stone.
 In Proceedings of the
            16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), May 2017.
 Details
                  
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               (348.6kB
               )
                [slides.pdf]
               (2.8MB
               )
- Automated Design of Robust Mechanisms.
 Michael Albert, Vincent
            Conitzer, and Peter Stone.
 In Proceedings of the Thirty-First AAAI Conference
            on Artificial Intelligence (AAAI-17), Feb 2017.
 Details
                  
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               (366.4kB
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               )
- Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial.
 Stefano
            Albrecht, Somchaya Liemhetcharat, and Peter Stone.
 Autonomous Agents
            and Multi-Agent Systems, 31(4):765–66, July 2017.
 Official version from Publisher's
            Webpage
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               (304.3kB
               )
- Reasoning about Hypothetical Agent Behaviours and their Parameters.
 Stefano Albrecht
            and Peter Stone.
 In Proceedings of the 16th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
 Available from IFAAMAS
            and from ACM
 Details
                  
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               (608.2kB
               )
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               (1.2MB
               )
- TD Learning with Constrained Gradients.
 Ishan Durugkar and Peter
            Stone.
 In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017, December 2017.
 Details
                  
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               (381.4kB
               )
- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
            Ad Hoc Teamwork Robotics Competition.
 Katie Genter, Tim
            Laue, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems
            (JAAMAS), 31(4):790–820, Springer, July 2017.
 Official version from Publisher's
            Webpage
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               (1.2MB
               )
- CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression.
 Santiago Gonzalez,
            Vijay Chidambaram, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '17),
            July 2017.
 Details
                  
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               (241.6kB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            Hanna, Philip Thomas, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
 Details
                  
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               )
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               (1.1MB
               )
- Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
 Josiah
            Hanna, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2017.
 Details
                  
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               (663.8kB
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                [ps]
               (572.6kB
               )
                [slides.pdf]
               (1.3MB
               )
- Grounded Action Transformation for Robot Learning in Simulation.
 Josiah
            Hanna and Peter Stone.
 In Proceedings of the 31st AAAI Conference
            on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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               (1.3MB
               )
                [slides.pdf]
               (1.3MB
               )
- Machine Learning Capabilities of a Simulated Cerebellum.
 Matthew Hausknecht,
            Wen-Ke Li, Michael Mauk, and Peter Stone.
 "IEEE
            Transactions on Neural Networks and Learning Systems", 28(3):510–22, March 2017.
 Details
                  
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               (1.1MB
               )
- Intrinsically motivated model learning for developing curious robots.
 Todd
            Hester and Peter Stone.
 Artificial Intelligence, 247:170–86,
            June 2017.
 from journal website.
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               (1.4MB
               )
- BWIBots: A platform for bridging the gap between AI and human--robot interaction research.
 Piyush
            Khandelwal, Shiqi Zhang, Jivko
            Sinapov, Matteo Leonetti, Jesse Thomason,
            Fangkai Yang, Ilaria Gori, Maxwell Svetlik, Priyanka Khante, Vladimir
            Lifschitz, J. K. Aggarwal, Raymond Mooney, and Peter
            Stone.
 The International Journal of Robotics Research, 36(5--7):635–59, 2017.
 Accompanying videos
            at https://youtu.be/2UJG4-ejVww
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               (4.4MB
               )
- Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests.
 Piyush
            Khandelwal and Peter Stone.
 In International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2017.
 Details
                  
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               (1.8MB
               )
- An Assessment of Autonomous Vehicles:  Traffic Impacts and  Infrastructure Needs --- Final Report.
 Kara Kockelman,
            Stephen Boyles, Peter
            Stone, Dan Fagnant, Rahul  Patel, Michael W.
            Levin, Guni Sharon, Michele Simoni, Michael
             Albert, Hagen Fritz, Rebecca Hutchinson, Prateek Bansal, Gelb  Domnenko, Pavle Bujanovic, Bumsik Kim, Elaham Pourrahmani,
            Sudesh  Agrawal, Tianxin Li, Josiah Hanna, Aqshems Nichols, and Jia Li.
 Technical
            Report 0-6847-1, The University of Texas at Austin Center for Transportation Research, 2017.
 Available
            online
 Details
                  
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- Designing Better Playlists with Monte Carlo Tree Search.
 Elad Liebman,
            Piyush Khandelwal, Maytal
            Saar-Tsechansky, and Peter Stone.
 In Proceedings of the Twenty-Ninth
            Conference On Innovative Applications Of Artificial Intelligence (IAAI-17), February 2017.
 Details
                  
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               (377.0kB
               )
- Iterative Human-Aware Mobile Robot Navigation.
 Shih-Yun Lo, Benito Fernandez, and Peter
            Stone.
 In Proceedings of the Human-Centered Robotics workshop of the 13th International Conference on Robotics:
            Science and System (RSS), July 2017.
 Details
                  
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               (2.0MB
               )
- Leveraging Commonsense Reasoning and Multimodal Perception for Robot    Spoken Dialog Systems.
 Dongcai Lu, Shiqi
            Zhang, Peter Stone, and Xiaoping
            Chen.
 In Proceedings of the IEEE/RSJ International Conference on    Intelligent Robots and Systems (IROS), September
            2017.
 Details
                  
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               (1.6MB
               )
- Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges.
 Patrick
            MacAlpine and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 168–86, Springer International Publishing, 2017.
 Details
                  
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               (518.7kB
               )
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               (2.6MB
               )
                [slides.pdf]
               (45.5MB
               )
- UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions.
 Patrick
            MacAlpine and Peter Stone.
 In Sven Behnke, Daniel
            D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
            Intelligence, pp. 515–28, Springer, 2017.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2016
 Details
                  
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                [ps]
               (14.4MB
               )
- Prioritized Role Assignment for Marking.
 Patrick MacAlpine and Peter Stone.
 In Sven Behnke, Daniel
            D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
            Intelligence, pp. 306–18, Springer Verlag, Berlin, 2017.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2016/html/marking.html
 Details
                  
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               (1.7MB
               )
                [ps]
               (13.5MB
               )
                [slides.pdf]
               (157.3MB
               )
- UT Austin Villa RoboCup 3D Simulation Base Code Release.
 Patrick MacAlpine
            and Peter Stone.
 In Sven Behnke, Daniel
            D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
            Intelligence, pp. 135–43, Springer Verlag, Berlin, 2017.
 Code release at https://github.com/LARG/utaustinvilla3d
 Details
                  
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               (394.2kB
               )
                [ps]
               (2.1MB
               )
                [slides.pdf]
               (107.1MB
               )
- Fast and Precise Black and White Ball Detection for RoboCup Soccer.
 Jacob
            Menashe, Josh Kelle, Katie Genter, Josiah
            Hanna, Elad Liebman, Sanmit
            Narvekar, Ruohan Zhang, and Peter
            Stone.
 In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
 Details
                  
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               (254.2kB
               )
                [ps]
               (716.1kB
               )
                [slides.pdf]
               (1.5MB
               )
- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
 Sanmit
            Narvekar, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
            2017.
 Details
                  
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               (826.2kB
               )
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               )
- Network-wide Adaptive Tolling for Connected and Automated vehicles.
 Guni
            Sharon, Michael W. Levin, Josiah
            P. Hanna, Tarun Rambha, Stephen
            D. Boyles, and Peter Stone.
 Transportation Research Part C, 84:142–157,
            September 2017.
 Transportation Research Part C.
 Audio slides.
 Contains material
            that was previously published in an AAMAS-17 paper.
 Details
                  
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               )
                [ps]
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               )
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
 Guni
            Sharon and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
 Details
                  
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               (1.1MB
               )
                [ps]
               (7.1MB
               )
                [slides.pptx]
               (140.9MB
               )
- Automatic Curriculum Graph Generation for Reinforcement Learning Agents.
 Maxwell Svetlik, Matteo
            Leonetti, Jivko Sinapov, Rishi Shah, Nick
            Walker, and Peter Stone.
 In Proceedings of the 31st AAAI Conference
            on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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               (2.0MB
               )
- Opportunistic Active Learning for Grounding Natural Language Descriptions.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Justin
            Hart, Peter Stone, and Raymond
            J. Mooney.
 In Proceedings of the 1st Annual Conference on Robot Learning (CoRL-17), pp. 67–76, PMLR, Mountain
            View, California, November 2017.
 Details
                  
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               (1.2MB
               )
- Multirobot Symbolic Planning under Temporal Uncertainty.
 Shiqi Zhang,
            Yuqian Jiang, Guni Sharon, and Peter
            Stone.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS),
            May 2017.
 Accompanying videos at https://youtu.be/ADbH3sppLHQ
 Details
                  
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               (2.3MB
               )
- Dynamically Constructed (PO)MDPs for Adaptive Robot Planning.
 Shiqi
            Zhang, Piyush Khandelwal, and Peter
            Stone.
 In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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               (3.2MB
               )
- Autonomous Intersection Management for Semi-Autonomous Vehicles.
 Tsz-Chiu
            Au, Shun Zhang, and Peter
            Stone.
 In Dusan Teodorovi'c, editors, Handbook of Transportation, pp. 88–104, Routledge, 2016.
 Details
                  
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               (2.6MB
               )
- Making Friends on the Fly: Cooperating with New Teammates.
 Samuel Barrett,
            Avi Rosenfeld, Sarit Kraus,
            and Peter Stone.
 Artificial Intelligence, October 2016.
 Official version from journal website.
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               (917.9kB
               )
- State Aggregation through Reasoning in Answer Set Programming.
 Ginevra Gaudioso, Matteo
            Leonetti, and Peter Stone.
 In Proceedings of the IJCAI Workshop on
            Autonomous Mobile Service Robots (WSR 16), July 2016.
 Details
                  
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               (776.6kB
               )
- Ad Hoc Teamwork Behaviors for Influencing a Flock.
 Katie Genter and
            Peter Stone.
 Acta Polytechnica, 56(1), 2016.
 Details
                  
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               (421.5kB
               )
                [ps]
               (1.6MB
               )
- Adding Influencing Agents to a Flock.
 Katie Genter and Peter
            Stone.
 In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-16),
            May 2016.
 Details
                  
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               (1.2MB
               )
                [ps]
               (4.5MB
               )
                [slides.pdf]
               (433.7kB
               )
- Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication.
 Jonathan Grizou, Samuel
            Barrett, Manuel Lopes, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
 Details
                  
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               (339.0kB
               )
- Minimum Cost Matching for Autonomous Carsharing.
 Josiah P. Hanna,
            Michael Albert, Donna
            Chen, and Peter Stone.
 In Proceedings of the 9th IFAC Symposium on
            Intelligent Autonomous Vehicles (IAV 2016), June 2016.
 Details
                  
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               (117.5kB
               )
                [ps]
               (355.2kB
               )
                [slides.pdf]
               (4.7MB
               )
- Deep Reinforcement Learning in Parameterized Action Space.
 Matthew Hausknecht
            and Peter Stone.
 In Proceedings of the International Conference on Learning
            Representations (ICLR), May 2016.
 Details
                  
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               (468.3kB
               )
- Grounded Semantic Networks for Learning Shared Communication Protocols.
 Matthew
            Hausknecht and Peter Stone.
 In Deep Reinforcement Learning, NIPS
            Workshop, December 2016.
 Details
                  
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               (899.9kB
               )
- On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning.
 Matthew
            Hausknecht and Peter Stone.
 In Deep Reinforcement Learning: Frontiers
            and Challenges, IJCAI Workshop, July 2016.
 Details
                  
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               (2.5MB
               )
- Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork.
 Matthew
            Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan,
            and Peter Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop,
            May 2016.
 Details
                  
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               (253.9kB
               )
- Deep Imitation Learning for Parameterized Action Spaces.
 Matthew Hausknecht,
            Yilun Chen, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
 Details
                  
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               (483.4kB
               )
- Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines.
 Kazunori
            Iwata, Elad Liebman, Peter Stone,
            Toyoshiro Nakashima, Yoshiyuki Anan, and Naohiro Ishii.
 In Roger
            Lee, editors, Computer and Information Science 2015, Studies in Computational Intelligence, Springer Verlag, Berlin,
            2016.
 Details
                  
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               (807.5kB
               )
- On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search.
 Piyush
            Khandelwal, Elad Liebman, Scott
            Niekum, and Peter Stone.
 In Proceedings of The 33rd International
            Conference on Machine Learning, pp. 1319–1328, June 2016.
 Details
                  
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               (1.3MB
               )
                [slides.pdf]
               (1.7MB
               )
- Bringing Smart Transport to Texans:  Ensuring the Benefits of a	Connected and Autonomous Transport System in Texas ---
            Final Report.
 Kara Kockelman, Stephen Boyles, Paul
            Avery, Christian Claudel, Lisa	Loftus-Otway, Daniel Fagnant, Prateek Bansal, Michael
            Levin, Yong Zhao, Jun Liu, Lewis Clements, Wendy Wagner, Duncan Stewart, Guni
            Sharon, Michael Albert, Peter
            Stone, Josiah Hanna, Rahul Patel, Hagen Fritz, Tejas Choudhary, Tianxin
            Li, Aqshems Nichols, Kapil Sharma, and Michele Simoni.
 Technical Report 0-6838-2, The University of Texas at Austin Center
            for Transportation Research, 2016.
 Available online
 Details
                  
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            (unavailable)
- A synthesis of automated planning and reinforcement learning for efficient, robust decision-making.
 Matteo
            Leonetti, Luca Iocchi, and Peter Stone.
 Artificial Intelligence,
            241:103 – 130, September 2016.
 Details
                  
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               (3.2MB
               )
- A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer.
 David
            L. Leottau, Javier Ruiz-del-Solar, Patrick
            MacAlpine, and Peter Stone.
 In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
            and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2016.
 Details
                  
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               (625.8kB
               )
- Impact of Music on Decision Making in Quantitative Tasks.
 Elad Liebman,
            Peter Stone, and Corey
            N. White.
 In 17th International Society for Music Information retrieval Conference (ISMIR), August 2016.
 Details
                  
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               (591.1kB
               )
                [slides.pdf]
               (678.6kB
               )
- UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.
 Patrick
            MacAlpine, Josiah Hanna, Jason
            Liang, and Peter Stone.
 In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
            and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2016.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2015
 Details
                  
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               (790.2kB
               )
                [ps]
               (7.2MB
               )
- Adaptation of Surrogate Tasks for Bipedal Walk Optimization.
 Patrick
            MacAlpine, Elad Liebman, and Peter
            Stone.
 In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.
 Details
                  
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               (172.1kB
               )
                [ps]
               (739.5kB
               )
                [slides.pdf]
               (165.0MB
               )
- Source Task Creation for Curriculum Learning.
 Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti,
            and Peter Stone.
 In Proceedings of the 15th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
 Details
                  
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               (630.0kB
               )
                [slides.pdf]
               (10.2MB
               )
- Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors.
 Jivko
            Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone.
 In Proceedings
            of the 25th International Joint Conference on Artificial  Intelligence (IJCAI), July 2016.
 Details
                  
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               (6.6MB
               )
                [slides.pdf]
               (5.2MB
               )
- Learning Multi-Modal Grounded Linguistic Semantics by Playing I Spy.
 Jesse Thomason,
            Jivko Sinapov, Maxwell Svetlik, Peter
            Stone, and Raymond Mooney.
 In Proceedings of the 25th international
            joint conference on Artificial Intelligence (IJCAI), July 2016.
 Demo Video
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               (3.1MB
               )
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               (1.0MB
               )
- An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis.
 Daniel
            Urieli and Peter Stone.
 In Proceedings of the 15th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
 Details
                  
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               (11.9MB
               )
- Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market.
 Daniel
            Urieli and Peter Stone.
 In Proceedings of the 30th Conference on
            Artificial Intelligence (AAAI 2016), February 2016.
 Details
                  
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               (1.2MB
               )
- Robot Scavenger Hunt: A Standardized Framework for Evaluating  Intelligent Mobile Robots.
 Shiqi
            Zhang, Dongcai Lu, Xiaoping Chen, and Peter
            Stone.
 In Proceedings of the International Joint Conference on Artificial  Intelligence (IJCAI), July 2016.
 Details
                  
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               (326.5kB
               )
- Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork.
 Samuel
            Barrett and Peter Stone.
 In Proceedings of the Twenty-Ninth AAAI
            Conference on Artificial Intelligence, January 2015.
 Details
                  
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               (993.2kB
               )
                [ps]
               (2.8MB
               )
- Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League.
 Mike Depinet, Patrick MacAlpine,
            and Peter Stone.
 In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian
            Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot Soccer World Cup XVIII, Lecture Notes in Artificial
            Intelligence, Springer Verlag, Berlin, 2015.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/learningFromObservation.html
 Details
                  
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               )
                [ps]
               (42.3MB
               )
- When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing.
 Fei
            Fang, Peter Stone, and Milind
            Tambe.
 In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
 Winner of Computational Sustainability Track Outstanding Paper Award at IJCAI 2015
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                [ps]
               (983.9kB
               )
                [slides.pptx]
               (6.2MB
               )
- Determining Placements of Influencing Agents in a Flock.
 Katie Genter,
            Shun Zhang, and Peter Stone.
 In
            Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
 Details
                  
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               (1.4MB
               )
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               (1.6MB
               )
- Robot-centric Activity Recognition 'in the Wild'.
 Ilaria Gori, Jivko
            Sinapov, Priyanka Khante, Peter Stone, and J.K. Aggarwal.
 In Proceedings
            of the International Conference on Social Robotics (ICSR), October 2015.
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               )
- The Impact of Determinism on Learning Atari 2600 Games.
 Matthew Hausknecht
            and Peter Stone.
 In AAAI Workshop on Learning for General Competency
            in Video Games, January 2015.
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               (65.1kB
               )
- Deep Recurrent Q-Learning for Partially Observable MDPs.
 Matthew Hausknecht
            and Peter Stone.
 In AAAI Fall Symposium on Sequential Decision Making
            for Intelligent Agents (AAAI-SDMIA15), November 2015.
 Details
                  
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               (1.5MB
               )
                [slides.pdf]
               (3.8MB
               )
- Leading the Way: An Efficient Multi-robot Guidance System.
 Piyush Khandelwal,
            Samuel Barrett, and Peter Stone.
 In
            International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
 Accompanying videos at
            https://www.youtube.com/watch?v=os1BjHgM5ao&feature=youtu.be
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               )
- Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance.
 W. Bradley Knox and Peter Stone.
 Artificial
            Intelligence, 225(), August 2015.
 Artificial
            Intelligence
 Contains material that was previously published in a IUI 2013 paper and a RoMan 2012 paper that was nominated as a CoTeSys Cognitive Robotics BEST PAPER AWARD FINALIST.
 Details
                  
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               (3.9MB
               )
- Representative Selection in Nonmetric Datasets.
 Elad Liebman, Benny Chor, and Peter Stone.
 "Applied
            Artificial Intelligence", 29:807–838, 2015.
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               (846.3kB
               )
- How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification.
 Elad
            Liebman, Peter Stone, and Corey
            N. White.
 In 16th International Society for Music Information retrieval Conference (ISMIR), October 2015.
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               (832.6kB
               )
                [ps]
               (6.3MB
               )
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               (2.0MB
               )
- DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone.
 In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2015.
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               (1.5MB
               )
                [ps]
               (38.4MB
               )
                [slides.pdf]
               (2.6MB
               )
- UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions.
 Patrick
            MacAlpine, Mike Depinet, Jason
            Liang, and Peter Stone.
 In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot
            Soccer World Cup XVIII, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2015.
 Accompanying videos
            at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2014
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               (1.9MB
               )
- UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning.
 Patrick
            MacAlpine, Mike Depinet, and Peter
            Stone.
 In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 2842–48,
            January 2015.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/overlappingLayeredLearning.html
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               (2.5MB
               )
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               (105.3MB
               )
- SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning.
 Patrick
            MacAlpine, Eric Price, and Peter
            Stone.
 In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/scram.html
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               )
                [ps]
               (676.5kB
               )
                [slides.pdf]
               (40.3MB
               )
- Monte Carlo Hierarchical Model Learning.
 Jacob Menashe and Peter Stone.
 In Proceedings of the 14th International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2015.
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               )
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               (18.4MB
               )
- Learning Inter-Task Transferability in the Absence of Target  Task Samples.
 Jivko
            Sinapov, Sanmit Narvekar, Matteo
            Leonetti, and Peter Stone.
 In Proceedings of the International Conference
            on Autonomous  Agents and Multiagent Systems (AAMAS), 2015.
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               )
- Learning to Interpret Natural Language Commands through Human-Robot    Dialog.
 Jesse
            Thomason, Shiqi Zhang, Raymond
            Mooney, and Peter Stone.
 In Proceedings of the 2015 International
            Joint Conference on    Artificial Intelligence (IJCAI), July 2015.
 Demo
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               )
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               )
- Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy.
 Shiqi
            Zhang, Fangkai Yang, Piyush
            Khandelwal, and Peter Stone.
 In Proceedings of the 13th International
            Conference on Logic     Programming and Non-monotonic Reasoning (LPNMR), September 2015.
 Demo Video
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               )
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               )
- CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied      to Dialog with a Mobile Robot.
 Shiqi
            Zhang and Peter Stone.
 In Proceedings of the 29th Conference on Artificial
            Intelligence (AAAI), January 2015.
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               (306.0kB
               )
                [ps]
               (1.5MB
               )
- Modeling Uncertainty in Leading Ad Hoc Teams.
 Noa Agmon, Samuel
            Barrett, and Peter Stone.
 In Proc. of 13th Int. Conf. on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2014.
 Details
                  
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               )
                [ps]
               (1.7MB
               )
- Communicating with Unknown Teammates.
 Samuel Barrett, Noa
            Agmon, Noam Hazon, Sarit Kraus,
            and Peter Stone.
 In Proceedings of the Twenty-First European Conference
            on Artificial Intelligence, August 2014.
 Details
                  
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               (2.6MB
               )
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               (1.4MB
               )
- Influencing a Flock via Ad Hoc Teamwork.
 Katie Genter and Peter
            Stone.
 In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
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               (358.4kB
               )
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               )
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               (15.3MB
               )
- A Neuroevolution Approach to General Atari Game Playing.
 Matthew Hausknecht,
            Joel Lehman, Risto Miikkulainen, and Peter Stone.
 IEEE Transactions on Computational Intelligence and AI in Games,
            2014.
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               (1.3MB
               )
                [ps]
               (3.1MB
               )
- Planning in Action Language $\cal BC$ while Learning Action Costs    for Mobile Robots.
 Piyush
            Khandelwal, Fangkai Yang, Matteo
            Leonetti, Vladimir    Lifschitz, and Peter
            Stone.
 In International Conference on Automated Planning and Scheduling    (ICAPS), June 2014.
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               )
                [ps]
               (6.0MB
               )
- Multi-robot Human Guidance using Topological Graphs.
 Piyush Khandelwal
            and Peter Stone.
 In AAAI Spring 2014 Symposium on Qualitative Representations
            for Robots (AAAI-SSS), March 2014.
 Details
                  
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               (1.1MB
               )
                [ps]
               (7.6MB
               )
- The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork.
 Patrick
            MacAlpine, Katie Genter, Samuel
            Barrett, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS), September 2014.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/dropin.html
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               )
                [ps]
               (4.0MB
               )
                [slides.pdf]
               (30.4MB
               )
- TacTex'13: A Champion Adaptive Power Trading Agent.
 Daniel Urieli
            and Peter Stone.
 In Proceedings of the Twenty-Eighth Conference on Artificial
            Intelligence (AAAI 2014), July 2014.
 Details
                  
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               (257.8kB
               )
                [ps]
               (7.3MB
               )
                [slides.pdf]
               (3.8MB
               )
- Planning in Answer Set Programming while Learning Action Costs for    Mobile Robots.
 Fangkai
            Yang, Piyush Khandelwal, Matteo
            Leonetti, and Peter Stone.
 In AAAI Spring 2014 Symposium on Knowledge
            Representation and Reasoning in Robotics (AAAI-SSS), March 2014.
 Details
                  
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               )
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               (5.3MB
               )
- The 2012 UT Austin Villa Code Release.
 Samuel Barrett, Katie
            Genter, Yuchen He, Todd
            Hester, Piyush Khandelwal, Jacob
            Menashe, and Peter Stone.
 In RoboCup-2013: Robot Soccer World Cup
            XVII, Springer Verlag, 2013.
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               )
- UT Austin Villa 2012: Standard Platform League World Champions.
 Samuel
            Barrett, Katie Genter, Yuchen
            He, Todd Hester, Piyush Khandelwal,
            Jacob Menashe, and Peter Stone.
 In
            Xiaoping Chen, Peter
            Stone, Luis Enrique Sucar, and Tijn
            Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2013.
 Details
                  
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               )
                [ps]
               (15.0MB
               )
- Teamwork with Limited Knowledge of Teammates.
 Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld.
 In Proceedings of the Twenty-Seventh AAAI Conference on
            Artificial Intelligence, July 2013.
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               (2.0MB
               )
- Auction-based autonomous intersection management.
 Dustin Carlino,
            Stephen D. Boyles, and Peter
            Stone.
 In Proceedings of the 16th IEEE Intelligent Transportation Systems Conference (ITSC), October 2013.
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               (318.1kB
               )
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               (1.4MB
               )
- Multiagent Learning in the Presence of Memory-Bounded Agents.
 Doran
            Chakraborty and Peter Stone.
 Autonomous Agents and Multiagent Systems
            (JAAMAS), Springer, 2013.
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               (676.7kB
               )
                [ps]
               (447.9kB
               )
- Cooperating with a Markovian Ad Hoc Teammate.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the 12th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
 Details
                  
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               (202.3kB
               )
                [ps]
               (408.2kB
               )
- Targeted Opponent Modeling of Memory-Bounded Agents.
 Doran
            Chakraborty, Noa Agmon, and Peter
            Stone.
 In Proceedings of the Adaptive Learning Agents Workshop (ALA), May 2013.
 Details
                  
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               (629.0kB
               )
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               (1.6MB
               )
- Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back.
 Alon
            Farchy, Samuel Barrett, Patrick
            MacAlpine, and Peter Stone.
 In Proc. of 12th Int. Conf. on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2013.
 The videos referenced in the paper: original
            and optimized.
 Details
                  
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               )
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               (36.5MB
               )
- Role-Based Ad Hoc Teamwork.
 Katie Genter, Noa
            Agmon, and Peter Stone.
 In Gita Sukthankar, Robert P. Goldman, Christopher
            Geib, David V. Pyhadath, and Hung Hai Bui, editors, Plan, Activity, and Intent Recognition: Theory and Practice, pp.
            251–272, Elsevier, Philadelphia, PA, USA, 2013.
 Details
                  
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               (1.5MB
               )
                [ps]
               (1.6MB
               )
- Ad Hoc Teamwork for Leading a Flock.
 Katie Genter, Noa
            Agmon, and Peter Stone.
 In Proceedings of the 12th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), May 2013.
 Details
                  
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               (246.7kB
               )
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               (563.3kB
               )
                [slides.pdf]
               (28.3MB
               )
- Improving Efficiency of Leading a Flock in Ad Hoc Teamwork Settings.
 Katie
            Genter, Noa Agmon, and Peter Stone.
 In
            AAMAS Autonomous Robots and Multirobot Systems (ARMS) Workshop, May 2013.
 Details
                  
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               (179.8kB
               )
                [ps]
               (413.8kB
               )
                [slides.pdf]
               (13.0MB
               )
- TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots.
 Todd
            Hester and Peter Stone.
 Machine Learning, 90(3):385–429,
            2013.
 Official version
            from journal website.
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               (987.8kB
               )
                [ps]
               (3.2MB
               )
- The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots.
 Todd
            Hester and Peter Stone.
 In Sven Behnke, Arnoud Visser, Rong Xiong, and
            Manuela Veloso, editors, RoboCup-2013: Robot Soccer World Cup XVII, Lecture
            Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
 Details
                  
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               (234.7kB
               )
                [ps]
               (2.9MB
               )
- Learning Exploration Strategies in Model-Based Reinforcement Learning.
 Todd
            Hester, Manuel Lopes, and Peter
            Stone.
 In The Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
 Details
                  
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               (258.7kB
               )
                [ps]
               (2.4MB
               )
- Training a Robot via Human Feedback: A Case Study.
 W. Bradley Knox, Peter
            Stone, and Cynthia Breazeal.
 In International Conference on
            Social Robotics, October 2013.
 BEST PAPER AWARD WINNER at ICSR 2013
 An
            associated video summarizing the paper (direct
            link).
 Details
                  
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               (2.3MB
               )
- UT Austin Villa: RoboCup 2012 3D Simulation League Champion.
 Patrick
            MacAlpine, Nick Collins, Adrian
            Lopez-Mobilia, and Peter Stone.
 In Xiaoping
            Chen, Peter Stone, Luis Enrique
            Sucar, and Tijn Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup
            XVI, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
 Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/results_3d/#highlights
 Details
                  
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               (654.8kB
               )
                [ps]
               (6.7MB
               )
- Positioning to Win: A Dynamic Role Assignment and FormationPositioning System.
 Patrick
            MacAlpine, Francisco Barrera, and Peter
            Stone.
 In Xiaoping Chen, Peter
            Stone, Luis Enrique Sucar, and Tijn
            Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2013.
 Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/positioning.html
 Details
                  
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               )
                [ps]
               (722.6kB
               )
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               (44.0MB
               )
- Simultaneous Learning and Reshaping of an Approximated Optimization Task.
 Patrick
            MacAlpine, Elad Liebman, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
 Details
                  
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               (435.1kB
               )
                [ps]
               (2.1MB
               )
                [slides.pdf]
               (35.2MB
               )
- UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy.
 Jacob
            Menashe, Katie Genter, Samuel
            Barrett, and Peter Stone.
 In The Eighth Workshop on Humanoid Soccer
            Robots at Humanoids 2013, October 2013.
 Details
                  
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               (350.2kB
               )
                [ps]
               (24.1MB
               )
                [slides.pdf]
               (3.1MB
               )
- Teaching and leading an ad hoc teammate: Collaboration without pre-coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, Jeffrey S. Rosenschein, and Noa
            Agmon.
 Artificial Intelligence, 203:35–65, Elsevier, October 2013.
 Official
            version from journal website.
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               (499.6kB
               )
                [ps]
               (734.2kB
               )
- Model-Selection for Non-Parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy
            System.
 Daniel Urieli and Peter
            Stone.
 In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML'13),
            Sep 2013.
 Official publisher version
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               (2.3MB
               )
                [ps]
               (1.4MB
               )
                [slides.pdf]
               (3.6MB
               )
- A Learning Agent for Heat-Pump Thermostat Control.
 Daniel Urieli
            and Peter Stone.
 In Proceedings of the 12th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
 Details
                  
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               (426.6kB
               )
                [slides.pdf]
               (4.6MB
               )
- Leading Ad Hoc Agents in Joint Action Settings with Multiple Teammates.
 Noa
            Agmon and Peter Stone.
 In Proc. of 11th Int. Conf. on Autonomous
            Agents and Multiagent Systems (AAMAS), June 2012.
 Details
                  
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               (229.4kB
               )
                [ps]
               (757.7kB
               )
- On Coordination in Practical Multi-Robot Patrol.
 Noa Agmon, Chien-Liang
            Fok, Yehuda Emaliah, Peter
            Stone, Christine Julien, and Sriram
            Vishwanath.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
 Details
                  
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               )
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               (5.4MB
               )
- Setpoint Scheduling for Autonomous Vehicle Controllers.
 Tsz-Chiu Au,
            Michael Quinlan, and Peter
            Stone.
 In Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 2012.
 Details
                  
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               (684.9kB
               )
                [ps]
               (2.7MB
               )
- Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions.
 Aijun
            Bai, Xiaoping Chen, Patrick
            MacAlpine, Daniel Urieli, Samuel
            Barrett, and Peter Stone.
 In Thomas Roefer, Norbert Michael Mayer, Jesus
            Savage, and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence,
            Springer Verlag, Berlin, 2012.
 Details
                  
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               (257.0kB
               )
                [ps]
               (829.5kB
               )
- An Analysis Framework for Ad Hoc Teamwork Tasks.
 Samuel Barrett
            and Peter Stone.
 In Proceedings of the 11th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
 Details
                  
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               (177.6kB
               )
                [ps]
               (1.1MB
               )
                [slides.pdf]
               (1.6MB
               )
- Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing.
 Samuel
            Barrett, Katie Genter, Todd Hester,
            Piyush Khandelwal, Michael
            Quinlan, Peter Stone, and Mohan
            Sridharan.
 Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI
            Laboratory, 2012.
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               (1.1MB
               )
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               (32.8MB
               )
- Approximately Orchestrated Routing and Transportation Analyzer: Large-scale Traffic Simulation for Autonomous Vehicles.
 Dustin Carlino, Mike
            Depinet, Piyush Khandelwal, and Peter
            Stone.
 In Proceedings of the 15th IEEE Intelligent Transportation Systems Conference (ITSC), September 2012.
 Details
                  
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               (727.1kB
               )
                [ps]
               (14.3MB
               )
- Automated Intersection Control: Performance of a Future Innovation Versus Current Traffic Signal Control.
 David
            Fajardo, Tsz-Chiu Au, Travis Waller,
            Peter Stone, and David Yang.
 Transportation
            Research Record (TRR), 2259:223–32, 2012.
 Details
                  
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               (591.8kB
               )
- HyperNEAT-GGP: A HyperNEAT-based Atari General Game Player.
 Matthew
            Hausknecht, Piyush Khandelwal, Risto
            Miikkulainen, and Peter Stone.
 In Genetic and Evolutionary Computation
            Conference (GECCO), July 2012.
 Details
                  
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               (880.9kB
               )
                [ps]
               (3.3MB
               )
- RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control.
 Todd
            Hester, Michael Quinlan, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
 Details
                  
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- PAC Subset Selection in Stochastic Multi-armed Bandits.
 Shivaram
            Kalyanakrishnan, Ambuj Tewari, Peter
            Auer, and Peter Stone.
 In Proceedings of the 29th International Conference
            on Machine Learning (ICML), pp. 655–662, Omnipress, New York, NY, USA, June-July 2012.
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               (519.5kB
               )
- A Low Cost Ground Truth Detection System Using the Kinect.
 Piyush Khandelwal
            and Peter Stone.
 In Thomas Roefer, Norbert Michael Mayer, Jesus Savage,
            and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2012.
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               (2.7MB
               )
- How Humans Teach Agents: A New Experimental Perspective.
 W. Bradley Knox,
            Brian D. Glass, Bradley
            C. Love, W. Todd Maddox, and Peter
            Stone.
 International Journal of Social Robotics, 4:409–421, Springer Netherlands, October 2012. 10.1007/s12369-012-0163-x
 International Journal of Social Robotics
 Download article from publisher
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- The Nature of Belief-Directed Exploratory Choice in Human Decision-Making.
 W.
            Bradley Knox, A. Ross Otto, Peter
            Stone, and Bradley Love.
 Frontiers in Psychology, 2(398), January 2012.
 Frontiers in Psychology
 Download
            article from publisher (free)
 A follow-up
            commentary by Erica Yu.
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- Reinforcement Learning from Simultaneous Human and MDP Reward.
 W. Bradley Knox
            and Peter Stone.
 In Proceedings of the 11th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
 AAMAS 2012
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               (4.9MB
               )
- Learning from feedback on actions past and intended.
 W. Bradley Knox,
            Cynthia Breazeal, and Peter
            Stone.
 In Proceedings of 7th ACM/IEEE International Conference on Human-Robot Interaction, Late-Breaking Reports
            Session (HRI), March 2012.
 HRI 2012
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               (3.9MB
               )
- Using a million cell simulation of the cerebellum: Network scaling and task generality.
 Wen-Ke Li, Matthew
            J. Hausknecht, Peter Stone, and Michael
            D. Mauk.
 Neural Networks, November 2012.
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               )
- Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition.
 Patrick MacAlpine, Samuel Barrett,
            Daniel Urieli, Victor
            Vu, and Peter Stone.
 In Proceedings of the Twenty-Sixth AAAI Conference
            on Artificial Intelligence (AAAI), July 2012.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html
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               (2.0MB
               )
                [slides.pdf]
               (204.2MB
               )
- UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition.
 Patrick
            MacAlpine, Daniel Urieli, Samuel
            Barrett, Shivaram Kalyanakrishnan, Francisco
            Barrera, Adrian Lopez-Mobilia, Nicolae \cStiurc\ua,
            Victor Vu, and Peter
            Stone.
 In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
 Accompanying
            videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/components.html
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               )
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               (135.4MB
               )
- Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk.
 Patrick
            MacAlpine and Peter Stone.
 In AAMAS Adaptive Learning Agents (ALA)
            Workshop, June 2012.
 Video available at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/holonomicwalk.html
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                [ps]
               (2.2MB
               )
                [slides.pdf]
               (159.5MB
               )
- Multiagent Patrol Generalized to Complex Environmental Conditions.
 Noa Agmon,
            Daniel Urieli, and Peter Stone.
 In
            Proceedings of the Twenty-Fifth Conference on ArtificialIntelligence (AAAI), August 2011.
 Extended
            version, book
            chapter
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               )
- Enforcing Liveness in Autonomous Traffic Management.
 Tsz-Chiu Au, Neda Shahidi, and Peter
            Stone.
 In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
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                [ps]
               (31.7MB
               )
- Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain.
 Samuel
            Barrett, Peter Stone, and Sarit
            Kraus.
 In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
 Details
                  
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               (361.8kB
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               (11.4MB
               )
                [slides.pdf]
               (616.4kB
               )
- Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards.
 Samuel
            Barrett and Peter Stone.
 In Tenth International Conference on Autonomous
            Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
 Details
                  
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               (136.1kB
               )
                [ps]
               (384.8kB
               )
- Austin Villa 2010 Standard Platform Team Report.
 Samuel Barrett,
            Katie Genter, Matthew Hausknecht,
            Todd Hester, Piyush Khandelwal,
            Juhyun Lee, Michael
            Quinlan, Aibo Tian, Peter Stone,
            and Mohan Sridharan.
 Technical Report UT-AI-TR-11-01, The University of Texas
            at Austin, Department of Computer Sciences, AI Laboratory, 2011.
 Details
                  
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               (1.3MB
               )
                [ps]
               (38.0MB
               )
- Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the Twenty Eighth
            International Conference on Machine Learning (ICML), 2011.
 Details
                  
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               (223.3kB
               )
                [ps]
               (521.1kB
               )
- Dynamic Lane Reversal in Traffic Management.
 Matthew Hausknecht,
            Tsz-Chiu Au, Peter Stone, David
            Fajardo, and Travis Waller.
 In Proceedings of IEEE Intelligent Transportation
            Systems Conference (ITSC), 2011.
 Details
                  
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                [ps]
               (4.3MB
               )
- Autonomous Intersection Management: Multi-Intersection Optimization.
 Matthew
            Hausknecht, Tsz-Chiu Au, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2011.
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               (1.9MB
               )
- Learning and Using Models.
 Todd Hester and Peter
            Stone.
 In Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Springer
            Verlag, Berlin, Germany, 2011.
 Details
                  
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               )
- Characterizing Reinforcement Learning Methods through Parameterized Learning Problems.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 Machine Learning (MLJ), 84(1--2):205–247,
            July 2011.
 Publisher's
            on-line version
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               (2.4MB
               )
- On Learning with Imperfect Representations.
 Shivaram Kalyanakrishnan
            and Peter Stone.
 In Proceedings of the 2011 IEEE Symposium on Adaptive
            Dynamic Programming and Reinforcement Learning, pp. 17–24, IEEE, April 2011.
 Details
                  
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               (196.0kB
               )
- Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report.
 W. Bradley
            Knox and Peter Stone.
 In IJCAI 2011 Workshop on Agents Learning Interactively
            from Human Teachers (ALIHT), July 2011.
 IJCAI 2011 Workshop
            on Agents Learning Interactively  from Human Teachers (ALIHT)
 Details
                  
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                [ps]
               (41.6MB
               )
- Comparing Agents: Success against People in Security Domains.
 Raz Lin,
            Sarit Kraus, Noa Agmon, Samuel
            Barrett, and Peter Stone.
 In Proceedings of the Twenty-Fifth AAAI
            Conference on Artificial Intelligence, August 2011.
 Details
                  
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               (387.5kB
               )
- UT Austin Villa 2011 3D Simulation Team Report.
 Patrick MacAlpine,
            Daniel Urieli, Samuel Barrett,
            Shivaram Kalyanakrishnan, Francisco
            Barrera, Adrian Lopez-Mobilia, Nicolae\cStiurc\ua,
            Victor Vu, and Peter
            Stone.
 Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
            2011.
 Details
                  
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               (1.2MB
               )
                [ps]
               (5.3MB
               )
- Designing Adaptive Trading Agents.
 David Pardoe and Peter
            Stone.
 ACM SIGecom Exchanges, 10(2):37–9, June 2011.
 SIGecom
            Exchanges
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               )
- A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations.
 David
            Pardoe and Peter Stone.
 In Proceedings of the 10th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
 Details
                  
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               (313.6kB
               )
                [ps]
               (280.8kB
               )
- An Introduction to Inter-task Transfer for Reinforcement Learning.
 Matthew
            E. Taylor and Peter Stone.
 AI Magazine, 32(1):15–34,
            2011.
 Details
                  
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               (237.0kB
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                [ps]
               (773.0kB
               )
- On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer.
 Daniel
            Urieli, Patrick MacAlpine, Shivaram
            Kalyanakrishnan, Yinon Bentor, and Peter
            Stone.
 In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), pp. 769–776, IFAAMAS,
            May 2011.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2010/html/skilloptimization2010.html
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               (530.9kB
               )
                [ps]
               (1.6MB
               )
                [slides.pptx]
               (3.8MB
               )
- Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning.
 Shimon
            Whiteson, Brian Tanner, Matthew
            E. Taylor, and Peter Stone.
 In IEEE Symposium on Adaptive Dynamic
            Programming and Reinforcement Learning (ADPRL), April 2011.
 2011
            IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL)
 Details
                  
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               )
- Motion Planning Algorithms for Autonomous Intersection Management.
 Tsz-Chiu
            Au and Peter Stone.
 In AAAI 2010 Workshop on Bridging The Gap Between
            Task And Motion Planning (BTAMP), 2010.
 Details
                  
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               (417.4kB
               )
                [ps]
               (2.0MB
               )
- Controlled Kicking under Uncertainty.
 Samuel Barrett, Katie
            Genter, Todd Hester, Michael
            Quinlan, and Peter Stone.
 In The Fifth Workshop on Humanoid Soccer
            Robots at Humanoids 2010, December 2010.
 Details
                  
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               (357.3kB
               )
                [ps]
               (17.7MB
               )
- Transfer Learning for Reinforcement Learning on a Physical Robot.
 Samuel
            Barrett, Matt E. Taylor, and Peter
            Stone.
 In Ninth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents
            Workshop (AAMAS - ALA), May 2010.
 AAMAS ALA 2010
 Details
                  
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                [ps]
               (5.7MB
               )
- Convergence, Targeted Optimality and Safety in Multiagent Learning.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the Twenty-seventh
            International Conference on Machine Learning (ICML), June 2010.
 Details
                  
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               (196.9kB
               )
                [ps]
               (474.1kB
               )
- Real Time Targeted Exploration in Large Domains.
 Todd Hester and Peter Stone.
 In The Ninth International Conference on Development and Learning
            (ICDL), August 2010.
 ICDL 2010
 Details
                  
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               (253.9kB
               )
                [ps]
               (554.1kB
               )
- Generalized Model Learning for Reinforcement Learning on a Humanoid Robot.
 Todd
            Hester, Michael Quinlan, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2010.
 Video available at
            http://www.cs.utexas.edu/~AustinVilla/?p=research/rl_kick
 Details
                  
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               (1.5MB
               )
                [ps]
               (25.3MB
               )
- Gaussian processes for sample efficient reinforcement learning with RMAX-like exploration.
 Tobias
            Jung and Peter Stone.
 In The European Conference on Machine Learning
            (ECML), September 2010.
 Details
                  
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               (417.0kB
               )
                [ps]
               (6.5MB
               )
                [slides.pdf]
               (505.6kB
               )
- Efficient Selection of Multiple Bandit Arms: Theory and Practice.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 In Proceedings of the Twenty-seventh
            International Conference on Machine Learning (ICML), 2010.
 Details
                  
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               (257.1kB
               )
                [ps]
               (679.3kB
               )
- Vision Calibration and Processing on a Humanoid Soccer Robot.
 Piyush
            Khandelwal, Matthew Hausknecht, Juhyun
            Lee, Aibo Tian, and Peter Stone.
 In
            The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
 Details
                  
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               (402.6kB
               )
                [ps]
               (14.8MB
               )
- Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning.
 W. Bradley
            Knox and Peter Stone.
 In Proc. of 9th Int. Conf. on Autonomous Agents
            and Multiagent Systems (AAMAS 2010), May 2010.
 Winner of the Pragnesh Jay Modi BEST STUDENT PAPER AWARD (and
            best paper award nominee).
 The TAMER project page with videos
            of TAMER in action.
 AAMAS-2010
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               )
                [ps]
               (3.5MB
               )
- Multi-Agent Social Simulation.
 Itsuki Noda, Peter
            Stone, Tomohisa Yamashita, and Koichi Kurumatani.
 In Nakashima, H., Aghajan, H., \& Augusto, J. C., editors, Handbook
            of Ambient Intelligence and Smart Environments, pp. 703–729, Springer Verlag, 2010.
 Official version from
            publisher's webage
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- Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge.
 David
            Pardoe, Peter Stone, Maytal
            Saar-Tsechansky, Tayfun Keskin, and Kerem Tomak.
 Informs Journal
            on Computing, 22(3):353–370, 2010.
 Details
                  
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               )
                [ps]
               (9.2MB
               )
- The 2007 TAC SCM Prediction Challenge.
 David Pardoe and Peter
            Stone.
 In Wolfgang Ketter, Han La Poutré, Norman Sadeh, Onn
            Shehory, and William Walsh, editors, Agent-Mediated Electronic Commerce and Trading Agent Design and Alaysis, Lecture
            Notes in Business Information Processing (LNBIP), pp. 175–89, Springer Verlag, 2010.
 Details
                  
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               (1.0MB
               )
                [ps]
               (2.0MB
               )
- Boosting for Regression Transfer.
 David Pardoe and Peter
            Stone.
 In Proceedings of the 27th International Conference on Machine Learning (ICML), June 2010.
 Some
            of the data used in the experiments.
 Details
                  
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                [ps]
               (1.7MB
               )
- TacTex09: A Champion Bidding Agent for Ad Auctions.
 David Pardoe,
            Doran Chakraborty, and Peter
            Stone.
 In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010),
            May 2010.
 Details
                  
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               (564.3kB
               )
                [ps]
               (1.0MB
               )
- Bringing Simulation to Life: A Mixed Reality Autonomous Intersection.
 Michael
            Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
            2010.
 Video available at http://www.cs.utexas.edu/~aim/video/MixedReality.wmv
 Details
                  
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               (1.3MB
               )
                [ps]
               (10.6MB
               )
- MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training.
 Adam
            Setapen, Michael Quinlan, and Peter
            Stone.
 In Ninth International Conference on Autonomous Agents and Multiagent Systems - Agents Learning Interactively
            from Human Teachers Workshop (AAMAS - ALIHT), May 2010.
 supplemental
            video cited in the paper.
 Details
                  
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               (533.2kB
               )
                [ps]
               (9.7MB
               )
- The Essence of Soccer, Can Robots Play Too?.
 Peter Stone, Michael
            Quinlan, and Todd Hester.
 In Ted Richards, editors, Soccer and Philosophy:
             Beautiful Thoughts on theBeautiful Game, Popular Culture and Philosophy, pp. 75–88, Open Court Publishing Company,
            2010.
 Appears in Soccer and Philosophy (available from amazon.com)
 Details
                  
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               (121.3kB
               )
                [ps]
               (514.1kB
               )
- Ad Hoc Autonomous Agent Teams:  Collaboration without Pre-Coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, and Jeffrey S. Rosenschein .
 In Proceedings of the Twenty-Fourth
            Conference on Artificial Intelligence, July 2010.
 AAAI
            2010
 Details
                  
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               (119.0kB
               )
                [ps]
               (266.6kB
               )
                [slides.pdf]
               (8.1MB
               )
- To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams.
 Peter
            Stone and Sarit Kraus.
 In The Ninth International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), International Foundation for Autonomous Agents and Multiagent Systems, May 2010.
 supplemental material cited in the paper,
            including a proof and an algorithm.
 AAMAS 2010
 Details
                  
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               )
                [ps]
               (285.3kB
               )
- Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning.
 Shimon Whiteson, Matthew
            E. Taylor, and Peter Stone.
 Journal of Autonomous Agents and
            Multi-Agent Systems, 21(1):1–27, 2010.
 Details
                  
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               (760.6kB
               )
                [ps]
               (1.9MB
               )
- Autonomous Return on Investment Analysis of Additional Processing Resources.
 Jonathan
            Wildstrom, Peter Stone, and Emmett
            Witchel.
 International Journal on Autonomic Computing, 1(3):280–296, Inderscience Publishers, Inderscience
            Publishers, Geneva, SWITZERLAND, 2010.
 IJAC
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- Improving Particle Filter Performance Using SSE Instructions.
 Peter
            Djeu, Michael Quinlan, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
            2009.
 Details
                  
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               (176.8kB
               )
                [ps]
               (2.7MB
               )
- A Task Specification Language for Bootstrap Learning.
 Ian
            Fasel, Michael Quinlan, and Peter
            Stone.
 In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.
 AAAI
            Spring 2009 Symposium: Agents that Learn from Human Teachers
 Details
                  
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               (407.2kB
               )
                [ps]
               (1.9MB
               )
- Generalized Model Learning for Reinforcement Learning in Factored Domains.
 Todd
            Hester and Peter Stone.
 In The Eighth International Conference on
            Autonomous Agents and Multiagent Systems (AAMAS), May 2009.
 AAMAS
            2009
 Details
                  
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               (181.5kB
               )
                [ps]
               (425.5kB
               )
- An Empirical Comparison of Abstraction in Models of Markov Decision Processes.
 Todd
            Hester and Peter Stone.
 In Proceedings of the ICML/UAI/COLT Workshop
            on Abstraction in Reinforcement Learning, June 2009.
 ICML ARL 2009
 Details
                  
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               (127.0kB
               )
                [ps]
               (363.0kB
               )
- TT-UT Austin Villa 2009: Naos across Texas.
 Todd Hester, Michael
            Quinlan, Peter Stone, and Mohan
            Sridharan.
 Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
            2009.
 Details
                  
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               (787.9kB
               )
                [ps]
               (7.0MB
               )
- Compositional Models for Reinforcement Learning.
 Nicholas
            K. Jong and Peter Stone.
 In The European Conference on Machine Learning
            and Principles and Practice of Knowledge Discovery in Databases, September 2009.
 Details
                  
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               (173.0kB
               )
                [ps]
               (431.7kB
               )
- Feature Selection for Value Function Approximation Using Bayesian Model Selection.
 Tobias
            Jung and Peter Stone.
 In The European Conference on Machine Learning
            and Principles and Practice of Knowledge Discovery in Databases, September 2009.
 Details
                  
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               (746.9kB
               )
                [ps]
               (2.3MB
               )
                [slides.pdf]
               (957.5kB
               )
- Connectivity-based Localization in Robot Networks.
 Tobias Jung,
            Mazda Ahmadi, and Peter
            Stone.
 In International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09), June 2009.
 Details
                  
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               (176.8kB
               )
                [ps]
               (514.7kB
               )
- An Empirical Analysis of Value Function-Based and Policy Search Reinforcement Learning.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 In The Eighth International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), pp. 749–756, International Foundation for Autonomous Agents
            and Multiagent Systems, May 2009.
 AAMAS 2009
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- The UT Austin Villa 3D Simulation Soccer Team 2008.
 Shivaram Kalyanakrishnan,
            Yinon Bentor, and Peter Stone.
 Technical
            Report AI09-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2009.
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               )
                [ps]
               (983.9kB
               )
- Interactively Shaping Agents via Human Reinforcement: The TAMER Framework.
 W. Bradley
            Knox and Peter Stone.
 In The Fifth International Conference on Knowledge
            Capture, September 2009.
 The TAMER project page with
            videos of TAMER in action.
 K-CAP
            2009
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               )
- Design Principles for Creating Human-Shapable Agents.
 W. Bradley Knox,
            Ian Fasel, and Peter
            Stone.
 In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.
 AAAI
            Spring 2009 Symposium: Agents that Learn from Human Teachers
 Details
                  
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               )
- An Autonomous Agent for Supply Chain Management.
 David Pardoe and
            Peter Stone.
 In Gedas Adomavicius and Alok Gupta, editors, Handbooks
            in Information Systems Series: Business Computing, pp. 141–72, Emerald Group, 2009.
 Details
                  
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               )
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               (736.6kB
               )
- Adapting Price Predictions in TAC SCM.
 David Pardoe and Peter
            Stone.
 In John Collins, Peyman Faratin, Simon
            Parsons, Juan A. Rodriguez-Aguilar, Norman
            M. Sadeh, Onn Shehory, and Elizabeth
            Sklar, editors, Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis, Lecture Notes in Business
            Information Processing, pp. 30–45, Springer Verlag, 2009.
 Official version from publisher's
            webpage
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               (328.7kB
               )
                [ps]
               (524.0kB
               )
- Color Learning and Illumination Invariance on Mobile Robots: A Survey.
 Mohan
            Sridharan and Peter Stone.
 Robotics and Autonomous Systems (RAS)
            Journal, 57(60-7):629–44, June 2009.
 Details
                  
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               (1.3MB
               )
                [ps]
               (6.0MB
               )
- Transfer Learning for Reinforcement Learning Domains: A Survey.
 Matthew
            E. Taylor and Peter Stone.
 Journal of Machine Learning Research,
            10(1):1633–1685, 2009.
 Official	version
            from journal website.
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               (399.8kB
               )
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               (579.4kB
               )
- Instance-Based Action Models for Fast Action Planning.
 Mazda
            Ahmadi and Peter Stone.
 In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi,
            and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence, pp.
            1–16, Springer Verlag, Berlin, 2008.
 BEST PAPER AWARD WINNER at RoboCup International Symposium.
 Official
            version from Publisher's Webpage© Springer-Verlag
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               (3.0MB
               )
- Multiagent Interactions in Urban Driving.
 Patrick Beeson, Jack
            O'Quin, Bartley Gillan, Tarun Nimmagadda, Mickey Ristroph, David Li, and Peter
            Stone.
 Journal of Physical Agents, 2(1):15–30, March 2008. Special issue on Multi-Robot Systems
 JoPhA
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               (2.1MB
               )
                [ps]
               (6.6MB
               )
- Online Multiagent Learning against Memory Bounded Adversaries.
 Doran
            Chakraborty and Peter Stone.
 In Machine Learning and Knowledge Discovery
            in Databases, pp. 211–26, September 2008.
 Official version from Publisher's
            Webpage© Springer-Verlag
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               )
                [ps]
               (669.2kB
               )
- A Multiagent Approach to Autonomous Intersection Management.
 Kurt
            Dresner and Peter Stone.
 Journal of Artificial Intelligence Research,
            31:591–656, March 2008.
 Available from journal's
            web page.
 Further details and videos are on the project page.
 Details
                  
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               (1.3MB
               )
                [ps]
               (2.2MB
               )
- Mitigating Catastrophic Failure at Intersections of Autonomous Vehicles.
 Kurt
            Dresner and Peter Stone.
 In AAMAS Workshop on Agents in Traffic and
            Transportation, pp. 78–85, Estoril, Portugal, May 2008.
 Details
                  
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               (836.3kB
               )
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               (1.3MB
               )
- A Neural Network-Based Approach to Robot Motion Control.
 Uli Grasemann, Daniel
            Stronger, and Peter Stone.
 In Ubbo Visser, Fernando Ribeiro, Takeshi
            Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence,
            pp. 480–87, Springer Verlag, Berlin, 2008.
 Details
                  
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               )
                [ps]
               (1.6MB
               )
- Negative Information and Line Observations for Monte Carlo Localization.
 Todd
            Hester and Peter Stone.
 In IEEE International Conference on Robotics
            and Automation, May 2008.
 ICRA 2008
 Details
                  
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               (128.7kB
               )
                [ps]
               (501.7kB
               )
- UT Austin Villa 2008: Standing on Two Legs.
 Todd Hester, Michael
            Quinlan, and Peter Stone.
 Technical Report UT-AI-TR-08-8, The University
            of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2008.
 Details
                  
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               (705.9kB
               )
                [ps]
               (6.2MB
               )
- Hierarchical Model-Based Reinforcement Learning: Rmax + MAXQ.
 Nicholas
            K. Jong and Peter Stone.
 In Proceedings of the Twenty-Fifth
            International Conference on Machine Learning, July 2008.
 ICML 2008
 Details
                  
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               (157.5kB
               )
                [ps]
               (370.2kB
               )
- The Utility of Temporal Abstraction in Reinforcement Learning.
 Nicholas
            K. Jong, Todd Hester, and Peter
            Stone.
 In The Seventh International Joint Conference on Autonomous Agents and  Multiagent Systems, May 2008.
 AAMAS-2008
 Details
                  
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               (136.4kB
               )
                [ps]
               (325.7kB
               )
- Model-based Reinforcement Learning in a Complex Domain.
 Shivaram
            Kalyanakrishnan, Peter Stone, and Yaxin
            Liu.
 In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World
            Cup XI, Lecture Notes in Artificial Intelligence, pp. 171–83, Springer Verlag, Berlin, 2008.
 Details
                  
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               (200.9kB
               )
                [ps]
               (515.0kB
               )
- TAMER: Training an Agent Manually via Evaluative Reinforcement.
 W. Bradley
            Knox and Peter Stone.
 In IEEE 7th International Conference on Development
            and Learning, August 2008.
 ICDL-2008
 Also available in IEEE
            Xplore, 9-12 Aug. 2008 Pages:292 - 297
 Details
                  
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               )
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               (12.8MB
               )
- Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting.
 Juhyun
            Lee, W. Bradley Knox, and Peter
            Stone.
 Journal of Physical Agents, 2(2):41–50, July 2008. Special Issue on Human Interaction with Domestic
            Robots
 Available from journal's web page.
 Details
                  
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               (2.4MB
               )
                [ps]
               (3.4MB
               )
- Online Kernel Selection for Bayesian Reinforcement Learning.
 Joseph
            Reisinger, Peter Stone, and Risto
            Miikkulainen.
 In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
 ICML 2008
 Details
                  
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               )
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               )
- Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents.
 Daniel
            Stronger and Peter Stone.
 International Journal on Artificial Intelligence
            Tools, 17(1):159–174, February 2008.
 official
            published version
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               (236.4kB
               )
                [ps]
               (1.0MB
               )
- Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot.
 Daniel
            Stronger and Peter Stone.
 In IEEE International Conference on Robotics
            and Automation, May 2008.
 ICRA 2008
 Details
                  
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               (182.1kB
               )
                [ps]
               (902.7kB
               )
- Transferring Instances for Model-Based Reinforcement Learning.
 Matthew E. Taylor,
            Nicholas K. Jong, and Peter
            Stone.
 In Machine Learning and Knowledge Discovery in Databases, pp. 488–505, September 2008.
 Official
            version from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (304.9kB
               )
                [ps]
               (860.1kB
               )
- Autonomous Transfer for Reinforcement Learning.
 Matthew E. Taylor,
            Gregory Kuhlmann, and Peter
            Stone.
 In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
 AAMAS-2008
 Details
                  
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               (233.3kB
               )
                [ps]
               (391.7kB
               )
- Transfer Learning and Intelligence: an Argument and Approach.
 Matthew E. Taylor,
            Gregory Kuhlmann, and Peter
            Stone.
 In Proceedings of the First Conference on Artificial General Intelligence, March 2008.
 AGI-2008
 Google
            video version of the conference presentation.
 Details
                  
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               (149.0kB
               )
                [ps]
               (202.5kB
               )
- Replacing the Stop Sign: Unmanaged Intersection Control for Autonomous Vehicles.
 Mark
            VanMiddlesworth, Kurt Dresner, and Peter
            Stone.
 In AAMAS Workshop on Agents in Traffic and Transportation, pp. 94–101, Estoril, Portugal, May 2008.
 Details
                  
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               (161.4kB
               )
                [ps]
               (305.1kB
               )
- IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks.
 Mazda
            Ahmadi, Matthew E. Taylor, and Peter
            Stone.
 In The Sixth International Joint Conference on Autonomous Agents and  Multiagent Systems, May 2007.
 BEST PAPER AWARD NOMINEE.
 AAMAS-2007
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               )
                [ps]
               (1.0MB
               )
- General Game Learning using Knowledge Transfer.
 Bikramjit Banerjee
            and Peter Stone.
 In The 20th International Joint Conference on Artificial
            Intelligence, pp. 672–677, January 2007.
 IJCAI-07
 Details
                  
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               (118.1kB
               )
                [ps]
               (198.5kB
               )
- Sharing the Road: Autonomous Vehicles meet Human Drivers.
 Kurt
            Dresner and Peter Stone.
 In The 20th International Joint Conference
            on Artificial Intelligence, pp. 1263–68, January 2007.
 IJCAI-07
 Details
                  
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               (189.9kB
               )
                [ps]
               (287.7kB
               )
- Learning Policy Selection for Autonomous Intersection Management.
 Kurt
            Dresner and Peter Stone.
 In AAMAS 2007 Workshop on Adaptive and Learning
            Agents, pp. 34–39, Honolulu, Hawaii, USA, May 2007.
 Details
                  
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               (79.9kB
               )
                [ps]
               (197.6kB
               )
- The Chin Pinch:  A Case Study in Skill Learning on a Legged Robot.
 Peggy
            Fidelman and Peter Stone.
 In Gerhard Lakemeyer, Elizabeth
            Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
            in Artificial Intelligence, pp. 59–71, Springer Verlag, Berlin, 2007.
 Some videos
            referenced in the paper.
 Details
                  
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               (186.9kB
               )
                [ps]
               (1.6MB
               )
- Model-Based Function Approximation for Reinforcement Learning.
 Nicholas
            K. Jong and Peter Stone.
 In The Sixth International Joint Conference
            on Autonomous Agents and  Multiagent Systems, May 2007.
 Details
                  
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               (321.1kB
               )
                [ps]
               (1.0MB
               )
- Model-Based Exploration in Continuous State Spaces.
 Nicholas
            K. Jong and Peter Stone.
 In The Seventh Symposium on Abstraction,
            Reformulation, and Approximation, July 2007.
 Details
                  
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               (324.3kB
               )
                [ps]
               (1.1MB
               )
- Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study.
 Shivaram
            Kalyanakrishnan, Yaxin Liu, and Peter
            Stone.
 In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
            Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
            72–85, Springer Verlag, Berlin, 2007.
 BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
 Some simulations referenced in the paper.
 Details
                  
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               (992.2kB
               )
                [ps]
               (1.6MB
               )
- Batch Reinforcement Learning in a Complex Domain.
 Shivaram Kalyanakrishnan
            and Peter Stone.
 In The Sixth International Joint Conference on Autonomous
            Agents and  Multiagent Systems, pp. 650–657, ACM, New York, NY, USA, May 2007.
 BEST PAPER AWARD NOMINEE.
 AAMAS-2007
 Details
                  
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               (186.4kB
               )
                [ps]
               (384.8kB
               )
- The UT Austin Villa 3D Simulation Soccer Team 2007.
 Shivaram Kalyanakrishnan
            and Peter Stone.
 Technical Report AI-07-348, The University of Texas at
            Austin, Department of Computer Sciences, AI Laboratory, 2007.
 Supplementary resources at the UT
            Austin Villa 3D Simulation page.
 Details
                  
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               (273.4kB
               )
                [ps]
               (5.7MB
               )
- Graph-Based Domain Mapping for Transfer Learning in General Games.
 Gregory
            Kuhlmann and Peter Stone.
 In Proceedings of The Eighteenth European
            Conference on Machine Learning, September 2007.
 Details
                  
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               (377.0kB
               )
                [ps]
               (601.6kB
               )
- Autonomous Learning of Stable Quadruped Locomotion.
 Manish
            Saggar, Thomas D'Silva, Nate Kohl, and Peter
            Stone.
 In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
            Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
            98–109, Springer Verlag, Berlin, 2007.
 BEST PAPER AWARD NOMINEE at RoboCup International Symposium.
 Some videos referenced in the paper.
 Details
                  
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               (1.1MB
               )
                [ps]
               (26.8MB
               )
- Structure Based Color Learning on a Mobile Robot under Changing Illumination.
 Mohan
            Sridharan and Peter Stone.
 Autonomous Robots, 23(3):161–182,
            2007.
 Official versionfrom
            the Autonomous Robots publisher's webpage.
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               (2.0MB
               )
                [ps]
               (8.6MB
               )
- Planning Actions to Enable Color Learning on a Mobile Robot.
 Mohan Sridharan
            and Peter Stone.
 International Journal of Information and Systems Sciences,
            3(3):510–25, 2007.
 official
            published version
 Details
                  
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            (unavailable)
- Action Selection for Illumination Invariant Color Learning.
 Mohan Sridharan
            and Peter Stone.
 In The IEEE International Conference on Intelligent
            Robots and Systems (IROS), 2007.
 Details
                  
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               (176.5kB
               )
                [ps]
               (490.5kB
               )
- Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination.
 Mohan
            Sridharan and Peter Stone.
 In The 20th International Joint Conference
            on Artificial Intelligence, pp. 2212–2217, January 2007.
 IJCAI-07
 Details
                  
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               (129.5kB
               )
                [ps]
               (184.9kB
               )
- Intelligent Autonomous Robotics:  A Robot Soccer Case Study,
 Peter
            Stone.
 Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan \& Claypool Publishers, 2007.
 Available from Synthesis page.
 ISBN: 9781598291262
 Details
                  
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            (unavailable)
- Multiagent learning is not the answer. It is the question.
 Peter Stone.
 Artificial
            Intelligence, 171:402–05, May 2007.
 Response to Shoham, Powers, and Grenager If Multi-Agent Systems is
            the Answer, What is the Question?, available from Shoham's webpage.
 Official version from the AIJ
            publisher's webpage.
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               (117.9kB
               )
                [ps]
               (91.0kB
               )
- Learning and Multiagent Reasoning for Autonomous Agents.
 Peter Stone.
 In
            The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
 IJCAI-07
 Details
                  
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               (308.5kB
               )
                [ps]
               (379.3kB
               )
- DARPA Urban Challenge Technical Report: Austin Robot Technology.
 Peter
            Stone, Patrick Beeson, Tekin
            Mericli, and Ryan Madigan.
 June 2007. Available from http://www.darpa.mil/grandchallenge/rules.asp
 Details
                  
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               (2.7MB
               )
- Selective Visual Attention for Object Detection on a Legged Robot.
 Daniel
            Stronger and Peter Stone.
 In Gerhard Lakemeyer, Elizabeth
            Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
            in Artificial Intelligence, pp. 158–170, Springer Verlag, Berlin, 2007.
 Some videos
            referenced in the paper.
 Details
                  
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               (159.7kB
               )
                [ps]
               (342.4kB
               )
- A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot.
 Daniel
            Stronger and Peter Stone.
 In IEEE International Conference on Robotics
            and Automation, pp. 3915–3920, April 2007.
 Details
                  
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               (271.4kB
               )
                [ps]
               (2.2MB
               )
- Transfer Learning via Inter-Task Mappings for Temporal Difference Learning.
 Matthew
            E. Taylor, Peter Stone, and Yaxin
            Liu.
 Journal of Machine Learning Research, 8(1):2125–2167, 2007.
 Available from journal's
            web page.
 Details
                  
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               (499.9kB
               )
                [ps]
               (831.3kB
               )
- Temporal Difference and Policy Search Methods for         Reinforcement Learning: An Empirical Comparison.
 Matthew
            E. Taylor, Shimon Whiteson, and Peter
            Stone.
 In Proceedings of the Twenty-Second          Conference on Artificial Intelligence, pp. 1675–1678,
            July 2007. Nectar Track
 AAAI         2007
 Details
                  
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               (99.7kB
               )
                [ps]
               (190.4kB
               )
- Cross-Domain Transfer for Reinforcement Learning.
 Matthew E. Taylor
            and Peter Stone.
 In Proceedings of the Twenty-Fourth International  
                   Conference on Machine Learning, June 2007.
 ICML   
                  2007
 Details
                  
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               (220.7kB
               )
                [ps]
               (325.4kB
               )
- Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning.
 Matthew
            E. Taylor, Shimon Whiteson, and Peter
            Stone.
 In The Sixth International Joint Conference on Autonomous Agents and  Multiagent Systems, May 2007.
 AAMAS-2007
 Details
                  
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            [pdf]
               (222.5kB
               )
                [ps]
               (525.2kB
               )
- Representation Transfer for Reinforcement Learning.
 Matthew E. Taylor
            and Peter Stone.
 In AAAI 2007 Fall Symposium on Computational       
            Approaches to Representation Change during Learning and        Development, November 2007.
 2007
                   AAAI Fall Symposium: Computational Approaches to        Representation Change during Learning and Development
 Details
                  
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               (144.9kB
               )
                [ps]
               (375.1kB
               )
- Accelerating Search with Transferred Heuristics.
 Matthew E. Taylor,
            Gregory Kuhlmann, and Peter
            Stone.
 In ICAPS-07 workshop on AI Planning and Learning, September 2007.
 ICAPS
            2007 workshop on AI Planning and Learning
 Details
                  
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            [pdf]
               (139.9kB
               )
                [ps]
               (215.4kB
               )
- Autonomous Bidding Agents:  Strategies and Lessons from the Trading Agent Competition,
 Michael
            P. Wellman, Amy Greenwald, and Peter
            Stone.
 MIT Press, 2007.
 Available from 
            MIT Press page.
 ISBN: 0-262-23260-X
 Details
                  
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            (unavailable)
- Empirical Studies in Action Selection for Reinforcement Learning.
 Shimon
            Whiteson, Matthew E. Taylor, and Peter
            Stone.
 Adaptive Behavior, 15(1):33–50, March 2007.
 Details
                  
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               (828.6kB
               )
                [ps]
               (1.5MB
               )
- Adaptive Tile Coding for Value Function Approximation.
 Shimon
            Whiteson, Matthew E. Taylor, and Peter
            Stone.
 Technical Report AI-TR-07-339, University of Texas at Austin, 2007.
 Details
                  
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               (329.4kB
               )
                [ps]
               (942.5kB
               )
- Machine Learning for On-Line Hardware Reconfiguration.
 Jonathan
            Wildstrom, Peter Stone, Emmett
            Witchel, and Mike Dahlin.
 In The 20th International Joint Conference
            on Artificial Intelligence, pp. 1113–1118, January 2007.
 IJCAI-07
 Details
                  
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               (98.6kB
               )
                [ps]
               (191.7kB
               )
- Keeping in Touch: Maintaining Biconnected Structure by Homogeneous Robots.
 Mazda
            Ahmadi and Peter Stone.
 In Proceedings of the Twenty-First National
            Conference on Artificial Intelligence, pp. 580–85, July 2006.
 AAAI
            2006.
 Additional details on the distributed "biconnected check" can be found in Keeping
            in Touch: A Distributed Check for Biconnected Structure by Homogeneous Robots in the 2006 International Symposium
            on Distributed Autonomous Robotic Systems (DARS 2006).
 Details
                  
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               (105.0kB
               )
                [ps]
               (128.8kB
               )
- A Multi-Robot System for Continuous Area Sweeping Tasks.
 Mazda
            Ahmadi and Peter Stone.
 In Proceedings of the IEEE International
            Conference on Robotics and Automation, pp. 1724–1729, May 2006.
 Some videos
            of the robot referenced in the paper.
 ICRA 2006
 Details
                  
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               (171.3kB
               )
                [ps]
               (314.6kB
               )
- Value Function Transfer for General Game Playing.
 Bikramjit Banerjee,
            Gregory Kuhlmann, and Peter
            Stone.
 In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.
 ICML
            2006 workshop on Structural Knowledge Transfer for Machine Learning
 Details
                  
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               (172.9kB
               )
                [ps]
               (464.0kB
               )
- Multiagent Traffic Management: Opportunities for Multiagent Learning.
 Kurt
            Dresner and Peter Stone.
 In K. Tuyls et al., editors, LAMAS
            2005, Lecture Notes in Artificial Intelligence, pp. 129–138, Springer Verlag, Berlin, 2006.
 LAMAS-05.
 Official version from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (81.4kB
               )
                [ps]
               (168.2kB
               )
- Human-Usable and Emergency Vehicle-Aware Control Policies for Autonomous Intersection Management.
 Kurt
            Dresner and Peter Stone.
 In AAMAS 2006 Workshop on Agents in Traffic
            and Transportation, May 2006.
 ATT 2006.
 The project page with videos from the paper.
 Details
                  
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            Download: 
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               (227.5kB
               )
                [ps]
               (376.8kB
               )
- Automatic Heuristic Construction in a Complete General Game Player.
 Gregory
            Kuhlmann, Kurt Dresner, and Peter
            Stone.
 In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1457–62,
            July 2006.
 AAAI 2006
 Details
                  
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               (124.1kB
               )
                [ps]
               (156.2kB
               )
- Know Thine Enemy: A Champion RoboCup Coach Agent.
 Gregory Kuhlmann,
            William B. Knox, and Peter Stone.
 In
            Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1463–68, July 2006.
 AAAI 2006
 Details
                  
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               (126.0kB
               )
                [ps]
               (286.1kB
               )
- Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping.
 Yaxin
            Liu and Peter Stone.
 In Proceedings of the Twenty-First National
            Conference on Artificial Intelligence, pp. 415–20, July 2006.
 AAAI
            2006
 Details
                  
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               (151.7kB
               )
                [ps]
               (1.6MB
               )
- Adaptive Mechanism Design: A Metalearning Approach.
 David Pardoe,
            Peter Stone, Maytal
            Saar-Tsechansky, and Kerem Tomak.
 In The Eighth International Conference
            on Electronic Commerce, pp. 92–102, August 2006.
 ICEC 2006.  Contains material
            from Adaptive Auctions:  Learning to Adjust to Bidders,
             Workshop on Information Technologies and Systems (WITS), 2005.
 Details
                  
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               (334.2kB
               )
                [ps]
               (511.6kB
               )
- TacTex-2005: A Champion Supply Chain Management Agent.
 David Pardoe
            and Peter Stone.
 In Proceedings of the Twenty-First National Conference
            on Artificial Intelligence, pp. 1489–94, July 2006.
 AAAI
            2006
 Details
                  
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               (200.7kB
               )
                [ps]
               (196.5kB
               )
- Predictive Planning for Supply Chain Management.
 David Pardoe and
            Peter Stone.
 In Proceedings of the International Conference on Automated
            Planning and Scheduling, June 2006.
 ICAPS 2006
 Details
                  
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            Download: 
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               (366.2kB
               )
                [ps]
               (950.9kB
               )
- Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data.
 Mohan
            Sridharan and Peter Stone.
 In The Ninth International Conference
            on Control, Automation, Robotics and Vision, December 2006.
 ICARCV
            2006
 Details
                  
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               (444.1kB
               )
                [ps]
               (2.3MB
               )
- From Pixels to Multi-Robot Decision-Making:  A Study in Uncertainty.
 Peter
            Stone, Mohan Sridharan, Daniel
            Stronger, Gregory Kuhlmann, Nate Kohl,
            Peggy Fidelman, and Nicholas
            K. Jong.
 Robotics and Autonomous Systems , 54(11):933–43, November 2006. Special issue on Planning
            Under Uncertainty in Robotics.
 Official versionfrom the RAS
            publisher's webpage.
 Details
                  
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               (260.5kB
               )
                [ps]
               (3.6MB
               )
- Keepaway Soccer:  From Machine Learning Testbed to Benchmark.
 Peter Stone,
            Gregory Kuhlmann, Matthew E. Taylor,
            and Yaxin Liu.
 In Itsuki
            Noda, Adam Jacoff, Ansgar Bredenfeld, and Yasutake Takahashi, editors, RoboCup-2005: Robot Soccer World Cup IX,
            pp. 93–105, Springer Verlag, Berlin, 2006.
 Some simulations
            of keepaway referenced in the paper and keepaway software.
 Official version from Publisher's
            Webpage© Springer-Verlag
 Details
                  
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               (567.7kB
               )
                [ps]
               (2.3MB
               )
- The UT Austin Villa 2006 RoboCup Four-Legged Team.
 Peter Stone, Peggy Fidelman, Nate Kohl, Gregory
            Kuhlmann, Tekin Mericli, Mohan Sridharan,
            and Shao-en Yu.
 Technical Report UT-AI-TR-06-337, The University of Texas at Austin, Department of Computer Sciences, AI
            Laboratory, 2006.
 At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2006.html#06-337
 Details
                  
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               (123.7kB
               )
                [ps]
               (127.2kB
               )
- Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot.
 Daniel
            Stronger and Peter Stone.
 Connection Science, 18(2):97–119,
            2006. Special Issue on Developmental Robotics.
 Connection
            Science Journal. Contains material that was previously published in an ICRA-2005
            paper.
 Details
                  
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               (372.6kB
               )
                [ps]
               (1.4MB
               )
- Designing Safe, Profitable Automated Stock Trading Agents Using Evolutionary Algorithms.
 Harish Subramanian, Subramanian Ramamoorthy, Peter
            Stone, and Benjamin Kuipers.
 In Proceedings of the Genetic and
            Evolutionary Computation Conference, July 2006.
 GECCO 2006
 Details
                  
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               (214.6kB
               )
                [ps]
               (813.6kB
               )
- Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning.
 Matthew
            Taylor, Shimon Whiteson, and Peter
            Stone.
 In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1321–28, July 2006.
 BEST PAPER AWARD at GECCO 2006
 Details
                  
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               (235.9kB
               )
                [ps]
               (562.2kB
               )
- Evolutionary Function Approximation for Reinforcement Learning.
 Shimon
            Whiteson and Peter Stone.
 Journal of Machine Learning Research,
            7:877–917, May 2006.
 Available from journal's web
            page.
 Details
                  
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               (1.7MB
               )
                [ps]
               (6.1MB
               )
- Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning.
 Shimon
            Whiteson and Peter Stone.
 In Proceedings of the Twenty-First National
            Conference on Artificial Intelligence, pp. 518–23, July 2006.
 AAAI
            2006
 Details
                  
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               (316.7kB
               )
                [ps]
               (2.7MB
               )
- On-Line Evolutionary Computation for Reinforcement Learning in Stochastic Domains.
 Shimon
            Whiteson and Peter Stone.
 In Proceedings of the Genetic and Evolutionary
            Computation Conference, pp. 1577–84, July 2006.
 GECCO 2006
 Details
                  
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               (754.2kB
               )
                [ps]
               (1.4MB
               )
- Adapting to Workload Changes Through On-The-Fly Reconfiguration.
 Jonathan
            Wildstrom, Peter Stone, Emmett
            Witchel, and Mike Dahlin.
 Technical Report UT-AI-TR-06-330, The University
            of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2006.
 At ftp://ftp.cs.utexas.edu/pub/AI-Lab/tech-reports/UT-AI-TR-06-330.pdf
 Details
                  
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- Continuous Area Sweeping: A Task Definition and Initial Approach.
 Mazda
            Ahmadi and Peter Stone.
 In The 12th International Conference on Advanced
            Robotics, July 2005.
 Some videos of
            the robot referenced in the paper.
 ICAR 2005
 Details
                  
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               (186.7kB
               )
                [ps]
               (243.1kB
               )
- Multiagent Traffic Management: An Improved Intersection Control Mechanism.
 Kurt
            Dresner and Peter Stone.
 In The Fourth International Joint Conference
            on Autonomous Agents and  Multiagent Systems, ACM Press, New York, NY, July 2005.
 Some videos
            referenced in the paper.  The main project page
 Extended
            version citable as  University of Texas at Austin AI lab technical
            report number UT-AI-TR-04-315
 AAMAS-2005
 Details
                  
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               (143.5kB
               )
                [ps]
               (216.7kB
               )
- State Abstraction Discovery from Irrelevant State Variables.
 Nicholas
            K. Jong and Peter Stone.
 In Proceedings of the Nineteenth International
            Joint Conference on Artificial Intelligence, pp. 752–757, August 2005.
 Details
                  
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               (102.1kB
               )
                [ps]
               (249.8kB
               )
                [slides.pdf]
               (323.4kB
               )
- Bayesian Models of Nonstationary Markov Decision Problems.
 Nicholas
            K. Jong and Peter Stone.
 In IJCAI 2005 workshop on Planning
            and Learning in A Priori Unknown or Dynamic Domains, August 2005.
 Workshop
            webpage.
 Details
                  
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               (42.4kB
               )
- The UT Austin Villa 2003 Champion Simulator Coach: A Machine Learning Approach.
 Gregory
            Kuhlmann, Peter Stone, and Justin Lallinger.
 In Daniele
            Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Lecture Notes
            in Artificial Intelligence, pp. 636–644, Springer Verlag, Berlin, 2005.
 Official version from Publisher's
            Webpage© Springer-Verlag
 Details
                  
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               (112.7kB
               )
                [ps]
               (287.8kB
               )
- Developing Adaptive Auction Mechanisms.
 David Pardoe and Peter
            Stone.
 ACM SIGecom Exchanges, 5(3):1–10, April 2005.
 SIGecom
            Exchanges
 Details
                  
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               (155.6kB
               )
                [ps]
               (212.4kB
               )
- Bidding for Customer Orders in TAC SCM.
 David Pardoe and Peter
            Stone.
 In P. Faratin and J.A. Rodriguez-Aguilar,
            editors, Agent Mediated Electronic Commerce VI:  Theories for and Engineering of Distributed Mechanisms and Systems (AMEC
            2004), Lecture Notes in Artificial Intelligence, pp. 143–157, Springer Verlag, Berlin, 2005.
 Official version
            from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (174.3kB
               )
                [ps]
               (283.8kB
               )
- Three Automated Stock-Trading Agents: A Comparative Study.
 Alexander
            Sherstov and Peter Stone.
 In P. Faratin and J.A. Rodriguez-Aguilar,
            editors, Agent Mediated Electronic Commerce VI:  Theories for and Engineering of Distributed Mechanisms and Systems (AMEC
            2004), Lecture Notes in Artificial Intelligence, pp. 173–187, Springer Verlag, Berlin, 2005.
 Official version
            from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (167.0kB
               )
                [ps]
               (248.6kB
               )
- Function Approximation via Tile Coding: Automating Parameter Choice.
 Alexander
            A. Sherstov and Peter Stone.
 In J.-D. Zucker and I. Saitta,
            editors, SARA 2005, Lecture Notes in Artificial Intelligence, pp. 194–205, Springer Verlag, Berlin, 2005.
 SARA-05.
 Official version from Publisher's
            Webpage© Springer-Verlag
 Details
                  
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               (187.7kB
               )
                [ps]
               (583.4kB
               )
                [slides.pdf]
               (193.7kB
               )
- Improving Action Selection in MDP's via Knowledge Transfer.
 Alexander
            A. Sherstov and Peter Stone.
 In Proceedings of the Twentieth
            National Conference on Artificial Intelligence, July 2005.
 AAAI
            2005
 Details
                  
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               (205.5kB
               )
                [ps]
               (774.2kB
               )
- Towards Illumination Invariance in the Legged League.
 Mohan Sridharan
            and Peter Stone.
 In Daniele
            Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Lecture Notes
            in Artificial Intelligence, pp. 196–208, Springer Verlag, Berlin, 2005.
 Some videos
            of robots referenced in the paper.
 Official version from Publisher's
            Webpage© Springer-Verlag
 Details
                  
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               (245.1kB
               )
                [ps]
               (2.1MB
               )
- Autonomous Color Learning on a Mobile Robot.
 Mohan Sridharan and Peter Stone.
 In Proceedings of the Twentieth National Conference on Artificial
            Intelligence, July 2005.
 Some videos of
            the robot referenced in the paper.
 AAAI 2005
 Details
                  
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            [pdf]
               (901.5kB
               )
                [ps]
               (6.4MB
               )
- Real-Time Vision on a Mobile Robot Platform.
 Mohan Sridharan and Peter Stone.
 In IEEE/RSJ International Conference on Intelligent Robots
            and Systems (IROS), August 2005.
 Some videos
            of the robot referenced in the paper.
 IROS-2005
 Details
                  
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               (396.1kB
               )
                [ps]
               (5.0MB
               )
- Practical Vision-Based Monte Carlo Localization on a Legged Robot.
 Mohan
            Sridharan, Gregory Kuhlmann, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation, April 2005.
 ICRA
            2005
 Details
                  
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               (217.6kB
               )
                [ps]
               (2.0MB
               )
                [slides.pdf]
               (2.5MB
               )
- The UT Austin Villa 2005 RoboCup Four-Legged Team.
 Peter Stone, Kurt Dresner, Peggy
            Fidelman, Nate Kohl, Gregory Kuhlmann,
            Mohan Sridharan, and Daniel
            Stronger.
 Technical Report UT-AI-TR-05-325, The University of Texas at Austin, Department of Computer Sciences, AI
            Laboratory, 2005.
 At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2005.html#05-325
 Details
                  
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               (186.2kB
               )
                [ps]
               (243.4kB
               )
- A Model-Based Approach to Robot Joint Control.
 Daniel
            Stronger and Peter Stone.
 In Daniele
            Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Lecture Notes
            in Artificial Intelligence, pp. 297–309, Springer Verlag, Berlin, 2005.
 Official version from Publisher's
            Webpage© Springer-Verlag
 Details
                  
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               (235.3kB
               )
                [ps]
               (489.4kB
               )
- Value Functions for RL-Based Behavior Transfer: A Comparative Study.
 Matthew
            E. Taylor, Peter Stone, and Yaxin
            Liu.
 In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
 AAAI
            2005
 Details
                  
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               (147.3kB
               )
                [ps]
               (449.9kB
               )
- Behavior Transfer for Value-Function-Based Reinforcement Learning.
 Matthew
            E. Taylor and Peter Stone.
 In The Fourth International Joint
            Conference on Autonomous Agents and  Multiagent Systems, pp. 53–59, ACM Press, New York, NY, July 2005.
 AAMAS-2005
 Details
                  
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               (230.4kB
               )
                [ps]
               (620.1kB
               )
- Evolving Keepaway Soccer Players through Task Decomposition.
 Shimon
            Whiteson, Nate Kohl, Risto Miikkulainen,
            and Peter Stone.
 Machine Learning, 59(1):5–30, May 2005.
 Some videos of the agents before and after
            learning referenced in the paper.
 The publisher's official
            version
 An earlier version appeared in the proceedings of The Genetic
            and Evolutionary Computation Conference 2003 (GECCO-2003)
 Details
                  
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            [pdf]
               (278.8kB
               )
                [ps]
               (566.8kB
               )
- Automatic Feature Selection via Neuroevolution.
 Shimon
            Whiteson, Peter Stone, Kenneth
            O. Stanley, Risto Miikkulainen, and Nate
            Kohl.
 In Proceedings of the Genetic and Evolutionary Computation Conference, June 2005.
 Details
                  
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               (181.4kB
               )
                [ps]
               (1.6MB
               )
- Towards Self-Configuring Hardware for Distributed Computer Systems.
 Jonathan
            Wildstrom, Peter Stone, Emmett
            Witchel, Raymond J. Mooney, and Mike
            Dahlin.
 In The Second International Conference on Autonomic Computing, pp. 241–249, June 2005.
 ICAC-05
 A revised version of the paper appeared on IBM's Developer
            Works website
 Details
                  
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               (74.0kB
               )
                [ps]
               (104.6kB
               )
- Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism.
 Kurt
            Dresner and Peter Stone.
 In The Third International Joint Conference
            on Autonomous Agents and Multiagent Systems, pp. 530–537, July 2004.
 Some simulations
            of cars driving through intersections referenced in the paper. The main project
            page
 AAMAS-2004
 Details
                  
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               (233.8kB
               )
                [ps]
               (492.0kB
               )
- Two Stock-Trading Agents: Market Making and Technical Analysis.
 Yi Feng, Ronggang Yu, and Peter
            Stone.
 In Peyman Faratin, David C. Parkes, Juan A. Rodriguez-Aguilar,
            and William E. Walsh, editors, Agent Mediated Electronic Commerce V: Designing Mechanisms and Systems, Lecture
            Notes in Artificial Intelligence, pp. 18–36, Springer Verlag, 2004.
 AMEC-2003
 Details
                  
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            [pdf]
               (512.0kB
               )
                [ps]
               (912.4kB
               )
- Machine Learning for Fast Quadrupedal Locomotion.
 Nate Kohl and Peter
            Stone.
 In The Nineteenth National Conference on Artificial Intelligence, pp. 611–616, July 2004.
 Some videos of walking robots referenced in
            the paper.
 AAAI 2004
 Details
                  
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               (210.0kB
               )
                [ps]
               (1.4MB
               )
- Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion.
 Nate Kohl
            and Peter Stone.
 In Proceedings of the IEEE International Conference
            on Robotics and Automation, May 2004.
 Some videos
            of walking robots referenced in the paper.
 ICRA 2004
 Details
                  
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            Download: 
            [pdf]
               (301.5kB
               )
                [ps]
               (3.2MB
               )
- Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer.
 Gregory
            Kuhlmann, Peter Stone, Raymond
            Mooney, and Jude Shavlik.
 In The AAAI-2004 Workshop on Supervisory
            Control of Learning and Adaptive Systems, July 2004.
 Details
                  
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            [pdf]
               (170.3kB
               )
                [ps]
               (498.2kB
               )
- TacTex-03:  A Supply Chain Management Agent.
 David Pardoe and Peter Stone.
 ACM SIGecom Exchanges: Special Issue on Trading Agent     
                       Design and Analysis, 4(3):19–28, Winter 2004.
 SIGecom
            Exchanges
 Extended
            version citable as  University of Texas at Austin AI lab technical
            report number UT-AI-TR-04-308.
 Details
                  
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            Download: 
            [pdf]
               (145.3kB
               )
                [ps]
               (161.6kB
               )
- Using RoboCup in university-level computer science education.
 Elizabeth
            Sklar, Simon Parsons, and Peter
            Stone.
 Journal on Educational Resources in Computing, 4(2), June 2004. Special issue on robotics in undergraduate
            education. Part 1
 Available from the publisher's
            webpage
 JERIC
 Details
                  
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            (unavailable)
- The UT Austin Villa 2004 RoboCup Four-Legged Team:  Coming of Age.
 Peter
            Stone, Kurt Dresner, Peggy
            Fidelman, Nicholas K. Jong, Nate
            Kohl, Gregory Kuhlmann, Mohan
            Sridharan, and Daniel Stronger.
 Technical Report
            UT-AI-TR-04-313, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2004.
 At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2004.html#04-313
 Details
                  
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               (555.3kB
               )
                [ps]
               (1.6MB
               )
- The UT Austin Villa 2003 Four-Legged Team.
 Peter Stone, Kurt
            Dresner, Selim T. Erdo\ugan, Peggy Fidelman, Nicholas
            K. Jong, Nate Kohl, Gregory Kuhlmann,
            Ellie Lin, Mohan Sridharan, Daniel Stronger, and Gurushyam Hariharan.
 In Daniel
            Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors, RoboCup-2003: Robot Soccer World Cup VII,
            Springer Verlag, Berlin, 2004.
 Extended
            version (technical report with full details: "UT Austin Villa 2003: A New RoboCup Four-Legged Team").
 Details
                  
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            [pdf]
               (201.5kB
               )
                [ps]
               (170.3kB
               )
- Adaptive Job Routing and Scheduling.
 Shimon Whiteson
            and Peter Stone.
 Engineering Applications of Artificial Intelligence,
            17(7):855–69, October 2004. Special issue on Autonomic Computing and Automation
 Available from the publisher's
            webpage
 The version from this page corrects a minor error in the published version.
 An earlier version appeared
            in the proceedings of The Sixteenth Innovative Applications of Artificial
            Intelligence Conference (IAAI 2004)
 Details
                  
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               (664.7kB
               )
                [ps]
               (1.1MB
               )
AFOSR
      
      
         - Adversarial Intrinsic Motivation for Reinforcement Learning.
 Ishan Durugkar,
            Mauricio Tec, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
            December 2021.
 slides and video presentation
 Details
                  
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            Download: 
            [pdf]
               (5.1MB
               )
- Reducing Sampling Error in Policy Gradient Learning.
 Josiah Hanna
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 This paper contains material that was previously
            presented at the 2018 NeurIPS Deep Reinforcement Learning Workshop.
 Details
                  
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               (1.5MB
               )
                [slides.pdf]
               (3.1MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science.
 Decebal Constantin Mocanu, Elena
            Mocanu, Peter Stone, Phuong
            H. Nguyen, Madeleine Gibescu, and Antonio
            Liotta.
 Nature Communications, 9(2383), June 2018.
 Official version from Publisher's
            Webpage.
 Details
                  
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               (1.5MB
               )
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
 Tarun
            Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
            and Peter Stone.
 Transportation Research Part B: Methodological,
            110:104–21, 2018.
 Official version from Publisher's
            Webpage
 Details
                  
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               (1.6MB
               )
- Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?.
 Michael
            Albert, Vincent Conitzer, and Peter Stone.
 In Proceedings of the
            16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), May 2017.
 Details
                  
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               (348.6kB
               )
                [slides.pdf]
               (2.8MB
               )
- Automated Design of Robust Mechanisms.
 Michael Albert, Vincent
            Conitzer, and Peter Stone.
 In Proceedings of the Thirty-First AAAI Conference
            on Artificial Intelligence (AAAI-17), Feb 2017.
 Details
                  
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               (366.4kB
               )
                [slides.pdf]
               (2.7MB
               )
- Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial.
 Stefano
            Albrecht, Somchaya Liemhetcharat, and Peter Stone.
 Autonomous Agents
            and Multi-Agent Systems, 31(4):765–66, July 2017.
 Official version from Publisher's
            Webpage
 Details
                  
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            Download: 
            [pdf]
               (304.3kB
               )
- Reasoning about Hypothetical Agent Behaviours and their Parameters.
 Stefano Albrecht
            and Peter Stone.
 In Proceedings of the 16th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
 Available from IFAAMAS
            and from ACM
 Details
                  
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            Download: 
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               (608.2kB
               )
                [slides.pdf]
               (1.2MB
               )
- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
            Ad Hoc Teamwork Robotics Competition.
 Katie Genter, Tim
            Laue, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems
            (JAAMAS), 31(4):790–820, Springer, July 2017.
 Official version from Publisher's
            Webpage
 Details
                  
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            Download: 
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               (1.2MB
               )
- CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression.
 Santiago Gonzalez,
            Vijay Chidambaram, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '17),
            July 2017.
 Details
                  
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               (241.6kB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            Hanna, Philip Thomas, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
 Details
                  
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               (1.2MB
               )
                [slides.pdf]
               (1.1MB
               )
- Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
 Josiah
            Hanna, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2017.
 Details
                  
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               (663.8kB
               )
                [ps]
               (572.6kB
               )
                [slides.pdf]
               (1.3MB
               )
- Grounded Action Transformation for Robot Learning in Simulation.
 Josiah
            Hanna and Peter Stone.
 In Proceedings of the 31st AAAI Conference
            on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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            Download: 
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               (1.3MB
               )
                [slides.pdf]
               (1.3MB
               )
- Machine Learning Capabilities of a Simulated Cerebellum.
 Matthew Hausknecht,
            Wen-Ke Li, Michael Mauk, and Peter Stone.
 "IEEE
            Transactions on Neural Networks and Learning Systems", 28(3):510–22, March 2017.
 Details
                  
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               (1.1MB
               )
- BWIBots: A platform for bridging the gap between AI and human--robot interaction research.
 Piyush
            Khandelwal, Shiqi Zhang, Jivko
            Sinapov, Matteo Leonetti, Jesse Thomason,
            Fangkai Yang, Ilaria Gori, Maxwell Svetlik, Priyanka Khante, Vladimir
            Lifschitz, J. K. Aggarwal, Raymond Mooney, and Peter
            Stone.
 The International Journal of Robotics Research, 36(5--7):635–59, 2017.
 Accompanying videos
            at https://youtu.be/2UJG4-ejVww
 Details
                  
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               (4.4MB
               )
- Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests.
 Piyush
            Khandelwal and Peter Stone.
 In International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2017.
 Details
                  
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            Download: 
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               (1.8MB
               )
- Designing Better Playlists with Monte Carlo Tree Search.
 Elad Liebman,
            Piyush Khandelwal, Maytal
            Saar-Tsechansky, and Peter Stone.
 In Proceedings of the Twenty-Ninth
            Conference On Innovative Applications Of Artificial Intelligence (IAAI-17), February 2017.
 Details
                  
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            Download: 
            [pdf]
               (377.0kB
               )
- Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges.
 Patrick
            MacAlpine and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 168–86, Springer International Publishing, 2017.
 Details
                  
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               (518.7kB
               )
                [ps]
               (2.6MB
               )
                [slides.pdf]
               (45.5MB
               )
- Fast and Precise Black and White Ball Detection for RoboCup Soccer.
 Jacob
            Menashe, Josh Kelle, Katie Genter, Josiah
            Hanna, Elad Liebman, Sanmit
            Narvekar, Ruohan Zhang, and Peter
            Stone.
 In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
 Details
                  
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               (254.2kB
               )
                [ps]
               (716.1kB
               )
                [slides.pdf]
               (1.5MB
               )
- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
 Sanmit
            Narvekar, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
            2017.
 Details
                  
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            Download: 
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               (826.2kB
               )
                [slides.pdf]
               (5.8MB
               )
- Network-wide Adaptive Tolling for Connected and Automated vehicles.
 Guni
            Sharon, Michael W. Levin, Josiah
            P. Hanna, Tarun Rambha, Stephen
            D. Boyles, and Peter Stone.
 Transportation Research Part C, 84:142–157,
            September 2017.
 Transportation Research Part C.
 Audio slides.
 Contains material
            that was previously published in an AAMAS-17 paper.
 Details
                  
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               (2.8MB
               )
                [ps]
               (4.2MB
               )
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
 Guni
            Sharon and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
 Details
                  
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               (1.1MB
               )
                [ps]
               (7.1MB
               )
                [slides.pptx]
               (140.9MB
               )
- Automatic Curriculum Graph Generation for Reinforcement Learning Agents.
 Maxwell Svetlik, Matteo
            Leonetti, Jivko Sinapov, Rishi Shah, Nick
            Walker, and Peter Stone.
 In Proceedings of the 31st AAAI Conference
            on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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            Download: 
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               (2.0MB
               )
- Multirobot Symbolic Planning under Temporal Uncertainty.
 Shiqi Zhang,
            Yuqian Jiang, Guni Sharon, and Peter
            Stone.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS),
            May 2017.
 Accompanying videos at https://youtu.be/ADbH3sppLHQ
 Details
                  
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               (2.3MB
               )
- Dynamically Constructed (PO)MDPs for Adaptive Robot Planning.
 Shiqi
            Zhang, Piyush Khandelwal, and Peter
            Stone.
 In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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            Download: 
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               (3.2MB
               )
- Making Friends on the Fly: Cooperating with New Teammates.
 Samuel Barrett,
            Avi Rosenfeld, Sarit Kraus,
            and Peter Stone.
 Artificial Intelligence, October 2016.
 Official version from journal website.
 Details
                  
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            Download: 
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               (917.9kB
               )
- State Aggregation through Reasoning in Answer Set Programming.
 Ginevra Gaudioso, Matteo
            Leonetti, and Peter Stone.
 In Proceedings of the IJCAI Workshop on
            Autonomous Mobile Service Robots (WSR 16), July 2016.
 Details
                  
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            Download: 
            [pdf]
               (776.6kB
               )
- Ad Hoc Teamwork Behaviors for Influencing a Flock.
 Katie Genter and
            Peter Stone.
 Acta Polytechnica, 56(1), 2016.
 Details
                  
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            Download: 
            [pdf]
               (421.5kB
               )
                [ps]
               (1.6MB
               )
- Adding Influencing Agents to a Flock.
 Katie Genter and Peter
            Stone.
 In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-16),
            May 2016.
 Details
                  
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            Download: 
            [pdf]
               (1.2MB
               )
                [ps]
               (4.5MB
               )
                [slides.pdf]
               (433.7kB
               )
- Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication.
 Jonathan Grizou, Samuel
            Barrett, Manuel Lopes, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (339.0kB
               )
- Minimum Cost Matching for Autonomous Carsharing.
 Josiah P. Hanna,
            Michael Albert, Donna
            Chen, and Peter Stone.
 In Proceedings of the 9th IFAC Symposium on
            Intelligent Autonomous Vehicles (IAV 2016), June 2016.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (117.5kB
               )
                [ps]
               (355.2kB
               )
                [slides.pdf]
               (4.7MB
               )
- Deep Reinforcement Learning in Parameterized Action Space.
 Matthew Hausknecht
            and Peter Stone.
 In Proceedings of the International Conference on Learning
            Representations (ICLR), May 2016.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (468.3kB
               )
- Grounded Semantic Networks for Learning Shared Communication Protocols.
 Matthew
            Hausknecht and Peter Stone.
 In Deep Reinforcement Learning, NIPS
            Workshop, December 2016.
 Details
                  
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            Download: 
            [pdf]
               (899.9kB
               )
- On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning.
 Matthew
            Hausknecht and Peter Stone.
 In Deep Reinforcement Learning: Frontiers
            and Challenges, IJCAI Workshop, July 2016.
 Details
                  
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               (2.5MB
               )
- Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork.
 Matthew
            Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan,
            and Peter Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop,
            May 2016.
 Details
                  
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            Download: 
            [pdf]
               (253.9kB
               )
- Deep Imitation Learning for Parameterized Action Spaces.
 Matthew Hausknecht,
            Yilun Chen, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
 Details
                  
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            Download: 
            [pdf]
               (483.4kB
               )
- On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search.
 Piyush
            Khandelwal, Elad Liebman, Scott
            Niekum, and Peter Stone.
 In Proceedings of The 33rd International
            Conference on Machine Learning, pp. 1319–1328, June 2016.
 Details
                  
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               (1.3MB
               )
                [slides.pdf]
               (1.7MB
               )
- A synthesis of automated planning and reinforcement learning for efficient, robust decision-making.
 Matteo
            Leonetti, Luca Iocchi, and Peter Stone.
 Artificial Intelligence,
            241:103 – 130, September 2016.
 Details
                  
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            [pdf]
               (3.2MB
               )
- Impact of Music on Decision Making in Quantitative Tasks.
 Elad Liebman,
            Peter Stone, and Corey
            N. White.
 In 17th International Society for Music Information retrieval Conference (ISMIR), August 2016.
 Details
                  
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            Download: 
            [pdf]
               (591.1kB
               )
                [slides.pdf]
               (678.6kB
               )
- Source Task Creation for Curriculum Learning.
 Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti,
            and Peter Stone.
 In Proceedings of the 15th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
 Details
                  
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            Download: 
            [pdf]
               (630.0kB
               )
                [slides.pdf]
               (10.2MB
               )
- Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors.
 Jivko
            Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone.
 In Proceedings
            of the 25th International Joint Conference on Artificial  Intelligence (IJCAI), July 2016.
 Details
                  
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            Download: 
            [pdf]
               (6.6MB
               )
                [slides.pdf]
               (5.2MB
               )
- Learning Multi-Modal Grounded Linguistic Semantics by Playing I Spy.
 Jesse Thomason,
            Jivko Sinapov, Maxwell Svetlik, Peter
            Stone, and Raymond Mooney.
 In Proceedings of the 25th international
            joint conference on Artificial Intelligence (IJCAI), July 2016.
 Demo Video
 Details
                  
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            [pdf]
               (3.1MB
               )
                [slides.pdf]
               (1.0MB
               )
- An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis.
 Daniel
            Urieli and Peter Stone.
 In Proceedings of the 15th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
 Details
                  
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            Download: 
            [pdf]
               (11.9MB
               )
- Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market.
 Daniel
            Urieli and Peter Stone.
 In Proceedings of the 30th Conference on
            Artificial Intelligence (AAAI 2016), February 2016.
 Details
                  
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            Download: 
            [pdf]
               (1.2MB
               )
- When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing.
 Fei
            Fang, Peter Stone, and Milind
            Tambe.
 In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
 Winner of Computational Sustainability Track Outstanding Paper Award at IJCAI 2015
 Details
                  
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               (456.7kB
               )
                [ps]
               (983.9kB
               )
                [slides.pptx]
               (6.2MB
               )
- Determining Placements of Influencing Agents in a Flock.
 Katie Genter,
            Shun Zhang, and Peter Stone.
 In
            Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
 Details
                  
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            Download: 
            [pdf]
               (426.7kB
               )
                [ps]
               (1.4MB
               )
                [slides.pdf]
               (1.6MB
               )
- The Impact of Determinism on Learning Atari 2600 Games.
 Matthew Hausknecht
            and Peter Stone.
 In AAAI Workshop on Learning for General Competency
            in Video Games, January 2015.
 Details
                  
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            Download: 
            [pdf]
               (65.1kB
               )
- Deep Recurrent Q-Learning for Partially Observable MDPs.
 Matthew Hausknecht
            and Peter Stone.
 In AAAI Fall Symposium on Sequential Decision Making
            for Intelligent Agents (AAAI-SDMIA15), November 2015.
 Details
                  
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            Download: 
            [pdf]
               (1.5MB
               )
                [slides.pdf]
               (3.8MB
               )
- Representative Selection in Nonmetric Datasets.
 Elad Liebman, Benny Chor, and Peter Stone.
 "Applied
            Artificial Intelligence", 29:807–838, 2015.
 Details
                  
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               (846.3kB
               )
- DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone.
 In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2015.
 Details
                  
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               (1.5MB
               )
                [ps]
               (38.4MB
               )
                [slides.pdf]
               (2.6MB
               )
- Monte Carlo Hierarchical Model Learning.
 Jacob Menashe and Peter Stone.
 In Proceedings of the 14th International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2015.
 Details
                  
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            Download: 
            [pdf]
               (693.2kB
               )
                [ps]
               (18.4MB
               )
- Learning Inter-Task Transferability in the Absence of Target  Task Samples.
 Jivko
            Sinapov, Sanmit Narvekar, Matteo
            Leonetti, and Peter Stone.
 In Proceedings of the International Conference
            on Autonomous  Agents and Multiagent Systems (AAMAS), 2015.
 Details
                  
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            Download: 
            [pdf]
               (337.2kB
               )
- Influencing a Flock via Ad Hoc Teamwork.
 Katie Genter and Peter
            Stone.
 In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
 Details
                  
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            Download: 
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               (358.4kB
               )
                [ps]
               (1.4MB
               )
                [slides.pdf]
               (15.3MB
               )
- Role-Based Ad Hoc Teamwork.
 Katie Genter, Noa
            Agmon, and Peter Stone.
 In Gita Sukthankar, Robert P. Goldman, Christopher
            Geib, David V. Pyhadath, and Hung Hai Bui, editors, Plan, Activity, and Intent Recognition: Theory and Practice, pp.
            251–272, Elsevier, Philadelphia, PA, USA, 2013.
 Details
                  
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               (1.5MB
               )
                [ps]
               (1.6MB
               )
AFRL
      
      
         - Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial.
 Stefano
            Albrecht, Somchaya Liemhetcharat, and Peter Stone.
 Autonomous Agents
            and Multi-Agent Systems, 31(4):765–66, July 2017.
 Official version from Publisher's
            Webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (304.3kB
               )
- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
            Ad Hoc Teamwork Robotics Competition.
 Katie Genter, Tim
            Laue, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems
            (JAAMAS), 31(4):790–820, Springer, July 2017.
 Official version from Publisher's
            Webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
- Ad Hoc Teamwork Behaviors for Influencing a Flock.
 Katie Genter and
            Peter Stone.
 Acta Polytechnica, 56(1), 2016.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (421.5kB
               )
                [ps]
               (1.6MB
               )
- Adding Influencing Agents to a Flock.
 Katie Genter and Peter
            Stone.
 In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-16),
            May 2016.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
                [ps]
               (4.5MB
               )
                [slides.pdf]
               (433.7kB
               )
- Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication.
 Jonathan Grizou, Samuel
            Barrett, Manuel Lopes, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (339.0kB
               )
- Minimum Cost Matching for Autonomous Carsharing.
 Josiah P. Hanna,
            Michael Albert, Donna
            Chen, and Peter Stone.
 In Proceedings of the 9th IFAC Symposium on
            Intelligent Autonomous Vehicles (IAV 2016), June 2016.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (117.5kB
               )
                [ps]
               (355.2kB
               )
                [slides.pdf]
               (4.7MB
               )
- Deep Reinforcement Learning in Parameterized Action Space.
 Matthew Hausknecht
            and Peter Stone.
 In Proceedings of the International Conference on Learning
            Representations (ICLR), May 2016.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (468.3kB
               )
- Grounded Semantic Networks for Learning Shared Communication Protocols.
 Matthew
            Hausknecht and Peter Stone.
 In Deep Reinforcement Learning, NIPS
            Workshop, December 2016.
 Details
                  
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- On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning.
 Matthew
            Hausknecht and Peter Stone.
 In Deep Reinforcement Learning: Frontiers
            and Challenges, IJCAI Workshop, July 2016.
 Details
                  
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               (2.5MB
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- Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork.
 Matthew
            Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan,
            and Peter Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop,
            May 2016.
 Details
                  
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               (253.9kB
               )
- Deep Imitation Learning for Parameterized Action Spaces.
 Matthew Hausknecht,
            Yilun Chen, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
 Details
                  
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               (483.4kB
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- Source Task Creation for Curriculum Learning.
 Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti,
            and Peter Stone.
 In Proceedings of the 15th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
 Details
                  
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               (630.0kB
               )
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               (10.2MB
               )
- An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis.
 Daniel
            Urieli and Peter Stone.
 In Proceedings of the 15th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
 Details
                  
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               (11.9MB
               )
- Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market.
 Daniel
            Urieli and Peter Stone.
 In Proceedings of the 30th Conference on
            Artificial Intelligence (AAAI 2016), February 2016.
 Details
                  
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               (1.2MB
               )
- When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing.
 Fei
            Fang, Peter Stone, and Milind
            Tambe.
 In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
 Winner of Computational Sustainability Track Outstanding Paper Award at IJCAI 2015
 Details
                  
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               (456.7kB
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                [ps]
               (983.9kB
               )
                [slides.pptx]
               (6.2MB
               )
- Determining Placements of Influencing Agents in a Flock.
 Katie Genter,
            Shun Zhang, and Peter Stone.
 In
            Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
 Details
                  
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               (426.7kB
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                [ps]
               (1.4MB
               )
                [slides.pdf]
               (1.6MB
               )
- The Impact of Determinism on Learning Atari 2600 Games.
 Matthew Hausknecht
            and Peter Stone.
 In AAAI Workshop on Learning for General Competency
            in Video Games, January 2015.
 Details
                  
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               (65.1kB
               )
- Deep Recurrent Q-Learning for Partially Observable MDPs.
 Matthew Hausknecht
            and Peter Stone.
 In AAAI Fall Symposium on Sequential Decision Making
            for Intelligent Agents (AAAI-SDMIA15), November 2015.
 Details
                  
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               (1.5MB
               )
                [slides.pdf]
               (3.8MB
               )
- How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification.
 Elad
            Liebman, Peter Stone, and Corey
            N. White.
 In 16th International Society for Music Information retrieval Conference (ISMIR), October 2015.
 Details
                  
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               (832.6kB
               )
                [ps]
               (6.3MB
               )
                [slides.pdf]
               (2.0MB
               )
- DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone.
 In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2015.
 Details
                  
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               (1.5MB
               )
                [ps]
               (38.4MB
               )
                [slides.pdf]
               (2.6MB
               )
- Monte Carlo Hierarchical Model Learning.
 Jacob Menashe and Peter Stone.
 In Proceedings of the 14th International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2015.
 Details
                  
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               (693.2kB
               )
                [ps]
               (18.4MB
               )
- Learning Inter-Task Transferability in the Absence of Target  Task Samples.
 Jivko
            Sinapov, Sanmit Narvekar, Matteo
            Leonetti, and Peter Stone.
 In Proceedings of the International Conference
            on Autonomous  Agents and Multiagent Systems (AAMAS), 2015.
 Details
                  
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               (337.2kB
               )
- Influencing a Flock via Ad Hoc Teamwork.
 Katie Genter and Peter
            Stone.
 In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
 Details
                  
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               (358.4kB
               )
                [ps]
               (1.4MB
               )
                [slides.pdf]
               (15.3MB
               )
- Role-Based Ad Hoc Teamwork.
 Katie Genter, Noa
            Agmon, and Peter Stone.
 In Gita Sukthankar, Robert P. Goldman, Christopher
            Geib, David V. Pyhadath, and Hung Hai Bui, editors, Plan, Activity, and Intent Recognition: Theory and Practice, pp.
            251–272, Elsevier, Philadelphia, PA, USA, 2013.
 Details
                  
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               (1.5MB
               )
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               (1.6MB
               )
ARL
      
      
         - ComposableNav: Instruction-Following Navigation in Dynamic Environments via Composable Diffusion.
 Zichao
            Hu, Chen Tang, Michael J. Munje,
            Yifeng Zhu, Alex Liu, Shuijing Liu,
            Garrett Warnell, Peter
            Stone, and Joydeep Biswas.
 In Conference on Robot Learning, September
            2025.
 Details
                  
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               (12.0MB
               )
- Reinforcement Learning within the Classical Robotics Stack: A Case Study in Robot Soccer.
 Adam Labiosa, Zhihan Wang,
            Siddhant Agarwal, William Cong, Geethika Hemkumar, Abhinav Narayan Harish, Benjamin Hong, Josh Kelle, Chen Li, Yuhao Li, Zisen
            Shao, Peter Stone, and Josiah
            Hanna.
 In International Conference on Robotics and Automation (ICRA), May 2025.
 Details
                  
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               (1.1MB
               )
- SocialNav-SUB: Benchmarking VLMs for Scene Understanding in Social Robot Navigation.
 Michael
            J. Munje, Chen Tang, Shuijing Liu,
            Zichao Hu, Yifeng Zhu, Jiaxun
            Cui, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In Conference on Robot Learning, September
            2025.
 Details
                  
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               (22.5MB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            P. Hanna, Yash Chandak, Philip S. Thomas, Martha White,
            Peter Stone, and Scott Niekum.
 Journal
            of Machine Learning Research, 2024.
 Official version on publisher's
            website
 Details
                  
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               (1.7MB
               )
- Learning Optimal Advantage from Preferences and Mistaking it for Reward.
 W. Bradley
            Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter
            Stone, and Scott Niekum.
 In The 38th Annual AAAI Conference on Artificial
            Intelligence (AAAI), February 2024.
 Details
                  
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               (3.6MB
               )
                [slides.pdf]
               (3.9MB
               )
                [poster.pdf]
               (2.9MB
               )
- Conflict Avoidance in Social Navigation --- a Survey.
 Reuth
            Mirsky, Xuesu Xiao, Justin Hart, and
            Peter Stone.
 ACM Transactions on Human-Robot Interaction, 2024.
 Details
                  
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               (2.1MB
               )
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
 Amir Hossain Raj, Zichao
            Hu, Haresh Karnan, Rohan Chandra,
            Amirreza Payandeh, Luisa Mao, Peter Stone, Joydeep
            Biswas, and and Xuesu Xiao.
 In International Conference on Robotics
            and Automation, May 2024.
 Details
                  
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               (2.0MB
               )
- The Human in the Loop: Perspectives and Challenges for RoboCup 2050.
 Alessandra Rossi, Maike Paetzel-Prüsmann,
            Merel Keijsers, Michael Anderson, Susan Leigh Anderson, Daniel Barry, Jan Gutsche, Justin
            Hart, Luca Iocchi, Ainse Kokkelmans, Wouter Kuijpers, Yun Liu, Daniel
            Polani, Caleb Roscon, Marcus Scheunemann, Peter Stone, Florian Vahl, René
            van de Molengraft, and Oskar von Stryk.
 Autonomous
            Robots, May 2024.
 Official version on publisher's website
 Details
                  
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               (2.1MB
               )
- Dobby: A Conversational Service Robot Driven by GPT-4.
 Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
            Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
            Hart.
 In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
 Details
                  
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               (863.8kB
               )
                [poster.pdf]
               (892.0kB
               )
- Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes.
 Chen
            Tang, Ben Abbatematteo, Jiaheng Hu, Rohan
            Chandra, Roberto Martín-Martín, and Peter Stone.
 Annual Review
            of Control, Robotics, and Autonomous Systems (ARCRAS), 8:153–88, 2024.
 Presented in Senior member track at
            AAAI 2025
 Official
            version on publisher's website
 Details
                  
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               (4.3MB
               )
                [slides.pdf]
               (2.9MB
               )
                [poster.pdf]
               (604.3kB
               )
- SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions.
 Zizhao
            Wang, Jiaheng Hu, Caleb Chuck, Stephen
            Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2024.
 Details
                  
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               (2.1MB
               )
- iCORPP: Interleaved commonsense reasoning and probabilistic planning on robots.
 Shiqi
            Zhang, Piyush Khandelwal, and Peter
            Stone.
 Robotics and Autonomous Systems, 2024.
 Details
                  
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               (2.0MB
               )
- "What's That Robot Doing Here?": Factors Influencing Perceptions Of Incidental Encounters With Autonomous Quadruped Robots.
 Elliott
            Hauser, Yao-Cheng Chan, Geethika Hemkumar, Daksh Dua, Parth Chonkar, Efren Mendoza Enriquez, Tiffany Kao, Shikhar Gupta, Huihai
            Wang, Justin Hart, Reuth Mirsky,
            Joydeep Biswas, Junfeng Jiao, and Peter
            Stone.
 In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23), pp.
            1–15, July 2023.
 Available online at https://dl.acm.org/doi/10.1145/3597512.3599707
 Details
                  
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- Causal Policy Gradient for Whole-Body Mobile Manipulation.
 Jiaheng Hu,
            Peter Stone, and Roberto Martin-Martin.
 In Robotics: Science and Systems
            (RSS), July 2023.
 Details
                  
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               (4.0MB
               )
- Exploring the Cost of Interruptions in Human-Robot Teaming.
 Swathi Mannem, William
            Macke, Peter Stone, and Reuth
            Mirsky.
 In IEEE-RAS Humanoids, December 2023.
 Details
                  
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               (921.5kB
               )
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               (294.3kB
               )
- Towards a Real-Time, Low-Resource, End-to-end Object Detection Pipeline for Robot Soccer.
 Sai Kiran Narayanaswami,
            Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit
            Narvekar, and Peter Stone.
 In Amy Eguchi, Nuno Lau, Maike Paetzel-Prussman,
            and Thanapat Wanichanon, editors, RoboCup 2022: Robot World Cup XXV, pp. 62–74, Springer International Publishing,
            2023.
 The book
 Details
                  
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               (572.2kB
               )
- Program Embeddings for Rapid Mechanism Evaluation.
 Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
            and Peter Stone.
 In ICRA Workshop on Multi-Robot Learning, May 2023.
 Details
                  
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               (1.3MB
               )
                [poster.pdf]
               (916.2kB
               )
- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
 Jinsoo Park, Xuesu
            Xiao, Garrett Warnell, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 6-minute video
            presentation
 Details
                  
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               (4.6MB
               )
                [slides.pptx]
               (21.3MB
               )
                [poster.pdf]
               (1.1MB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
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               (4.8MB
               )
- D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning.
 Caroline
            Wang, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2023.
 Details
                  
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               (1.6MB
               )
                [slides.pdf]
               (2.4MB
               )
                [poster.pdf]
               (1.4MB
               )
- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
 Caroline
            Wang, Ishan Durugkar, Elad Liebman,
            and Peter Stone.
 In Proceedings of the 37th AAAI Conference on Artificial
            Intelligence (AAAI-23), February 2023.
 Details
                  
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            Download: 
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               (801.2kB
               )
                [slides.pdf]
               (3.7MB
               )
                [poster.pdf]
               (1.4MB
               )
- Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.
 Xiaohan Zhang, Saeid Amiri,
            Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
 Autonomous
            Robots, March 2023.
 Official version
            on publisher's website
 Details
                  
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               (2.6MB
               )
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
 Eddy Hudson, Garrett
            Warnell, Faraz Torabi, and Peter
            Stone.
 In International Conference on Robotics and Automation (ICRA), May 2022.
 Presentation
            Video
 Details
                  
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               (2.5MB
               )
- DynaBARN: Benchmarking Metric Ground Navigation in Dynamic Environments.
 Anirudh Nair, Fulin Jiang, Kang Hou, Zifan Xu, Shuozhe Li, Xuesu Xiao, and Peter Stone.
 In Proceedings of the 2022 IEEE International Symposium on
            Safety, Security, and Rescue Robotics (SSRR), November 2022.
 Details
                  
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               (895.8kB
               )
- Causal Dynamics Learning for Task-Independent State Abstraction.
 Zizhao
            Wang, Xuesu Xiao, Zifan Xu, Yuke
            Zhu, and Peter Stone.
 In Proceedings of the 39th International Conference
            on Machine Learning (ICML2022), July 2022.
 recorded presentation
 Details
                  
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               (4.2MB
               )
                [slides.pdf]
               (4.0MB
               )
                [poster.pdf]
               (1.6MB
               )
- APPL: Adaptive Planner Parameter Learning.
 Xuesu Xiao, Zizhao
            Wang, Zifan Xu, Bo Liu, abd Gauraang
            Dhamankar, Anirudh Nair, Garrett Warnell, and Peter
            Stone.
 Robotics and Autonomous Systems, May 2022.
 Details
                  
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               (2.6MB
               )
- Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Survey.
 Xuesu
            Xiao, Bo Liu, Garrett
            Warnell, and Peter Stone.
 Autonomous Robots, 46:569–97,
            March 2022.
 Details
                  
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               (1.3MB
               )
- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
 Michael
            Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
 Operations
            Research, March 2021.
 Details
                  
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               (692.5kB
               )
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
 Roberto Capobianco, Varun Kompella, James
            Ault, Guni Sharon, Stacy
            Jong, Spencer Fox, Lauren
            Meyers, Peter R. Wurman, and Peter
            Stone.
 The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
 Contains
            material that was previously published in an AAMAS
            2021 paper and a AAAI 2020 Fall
            Symposium paper.
 Article available from  JAIR website.
 Simulator
            source code.
 Details
                  
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               (1.6MB
               )
- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
 Yunshu Du, Garrett
            Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
            E. Taylor.
 Neural Computing and Applications, May 2021.
 Details
                  
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               (2.2MB
               )
- Adversarial Intrinsic Motivation for Reinforcement Learning.
 Ishan Durugkar,
            Mauricio Tec, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
            December 2021.
 slides and video presentation
 Details
                  
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               (5.1MB
               )
- Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy.
 Josiah
            P. Hanna, Scott Niekum, and Peter
            Stone.
 Machine Learning (MLJ), 110:1267–1317, May 2021.
 Details
                  
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               (3.7MB
               )
- Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation.
 Blake Holman, Abrar
            Anwar, Akash Singh, Mauricio Tec, Justin
            Hart, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA), May 2021.
 Details
                  
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               (5.7MB
               )
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
 Eddy Hudson, Garrett
            Warnell, and Peter Stone.
 In Autonomous Robots and Multirobot Systems
            Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
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               (393.0kB
               )
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
 Yuqian
            Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
 In
            Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
 Details
                  
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               (1.8MB
               )
                [slides.pdf]
               (1.8MB
               )
- Policy Evaluation in Continuous MDPs with Efficient Kernelized Gradient Temporal Difference.
 Alec Koppel, Garrett
            Warnell, Ethan Stump, Peter Stone, and Alejandro Ribeiro.
 IEEE Transactions
            on Automatic Control, 66(4):1856–63, April 2021.
 official
            online version
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               (648.8kB
               )
- APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback.
 Zizhao
            Wang, Xuesu Xiao, Bo Liu,
            Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), October 2021.
 5-minute
            Video Presentation;  15-minute Video Presentation
 Details
                  
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               (1.1MB
               )
                [slides.pdf]
               (2.7MB
               )
- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
 Zizhao
            Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
            Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
 In Proceedings
            of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
 1-minute
            Video Summary;   15-minute Video Presentation
 Details
                  
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            Download: 
            [pdf]
               (2.9MB
               )
                [slides.pdf]
               (2.7MB
               )
- APPLI: Adaptive Planner Parameter Learning From Interventions.
 Zizhao Wang,
            Xuesu Xiao, Bo Liu, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
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            Download: 
            [pdf]
               (4.2MB
               )
- Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain.
 Xuesu
            Xiao, Joydeep Biswas, and Peter Stone.
 IEEE
            Robotics and Automation Letters (RA-L), July 2021.
 Contains material that was previously presented in an ICRA21
            workshop paper Video
 Details
                  
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            [pdf]
               (3.2MB
               )
                [slides.pdf]
               (23.2MB
               )
- Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination.
 Xuesu
            Xiao, Bo Liu, Garrett
            Warnell, and Peter Stone.
 IEEE Robotics and Automation Letters (RA-L),
            January 2021.
 5-minute video demonstration
 Project
            webpage
 Details
                  
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               (3.2MB
               )
- Agile Robot Navigation through Hallucinated Learning and Sober Deployment.
 Xuesu
            Xiao, Bo Liu, and Peter Stone.
 In
            Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), June 2021.
 Video
 Details
                  
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               (3.1MB
               )
- Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks.
 Ruohan
            Zhang, Faraz Torabi, Garrett
            Warnell, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems,
            35(31), June 2021.
 official online version
 Details
                  
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               (3.8MB
               )
- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
 Siddarth Desai, Ishan
            Durugkar, Haresh Karnan, Garrett
            Warnell, Josiah Hanna, and Peter
            Stone.
 In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
            December 2020.
 Poster
 Details
                  
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               (1.3MB
               )
- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
 Siddharth Desai, Haresh
            Karnan, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 11-minute video
            presentation.
 Details
                  
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               (1.9MB
               )
- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
 Ishan
            Durugkar, Elad Liebman, and Peter
            Stone.
 In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
            2020.
 Details
                  
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               (3.9MB
               )
- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
 Justin Hart,
            Reuth Mirsky, Xuesu Xiao,
            Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
            Stone.
 In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
 Video presentation
 Details
                  
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            Download: 
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               (3.2MB
               )
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
 Haresh
            Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 14-minute video
            presentation.
 Details
                  
               BibTeX
                  
            Download: 
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               (506.6kB
               )
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
 Shih-Yun Lo, Shiqi
            Zhang, and Peter Stone.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, October 2020.
 Contains material that was previously published in an AAMAS-18
            paper (awarded the Best Robotics Paper Award at AAMAS 2018)
 Also
            available from  JAIR website
 Details
                  
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            Download: 
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               (4.0MB
               )
- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
 Sanmit
            Narvekar, Bei Peng, Matteo Leonetti, Jivko
            Sinapov, Matthew E. Taylor, and Peter
            Stone.
 Journal of Machine Learning Research, 21(181):1–50, 2020.
 Details
                  
               BibTeX
                  
            Download: 
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               (1.4MB
               )
- Generalizing Curricula for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In 4th Lifelong Learning Workshop at the International
            Conference on Machine Learning (ICML 2020), July 2020.
 Details
                  
               BibTeX
                  
            Download: 
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               (330.4kB
               )
                [slides.pdf]
               (3.8MB
               )
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
 Brahma
            Pavse, Faraz Torabi, Josiah
            Hanna, Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
 Video
            of the experiments; 13-minute video presentation.
 Details
                  
               BibTeX
                  
            Download: 
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               (405.1kB
               )
                [slides.pptx]
               (115.4MB
               )
- Reducing Sampling Error in Batch Temporal Difference Learning.
 Brahma Pavse,
            Ishan Durugkar, Josiah Hanna,
            and Peter Stone.
 In Proceedings of the 37th International Conference
            on Machine Learning (ICML), July 2020.
 The paper and talk is available from the ICML
            2020 virtual conference page.
 Details
                  
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            Download: 
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               (738.4kB
               )
                [slides.pdf]
               (5.2MB
               )
- On Sampling Error in Batch Action-Value Prediction Algorithms.
 Brahma S. Pavse,
            Josiah P. Hanna, Ishan Durugkar,
            and Peter Stone.
 In In the Offline Reinforcement Learning Workshop at
            Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
 5-minute
            Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (327.2kB
               )
- Benchmarking Metric Ground Navigation.
 Daniel Perille, Abigail Truong, Xuesu
            Xiao, and Peter Stone.
 In Proceedings of the 2020 IEEE International
            Symposium on Safety, Security, and Rescue Robotics (SSRR), November 2020.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- Deep R-Learning for Continual Area Sweeping.
 Rishi Shah, Yuqian Jiang, Justin
            Hart, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
 1-minute
            video demonstration; 13-minute Video
            presentation.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (374.2kB
               )
                [slides.pdf]
               (1.1MB
               )
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
 Xuesu
            Xiao, Bo Liu, Garrett
            Warnell, Jonathan Fink, and Peter Stone.
 IEEE Robotics and Automation
            Letters (RA-L), June 2020.
 Presented at International Conference on Intelligent Robots and Systems ({IROS})\\  
             5-minute Video presentation; 15-minute
            Video presentation
 Project webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
                [slides.pdf]
               (21.1MB
               )
- Ad hoc Teamwork with Behavior Switching Agents.
 Manish Ravula, Shani Alkobi and Peter
            Stone.
 In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (350.4kB
               )
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
 Yuqian
            Jiang, Fangkai Yang, Shiqi
            Zhang, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (925.2kB
               )
- Open-World Reasoning for Service Robots.
 Yuqian Jiang, Nick
            Walker, Justin Hart, and Peter Stone.
 In
            Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
 Accompanying video
 Details
                  
               BibTeX
                  
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               (813.5kB
               )
- The right music at the right time: adaptive personalized playlists based on sequence modeling.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone Peter Stone.
 Management Information Systems Quarterly, 43(3):765–786, Society for Information Management
            and The Management Information Systems Research Center, 2019.
 Available from publisher's
            website.
 Details
                  
               BibTeX
                  
            Download: 
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               (4.0MB
               )
- Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report.
 Rishi Shah, Yuqian
            Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta,
            Rachel Schlossman, Marika Murphy, Justin Hart, Luis
            Sentis, and Peter Stone.
 In AAAI Fall Symposium on Artificial Intelligence
            and Human-Robot Interaction for Service Robots in Human Environments (AI-HRI 2019), November 2019.
 Details
                  
               BibTeX
                  
            Download: 
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               (4.5MB
               )
- Agents teaching agents: a survey on inter-agent transfer learning.
 Felipe Leno
            Da Silva, Garrett Warnell, Anna
            Helena Reali Costa, and Peter Stone.
 Autonomous Agents and Multi-Agent
            Systems, Dec 2019.
 Official version from JAAMAS
 Details
                  
               BibTeX
                  
            Download: 
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               (572.4kB
               )
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
 Felipe
            Leno Da Silva, Anna Helena Reali Costa, and Peter
            Stone.
 In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
 Details
                  
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            Download: 
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               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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            Download: 
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
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               (6.1MB
               )
- Desiderata for Planning Systems in General-Purpose Service Robots.
 Nick Walker,
            Yuqian Jiang, Maya Cakmak, and
            Peter Stone.
 In Proceedings of the ICAPS Workshop on Planning and Robotics
            (PlanRob 2019), July 2019.
 Details
                  
               BibTeX
                  
            Download: 
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               (651.5kB
               )
- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
 Harel
            Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
            Stone, and Raymond Mooney.
 In International Conference on Social
            Robotics (ICSR), pp. 133–143, November 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (958.6kB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
ARO
      
      
         - Proto Successor Measure: Representing the Behavior Space of an RL Agent.
 Siddhant Agarwal, Harshit Sikchi, Peter
            Stone, and Amy Zhang.
 In International Conference on Machine Learning, June 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (911.1kB
               )
- Deadlock-free, Safe, and Decentralized Multi-Robot Navigation in Social Mini-Games via Discrete-Time Control Barrier Functions.
 Rohan Chandra, Vrushabh Zinage, Efstathios Bakolas, Peter
            Stone, and Joydeep Biswas.
 Autonomous Robots, 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.5MB
               )
                [poster.pdf]
               (1.7MB
               )
- Multi-Agent Inverse Reinforcement Learning in Real World Unstructured Pedestrian Crowds.
 Rohan
            Chandra, Haresh Karnan, Negar Mehr, Peter
            Stone, and Joydeep Biswas.
 In IEEE/RSJ International Conference on Intelligent
            Robots and Systems (IROS), October 2025.
 Details
                  
               BibTeX
                  
            Download: 
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               (695.7kB
               )
- Dyna-LfLH: Learning Agile Navigation in Dynamic Environments from Learned Hallucination.
 Saad Abdul Ghani, Zizhao
            Wang, Peter Stone, and and Xuesu
            Xiao.
 In International Conference  on Intelligent Robots and Systems, October 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- Offline Action-Free Learning of Ex-BMDPs by Comparing Diverse Datasets.
 Alexander Levine, Peter
            Stone, and and Amy Zhang.
 In Reinforcement Learning Conference, August 2025.
 Details
                  
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            Download: 
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               (770.2kB
               )
- PACER: Preference-conditioned All-terrain Costmap Generation.
 Luisa Mao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 Robotics
            and Automation Letters, 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.2MB
               )
                [slides.pptx]
               (28.0MB
               )
- ProtoCRL: Prototype-based Network for Continual Reinforcement Learning.
 Michela Proietti, Peter
            R. Wurman, Peter Stone, and Roberto Capobianco.
 In Reinforcement
            Learning Conference, August 2025.
 Details
                  
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            Download: 
            [pdf]
               (2.1MB
               )
- Dyn-O: Building Structured World Models with Object-Centric Representations.
 Zizhao
            Wang, Kaixin Wang, Li Zhao, Peter Stone, and Jiang Bian.
 In Annual
            Conference on Neural Information Processing Systems, December 2025.
 Details
                  
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            Download: 
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               (22.9MB
               )
- LLM-GROP: Visually grounded robot task and motion planning with large language models.
 Xiaohan Zhang, Yan Ding,
            Yohei Hayamizu, Zainab Altaweel, Yifeng Zhu, Yuke
            Zhu, Peter Stone, Chris Paxton, and Shiqi
            Zhang.
 The International Journal of Robotics Research, 2025.
 Details
                  
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            Download: 
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               (2.5MB
               )
- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
 Zizhao
            Wang, Caroline Wang, Xuesu
            Xiao, Yuke Zhu, and Peter Stone.
 In
            AAAI Conference on Artificial Intelligence, February 2024.
 Details
                  
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            Download: 
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               (4.5MB
               )
- f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences.
 Siddhant Agarwal, Ishan
            Durugkar, Peter Stone, and Amy Zhang.
 In Conference on Neural Information
            Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (13.6MB
               )
                [poster.pdf]
               (1.8MB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
               BibTeX
                  
            Download: 
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               (4.8MB
               )
- ELDEN: Exploration via Local Dependencies.
 Zizhao Wang, Jiaheng
            Hu, Peter Stone, and Roberto Martín-Martín.
 In Conference on Neural
            Information Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.2MB
               )
                [slides.pptx]
               (22.4MB
               )
                [poster.pdf]
               (856.5kB
               )
FLI
      
      
         - Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
 Haresh,
            Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
 In
            International Conference on Robotics and Automation, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.3MB
               )
- Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu,
            Peter Stone, and Shiqi Zhang.
 In
            International Conference on Intelligent Robots and Systems (IROS), October 2023.
 Project
            website (includes poster and 5-minute video presentation)
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
                [slides.pdf]
               (6.6MB
               )
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
 Eddy Hudson, Garrett
            Warnell, Faraz Torabi, and Peter
            Stone.
 In International Conference on Robotics and Automation (ICRA), May 2022.
 Presentation
            Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.5MB
               )
- BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.
 Bo
            Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu.
 In Conference
            on Neural Information Processing Systems, 2022, December 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (1.6MB
               )
                [poster.pdf]
               (885.6kB
               )
- Visually Grounded Task and Motion Planning for Mobile Manipulation.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuke Zhu, Peter
            Stone, and Shiqi Zhang.
 In International Conference on Robotics
            and Automation (ICRA), May 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
- Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation.
 Yifeng
            Zhu, Peter Stone, and Yuke
            Zhu.
 IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.3MB
               )
- VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors.
 Yifeng
            Zhu, Abhishek Joshi, Peter Stone, and Yuke
            Zhu.
 In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.4MB
               )
- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
 Michael
            Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
 Operations
            Research, March 2021.
 Details
                  
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            Download: 
            [pdf]
               (692.5kB
               )
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
 Roberto Capobianco, Varun Kompella, James
            Ault, Guni Sharon, Stacy
            Jong, Spencer Fox, Lauren
            Meyers, Peter R. Wurman, and Peter
            Stone.
 The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
 Contains
            material that was previously published in an AAMAS
            2021 paper and a AAAI 2020 Fall
            Symposium paper.
 Article available from  JAIR website.
 Simulator
            source code.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
 Jiaxun
            Cui, William Macke, Harel
            Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
            Stone.
 In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2021.
 Project page, with videos
 Details
                  
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            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pptx]
               (1.5MB
               )
- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
 Yunshu Du, Garrett
            Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
            E. Taylor.
 Neural Computing and Applications, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
- Machine versus Human Attention in Deep Reinforcement Learning Tasks.
 Sihang Guo, Ruohan
            Zhang, Bo Liu, Yifeng Zhu,
            Mary Hayhoe, Dana Ballard, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy.
 Josiah
            P. Hanna, Scott Niekum, and Peter
            Stone.
 Machine Learning (MLJ), 110:1267–1317, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.7MB
               )
- Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation.
 Blake Holman, Abrar
            Anwar, Akash Singh, Mauricio Tec, Justin
            Hart, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.7MB
               )
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
 Eddy Hudson, Garrett
            Warnell, and Peter Stone.
 In Autonomous Robots and Multirobot Systems
            Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (393.0kB
               )
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
 Yuqian
            Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
 In
            Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
                [slides.pdf]
               (1.8MB
               )
- A Lifelong Learning Approach to Mobile Robot Navigation.
 Bo Liu, Xuesu Xiao, and Peter Stone.
 IEEE
            Robotics and Automation Letters (RA-L), 6(2), April 2021.
 Presented at IEEE International Conference on Robotics
            and Automation (ICRA),
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.6MB
               )
- Conflict-Averse Gradient Descent for Multi-task learning.
 Bo Liu, Xingchao
            Liu, Xiaojie Jin, Peter Stone, and Qiang Liu.
 In Conference on Neural
            Information Processing Systems (NeurIPS), 2021, December 2021.
 slides
            and 9-minute presentation
 github repository
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.7MB
               )
- Team  Orienteering  Coverage  Planning  with  Uncertain  Reward.
 Bo Liu,
            Xuesu Xiao, and Peter Stone.
 In
            International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
 Details
                  
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            Download: 
            [pdf]
               (3.9MB
               )
- Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition.
 Bo
            Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke
            Zhu, and Animashree Anandkumar.
 In Proceedings of the 38th International Conference on Machine Learning, PMLR 139,
            2021 (ICML), July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
                [poster.pdf]
               (1.1MB
               )
- Reasoning about Human Behavior in Ad Hoc Teamwork.
 Jennifer Suriadinata, William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
 Video
            Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (926.2kB
               )
- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (742.7kB
               )
- APPLR: Adaptive Planner Parameter Learning from Reinforcement.
 Zifan Xu,
            Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett
            Warnell, Bo Liu, Zizhao Wang,
            and Peter Stone.
 In Proceedings of the 2021 IEEE International Conference
            on Robotics and Automation (ICRA 2021), June 2021.
 Video
            presentation
 Project webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (27.4MB
               )
- Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning.
 Zifan
            Xu, Xuesu Xiao, Garrett
            Warnell, Anirudh Nair, and Peter Stone.
 In Proceedings of the 2021
            IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), October 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.5MB
               )
- A Scavenger Hunt for Service Robots.
 Harel Yedidsion,
            Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
            Stone.
 In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
 Harel
            Yedidsion, Shani Alkoby, and Peter
            Stone.
 Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
 arXiv
 Details
                  
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            Download: 
            [pdf]
               (478.9kB
               )
- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
 Siddarth Desai, Ishan
            Durugkar, Haresh Karnan, Garrett
            Warnell, Josiah Hanna, and Peter
            Stone.
 In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
            December 2020.
 Poster
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- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
 Siddharth Desai, Haresh
            Karnan, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 11-minute video
            presentation.
 Details
                  
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               (1.9MB
               )
- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
 Ishan
            Durugkar, Elad Liebman, and Peter
            Stone.
 In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
            2020.
 Details
                  
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               (3.9MB
               )
- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
 Justin Hart,
            Reuth Mirsky, Xuesu Xiao,
            Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
            Stone.
 In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
 Video presentation
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               )
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
 Haresh
            Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 14-minute video
            presentation.
 Details
                  
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               (506.6kB
               )
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
 Shih-Yun Lo, Shiqi
            Zhang, and Peter Stone.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, October 2020.
 Contains material that was previously published in an AAMAS-18
            paper (awarded the Best Robotics Paper Award at AAMAS 2018)
 Also
            available from  JAIR website
 Details
                  
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               (4.0MB
               )
- Learning and Reasoning for Robot Dialog and Navigation Tasks.
 Keting Lu, Shiqi
            Zhang, Peter Stone, and Xiaoping
            Chen.
 In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
            107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
 Official version from ACL
            Digital Library, including a link to the conference presentation
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               )
- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
 Sanmit
            Narvekar, Bei Peng, Matteo Leonetti, Jivko
            Sinapov, Matthew E. Taylor, and Peter
            Stone.
 Journal of Machine Learning Research, 21(181):1–50, 2020.
 Details
                  
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               (1.4MB
               )
- Generalizing Curricula for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In 4th Lifelong Learning Workshop at the International
            Conference on Machine Learning (ICML 2020), July 2020.
 Details
                  
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               (330.4kB
               )
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               (3.8MB
               )
- Learning to Improve Multi-Robot Hallway Navigation.
 Jin-Soo Park, Brian Tsang, Harel
            Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
 In Proceedings of the 4th Conference on Robot Learning (CoRL),
            November 2020.
 Video presentation
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               (1.3MB
               )
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
 Brahma
            Pavse, Faraz Torabi, Josiah
            Hanna, Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
 Video
            of the experiments; 13-minute video presentation.
 Details
                  
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               (405.1kB
               )
                [slides.pptx]
               (115.4MB
               )
- Reducing Sampling Error in Batch Temporal Difference Learning.
 Brahma Pavse,
            Ishan Durugkar, Josiah Hanna,
            and Peter Stone.
 In Proceedings of the 37th International Conference
            on Machine Learning (ICML), July 2020.
 The paper and talk is available from the ICML
            2020 virtual conference page.
 Details
                  
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               (738.4kB
               )
                [slides.pdf]
               (5.2MB
               )
- On Sampling Error in Batch Action-Value Prediction Algorithms.
 Brahma S. Pavse,
            Josiah P. Hanna, Ishan Durugkar,
            and Peter Stone.
 In In the Offline Reinforcement Learning Workshop at
            Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
 5-minute
            Video Presentation
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               (327.2kB
               )
- Deep R-Learning for Continual Area Sweeping.
 Rishi Shah, Yuqian Jiang, Justin
            Hart, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
 1-minute
            video demonstration; 13-minute Video
            presentation.
 Details
                  
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               (374.2kB
               )
                [slides.pdf]
               (1.1MB
               )
- Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks.
 Lemeng Wu, Bo
            Liu, Peter Stone, and Qiang Liu.
 In Advances in Neural Information
            Processing Systems 34 (2020), December 2020.
 Details
                  
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               (8.1MB
               )
                [slides.pdf]
               (744.8kB
               )
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
 Xuesu
            Xiao, Bo Liu, Garrett
            Warnell, Jonathan Fink, and Peter Stone.
 IEEE Robotics and Automation
            Letters (RA-L), June 2020.
 Presented at International Conference on Intelligent Robots and Systems ({IROS})\\  
             5-minute Video presentation; 15-minute
            Video presentation
 Project webpage
 Details
                  
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               (2.2MB
               )
                [slides.pdf]
               (21.1MB
               )
- Ad hoc Teamwork with Behavior Switching Agents.
 Manish Ravula, Shani Alkobi and Peter
            Stone.
 In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (350.4kB
               )
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
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               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems.
 Yuqian
            Jiang, Shiqi Zhang, Piyush
            Khandelwal, and Peter Stone.
 Frontiers of Information Technology
            and Electronic Engineering, 20(3):363–373, Springer, March 2019.
 Official version from Publisher's
            Webpage
 Details
                  
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               (412.1kB
               )
- Multi-Robot Planning with Conflicts and Synergies.
 Yuqian Jiang, Harel
            Yedidsion, Shiqi Zhang, Guni
            Sharon, and Peter Stone.
 Autonomous Robots, Springer, March 2019.
 Official version from Publisher's Webpage
 Details
                  
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               (2.0MB
               )
- Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
 Yuqian
            Jiang, Fangkai Yang, Shiqi
            Zhang, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
 Details
                  
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               (925.2kB
               )
- Open-World Reasoning for Service Robots.
 Yuqian Jiang, Nick
            Walker, Justin Hart, and Peter Stone.
 In
            Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
 Accompanying video
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               )
- The right music at the right time: adaptive personalized playlists based on sequence modeling.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone Peter Stone.
 Management Information Systems Quarterly, 43(3):765–786, Society for Information Management
            and The Management Information Systems Research Center, 2019.
 Available from publisher's
            website.
 Details
                  
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               (4.0MB
               )
- Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report.
 Rishi Shah, Yuqian
            Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta,
            Rachel Schlossman, Marika Murphy, Justin Hart, Luis
            Sentis, and Peter Stone.
 In AAAI Fall Symposium on Artificial Intelligence
            and Human-Robot Interaction for Service Robots in Human Environments (AI-HRI 2019), November 2019.
 Details
                  
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               (4.5MB
               )
- Agents teaching agents: a survey on inter-agent transfer learning.
 Felipe Leno
            Da Silva, Garrett Warnell, Anna
            Helena Reali Costa, and Peter Stone.
 Autonomous Agents and Multi-Agent
            Systems, Dec 2019.
 Official version from JAAMAS
 Details
                  
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               (572.4kB
               )
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
 Felipe
            Leno Da Silva, Anna Helena Reali Costa, and Peter
            Stone.
 In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
 Details
                  
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               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
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               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (6.1MB
               )
- Desiderata for Planning Systems in General-Purpose Service Robots.
 Nick Walker,
            Yuqian Jiang, Maya Cakmak, and
            Peter Stone.
 In Proceedings of the ICAPS Workshop on Planning and Robotics
            (PlanRob 2019), July 2019.
 Details
                  
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               (651.5kB
               )
- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
 Harel
            Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
            Stone, and Raymond Mooney.
 In International Conference on Social
            Robotics (ICSR), pp. 133–143, November 2019.
 Details
                  
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               (958.6kB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
ONR
      
      
         - L3M+P: Lifelong Planning with Large Language Models.
 Krish Agarwal, Yuqian Jiang,
            Jiaheng Hu, Bo Liu, and Peter
            Stone.
 In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.
 Details
                  
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               (1.2MB
               )
- Proto Successor Measure: Representing the Behavior Space of an RL Agent.
 Siddhant Agarwal, Harshit Sikchi, Peter
            Stone, and Amy Zhang.
 In International Conference on Machine Learning, June 2025.
 Details
                  
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               (911.1kB
               )
- Deadlock-free, Safe, and Decentralized Multi-Robot Navigation in Social Mini-Games via Discrete-Time Control Barrier Functions.
 Rohan Chandra, Vrushabh Zinage, Efstathios Bakolas, Peter
            Stone, and Joydeep Biswas.
 Autonomous Robots, 2025.
 Details
                  
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               (4.5MB
               )
                [poster.pdf]
               (1.7MB
               )
- Multi-Agent Inverse Reinforcement Learning in Real World Unstructured Pedestrian Crowds.
 Rohan
            Chandra, Haresh Karnan, Negar Mehr, Peter
            Stone, and Joydeep Biswas.
 In IEEE/RSJ International Conference on Intelligent
            Robots and Systems (IROS), October 2025.
 Details
                  
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               (695.7kB
               )
- Dyna-LfLH: Learning Agile Navigation in Dynamic Environments from Learned Hallucination.
 Saad Abdul Ghani, Zizhao
            Wang, Peter Stone, and and Xuesu
            Xiao.
 In International Conference  on Intelligent Robots and Systems, October 2025.
 Details
                  
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               (2.1MB
               )
- SLAC: Simulation-Pretrained Latent Action Space for Whole-Body Real-World RL.
 Jiaheng
            Hu, Peter Stone, and Roberto Martín-Martín.
 In Conference on Robot
            Learning (CoRL), September 2025.
 Details
                  
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               (2.6MB
               )
- Reinforcement Learning within the Classical Robotics Stack: A Case Study in Robot Soccer.
 Adam Labiosa, Zhihan Wang,
            Siddhant Agarwal, William Cong, Geethika Hemkumar, Abhinav Narayan Harish, Benjamin Hong, Josh Kelle, Chen Li, Yuhao Li, Zisen
            Shao, Peter Stone, and Josiah
            Hanna.
 In International Conference on Robotics and Automation (ICRA), May 2025.
 Details
                  
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               (1.1MB
               )
- Offline Action-Free Learning of Ex-BMDPs by Comparing Diverse Datasets.
 Alexander Levine, Peter
            Stone, and and Amy Zhang.
 In Reinforcement Learning Conference, August 2025.
 Details
                  
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               (770.2kB
               )
- Longhorn: State Space Models are Amortized Online Learners.
 Bo Liu,
            Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, and qiang liu.
 In International
            Conference on Learning Representations, April 2025.
 Details
                  
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               (877.2kB
               )
- PACER: Preference-conditioned All-terrain Costmap Generation.
 Luisa Mao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 Robotics
            and Automation Letters, 2025.
 Details
                  
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               (3.2MB
               )
                [slides.pptx]
               (28.0MB
               )
- ProtoCRL: Prototype-based Network for Continual Reinforcement Learning.
 Michela Proietti, Peter
            R. Wurman, Peter Stone, and Roberto Capobianco.
 In Reinforcement
            Learning Conference, August 2025.
 Details
                  
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               (2.1MB
               )
- PRESTO: Fast Motion Planning Using Diffusion Models Based on Key-Configuration Environment Representation.
 Mingyo
            Seo, Yoonyoung Cho, Yoonchang Sung, Peter
            Stone, Yuke Zhu, and Beomjoon Kim.
 In IEEE International Conference
            on Robotics and Automation (ICRA), May 2025.
 Details
                  
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               (1.4MB
               )
                [slides.pdf]
               (2.1MB
               )
                [poster.pdf]
               (1.3MB
               )
- Dyn-O: Building Structured World Models with Object-Centric Representations.
 Zizhao
            Wang, Kaixin Wang, Li Zhao, Peter Stone, and Jiang Bian.
 In Annual
            Conference on Neural Information Processing Systems, December 2025.
 Details
                  
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               (22.9MB
               )
- LLM-GROP: Visually grounded robot task and motion planning with large language models.
 Xiaohan Zhang, Yan Ding,
            Yohei Hayamizu, Zainab Altaweel, Yifeng Zhu, Yuke
            Zhu, Peter Stone, Chris Paxton, and Shiqi
            Zhang.
 The International Journal of Robotics Research, 2025.
 Details
                  
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               (2.5MB
               )
- Learning to Look: Seeking Information for Decision Making via Policy Factorization.
 Shivin Dass, Jiaheng
            Hu, Ben Abbatematteo, Peter Stone, and Roberto Martín-Martín.
 In Conference
            on Robot Learning (CoRL), November 2024.
 Details
                  
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               (6.8MB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            P. Hanna, Yash Chandak, Philip S. Thomas, Martha White,
            Peter Stone, and Scott Niekum.
 Journal
            of Machine Learning Research, 2024.
 Official version on publisher's
            website
 Details
                  
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               (1.7MB
               )
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
 Haresh,
            Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
 In
            International Conference on Robotics and Automation, May 2024.
 Details
                  
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               (4.3MB
               )
- Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning.
 Jiaheng
            Hu, Zizhao Wang, Roberto Martín-Martín, and Peter
            Stone.
 In Conference on Neural Information Parocessing Systems (NeurIPS), December 2024.
 Details
                  
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               (2.7MB
               )
- Learning Optimal Advantage from Preferences and Mistaking it for Reward.
 W. Bradley
            Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter
            Stone, and Scott Niekum.
 In The 38th Annual AAAI Conference on Artificial
            Intelligence (AAAI), February 2024.
 Details
                  
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               (3.6MB
               )
                [slides.pdf]
               (3.9MB
               )
                [poster.pdf]
               (2.9MB
               )
- Conflict Avoidance in Social Navigation --- a Survey.
 Reuth
            Mirsky, Xuesu Xiao, Justin Hart, and
            Peter Stone.
 ACM Transactions on Human-Robot Interaction, 2024.
 Details
                  
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               (2.1MB
               )
- The Human in the Loop: Perspectives and Challenges for RoboCup 2050.
 Alessandra Rossi, Maike Paetzel-Prüsmann,
            Merel Keijsers, Michael Anderson, Susan Leigh Anderson, Daniel Barry, Jan Gutsche, Justin
            Hart, Luca Iocchi, Ainse Kokkelmans, Wouter Kuijpers, Yun Liu, Daniel
            Polani, Caleb Roscon, Marcus Scheunemann, Peter Stone, Florian Vahl, René
            van de Molengraft, and Oskar von Stryk.
 Autonomous
            Robots, May 2024.
 Official version on publisher's website
 Details
                  
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               (2.1MB
               )
- Relaxed Exploration Constrained Reinforcement Learning.
 Shahaf S. Shperberg, Bo
            Liu, and Peter Stone.
 In Conference on Autonomous Agents and Multiagent
            Systems, May 2024.
 Details
                  
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               (3.4MB
               )
- Dobby: A Conversational Service Robot Driven by GPT-4.
 Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
            Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
            Hart.
 In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
 Details
                  
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               (863.8kB
               )
                [poster.pdf]
               (892.0kB
               )
- Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning.
 Yoonchang
            Sung, Rahul Shome, and Peter Stone.
 In IEEE International Conference
            on Robotics and Automation (ICRA), March 2024.
 Video
            presentation
 Details
                  
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               (482.7kB
               )
- Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes.
 Chen
            Tang, Ben Abbatematteo, Jiaheng Hu, Rohan
            Chandra, Roberto Martín-Martín, and Peter Stone.
 Annual Review
            of Control, Robotics, and Autonomous Systems (ARCRAS), 8:153–88, 2024.
 Presented in Senior member track at
            AAAI 2025
 Official
            version on publisher's website
 Details
                  
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               (4.3MB
               )
                [slides.pdf]
               (2.9MB
               )
                [poster.pdf]
               (604.3kB
               )
- SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions.
 Zizhao
            Wang, Jiaheng Hu, Caleb Chuck, Stephen
            Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2024.
 Details
                  
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               (2.1MB
               )
- N-Agent Ad Hoc Teamwork.
 Caroline Wang, Arrasy
            Rahman, Ishan Durugkar, Elad
            Liebman, and Peter Stone.
 In Conference on Neural Information Processing
            Systems (NeurIPS), December 2024.
 Details
                  
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               (1.6MB
               )
                [slides.pdf]
               (1.3MB
               )
                [poster.pdf]
               (1.7MB
               )
- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
 Zizhao
            Wang, Caroline Wang, Xuesu
            Xiao, Yuke Zhu, and Peter Stone.
 In
            AAAI Conference on Artificial Intelligence, February 2024.
 Details
                  
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               (4.5MB
               )
- LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning.
 Zifan Xu, Haozhu
            Wang, Dmitriy Bespalov, Xian Wu, Peter Stone, and Yanjun Qi.
 In Findings
            of Empirical Methods in Natural Language Processing, November 2024.
 Details
                  
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               (1.6MB
               )
- Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks.
 Ziping Xu, Zifan
            Xu, Runxuan Jiang, Peter Stone, and Ambuj
            Tewari.
 In International Conference on Learning Representations (ICLR), May 2024.
 Details
                  
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               (1.4MB
               )
- Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning.
 Zifan
            Xu, Amir Hossain Raj, Xuesu Xiao, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation, May 2024.
 Details
                  
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               (2.0MB
               )
- t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making.
 William Yue,
            Bo Liu, and Peter Stone.
 In
            Conference on Lifelong Learning Agents (CoLLAs), July 2024.
 Details
                  
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               (599.7kB
               )
                [poster.pdf]
               (709.1kB
               )
- iCORPP: Interleaved commonsense reasoning and probabilistic planning on robots.
 Shiqi
            Zhang, Piyush Khandelwal, and Peter
            Stone.
 Robotics and Autonomous Systems, 2024.
 Details
                  
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               (2.0MB
               )
- f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences.
 Siddhant Agarwal, Ishan
            Durugkar, Peter Stone, and Amy Zhang.
 In Conference on Neural Information
            Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (13.6MB
               )
                [poster.pdf]
               (1.8MB
               )
- Task Phasing: Automated Curriculum Learning from Demonstrations.
 Vaibhav Bajaj, Guni
            Sharon, and Peter Stone.
 In Proceedings of the 33rd International
            Conference on Automated Planning and Scheduling (ICAPS 2023), July 2023.
 Accompanying code
 Details
                  
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            Download: 
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               (416.0kB
               )
- "What's That Robot Doing Here?": Factors Influencing Perceptions Of Incidental Encounters With Autonomous Quadruped Robots.
 Elliott
            Hauser, Yao-Cheng Chan, Geethika Hemkumar, Daksh Dua, Parth Chonkar, Efren Mendoza Enriquez, Tiffany Kao, Shikhar Gupta, Huihai
            Wang, Justin Hart, Reuth Mirsky,
            Joydeep Biswas, Junfeng Jiao, and Peter
            Stone.
 In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23), pp.
            1–15, July 2023.
 Available online at https://dl.acm.org/doi/10.1145/3597512.3599707
 Details
                  
               BibTeX
                  
            Download: 
            
            (unavailable)
- Causal Policy Gradient for Whole-Body Mobile Manipulation.
 Jiaheng Hu,
            Peter Stone, and Roberto Martin-Martin.
 In Robotics: Science and Systems
            (RSS), July 2023.
 Details
                  
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            Download: 
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               (4.0MB
               )
- VaryNote: A Method to Automatically Vary the Number of Notes in           Symbolic Music.
 Juan M. Huerta, Bo
            Liu, and Peter Stone.
 In The 16th International Symposium on Computer
            Music Multidisciplinary Research, (CMMR), Springer, November 2023.
 the
            conference presentation
 Details
                  
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               (1.4MB
               )
                [slides.pdf]
               (2.3MB
               )
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
 Haresh
            Karnan, Elvin Yang, Daniel Farkash, Garrett
            Warnell, Joydeep Biswas, and Peter
            Stone.
 In The Conference on Robot Learning (CoRL), November 2023.
 Poster,
            Video, Project Website
 Details
                  
               BibTeX
                  
            Download: 
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               (25.7MB
               )
- Models of human preference for learning reward functions.
 W. Bradley Knox,
            Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
            Stone, and Alessandro Allievi.
 Transactions on Machine Learning Research (TMLR), 2023.
 Details
                  
               BibTeX
                  
            Download: 
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               (6.7MB
               )
                [slides.pdf]
               (13.4MB
               )
- Reward (Mis)design for Autonomous Driving.
 W. Bradley Knox, Alessandro Allievi,
            Holger Banzhaf, Felix Schmitt, and Peter Stone.
 Artificial Intelligence,
            316:103829, 2023.
 Paper webpage
 Details
                  
               BibTeX
                  
            Download: 
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               (696.3kB
               )
                [ps]
               (5.6MB
               )
- FAMO: Fast Adaptive Multitask Optimization.
 Bo Liu, Yihao Feng, Peter Stone, and Qiang Liu.
 In Neural Information Processing Systems Foundation,
            July 2023.
 Details
                  
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            Download: 
            [pdf]
               (3.0MB
               )
- LIBERO: Benchmarking Knowledge Transfer in Lifelong Robot Learning.
 Bo
            Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke
            Zhu, and Peter Stone.
 In 37th Conference on Neural Information Processing
            Systems (NeurIPS 2023) Track on Datasets and Benchmarks, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (37.6MB
               )
                [poster.pdf]
               (2.6MB
               )
- Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning.
 Bo
            Liu, Yihao Feng, Qiang Liu, and Peter Stone.
 In Thirty-Seventh AAAI
            Conference on Artificial Intelligence (AAAI), Februray 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
- Exploring the Cost of Interruptions in Human-Robot Teaming.
 Swathi Mannem, William
            Macke, Peter Stone, and Reuth
            Mirsky.
 In IEEE-RAS Humanoids, December 2023.
 Details
                  
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            Download: 
            [pdf]
               (921.5kB
               )
                [poster.pdf]
               (294.3kB
               )
- Towards a Real-Time, Low-Resource, End-to-end Object Detection Pipeline for Robot Soccer.
 Sai Kiran Narayanaswami,
            Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit
            Narvekar, and Peter Stone.
 In Amy Eguchi, Nuno Lau, Maike Paetzel-Prussman,
            and Thanapat Wanichanon, editors, RoboCup 2022: Robot World Cup XXV, pp. 62–74, Springer International Publishing,
            2023.
 The book
 Details
                  
               BibTeX
                  
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            [pdf]
               (572.2kB
               )
- Program Embeddings for Rapid Mechanism Evaluation.
 Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
            and Peter Stone.
 In ICRA Workshop on Multi-Robot Learning, May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.3MB
               )
                [poster.pdf]
               (916.2kB
               )
- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
 Jinsoo Park, Xuesu
            Xiao, Garrett Warnell, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 6-minute video
            presentation
 Details
                  
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            Download: 
            [pdf]
               (4.6MB
               )
                [slides.pptx]
               (21.3MB
               )
                [poster.pdf]
               (1.1MB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
- Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search.
 Yoonchang
            Sung and Peter Stone.
 In Robotics: Science and Systems (RSS2023),
            July 2023.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.9MB
               )
                [slides.pdf]
               (8.1MB
               )
                [poster.pdf]
               (6.9MB
               )
- ELDEN: Exploration via Local Dependencies.
 Zizhao Wang, Jiaheng
            Hu, Peter Stone, and Roberto Martín-Martín.
 In Conference on Neural
            Information Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.2MB
               )
                [slides.pptx]
               (22.4MB
               )
                [poster.pdf]
               (856.5kB
               )
- D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning.
 Caroline
            Wang, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
                [slides.pdf]
               (2.4MB
               )
                [poster.pdf]
               (1.4MB
               )
- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
 Caroline
            Wang, Ishan Durugkar, Elad Liebman,
            and Peter Stone.
 In Proceedings of the 37th AAAI Conference on Artificial
            Intelligence (AAAI-23), February 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (801.2kB
               )
                [slides.pdf]
               (3.7MB
               )
                [poster.pdf]
               (1.4MB
               )
- Model-Based Meta Automatic Curriculum Learning.
 Zifan Xu, Yulin
            Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian
            Jiang, Bo Liu, and Peter Stone.
 In
            The Second Conference on Lifelong Learning Agents (CoLLAs), August 2023.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
                [slides.pptx]
               (6.6MB
               )
- Benchmarking Reinforcement Learning Techniques for Autonomous Navigation.
 Zifan
            Xu, Bo Liu, Xuesu Xiao, Anirudh
            Nair, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
- Learning Real-world Autonomous Navigation by Self-Supervised Environment Synthesis.
 Zifan
            Xu, Anirudh Nair, Xuesu Xiao, and Peter
            Stone.
 In IROS Workshop on Photorealistic Image and Environment Synthesis for Robotics (PIES-Rob) , January
            2023.
 Details
                  
               BibTeX
                  
            Download: 
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               (4.3MB
               )
- Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.
 Xiaohan Zhang, Saeid Amiri,
            Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
 Autonomous
            Robots, March 2023.
 Official version
            on publisher's website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.6MB
               )
- Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu,
            Peter Stone, and Shiqi Zhang.
 In
            International Conference on Intelligent Robots and Systems (IROS), October 2023.
 Project
            website (includes poster and 5-minute video presentation)
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
                [slides.pdf]
               (6.6MB
               )
- Learning Generalizable Manipulation Policies with Object-Centric 3D Representations.
 Yifeng
            Zhu, Zhenyu Jiang, Peter Stone, and Yuke
            Zhu.
 In Conference on Robot Learning (CoRL), November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (7.3MB
               )
                [poster.pdf]
               (5.2MB
               )
- Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles.
 Jiaxun
            Cui, Hang Qiu, Dian Chen, Peter
            Stone, and Yuke Zhu.
 In IEEE/CVF Conference on Computer Vision and
            Pattern Recognition (CVPR), June 2022.
 Project website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.5MB
               )
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
 Eddy Hudson, Garrett
            Warnell, Faraz Torabi, and Peter
            Stone.
 In International Conference on Robotics and Automation (ICRA), May 2022.
 Presentation
            Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.5MB
               )
- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
 Haresh Karnan, Anirudh Nair, Xuesu Xiao,
            Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
            Hart, Joydeep Biswas, and Peter Stone.
 Robotics
            and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
 Dataset;
            Poster; Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
 Haresh
            Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 In
            International Conference on Intelligent Robots and Systems, 2022, October 2022.
 Details
                  
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            Download: 
            [pdf]
               (3.0MB
               )
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
 Haresh
            Karnan, Garrett Warnell, Xuesu
            Xiao, and Peter Stone.
 In International Conference on Robotics and
            Automation, 2022, May 2022.
 Poster,
            Video
 Details
                  
               BibTeX
                  
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            [pdf]
               (1.5MB
               )
- Adversarial Imitation Learning from Video using a State Observer.
 Haresh
            Karnan, Garrett Warnell, Faraz
            Torabi, and Peter Stone.
 In International Conference on Robotics
            and Automation, 2022, May 2022.
 Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (933.2kB
               )
- Effective Mutation Rate Adaptation through Group Elite Selection.
 Akarsh Kumar, Bo
            Liu, Risto Miikkulainen, and Peter
            Stone.
 In Proceedings of the Genetic and Evolutionary Computation Conference, July 2022.
 Details
                  
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            Download: 
            [pdf]
               (9.7MB
               )
- BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.
 Bo
            Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu.
 In Conference
            on Neural Information Processing Systems, 2022, December 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (1.6MB
               )
                [poster.pdf]
               (885.6kB
               )
- Continual Learning and Private Unlearning.
 Bo Liu, Qiang Liu, and Peter Stone.
 In Proceedings of the 1st Conference on Lifelong Learning Agents
            (CoLLA), August 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (440.4kB
               )
                [slides.pdf]
               (710.5kB
               )
- UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions.
 Patrick
            MacAlpine, Bo Liu, William Macke,
            Caroline Wang, and Peter Stone.
 In
            Rachid Alami, Joydeep Biswas, Maya
            Cakmak, and Oliver Obst, editors, RoboCup 2021: Robot World Cup XXIV, pp. 314–26, Springer International
            Publishing, 2022.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021
 Details
                  
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               (2.5MB
               )
- Value Function Decomposition for Iterative Design of Reinforcement Learning Agents.
 James MacGlashan, Evan Archer,
            Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2022.
 5-minute
            Video Presentation; the
            slides
 Details
                  
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            [pdf]
               (11.6MB
               )
- Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings.
 Kingsley Nweye, Bo
            Liu, Nagy Zoltan, and Peter Stone.
 Journal of Energy and AI, 2022,
            September 2022.
 Details
                  
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            [pdf]
               (5.9MB
               )
- A Rule-based Shield: Accumulating Safety Rules from Catastrophic Action Effects.
 Shahaf Shperberg, Bo
            Liu, Allessandro Allievi, and Peter Stone.
 In Proceedings of the
            1st Conference on Lifelong Learning Agents (CoLLA), August 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (8.9MB
               )
- Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning.
 Yoonchang
            Sung, Zizhao Wang, and Peter Stone.
 In
            Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Details
                  
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            Download: 
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               (742.0kB
               )
                [poster.pdf]
               (5.7MB
               )
- Causal Dynamics Learning for Task-Independent State Abstraction.
 Zizhao
            Wang, Xuesu Xiao, Zifan Xu, Yuke
            Zhu, and Peter Stone.
 In Proceedings of the 39th International Conference
            on Machine Learning (ICML2022), July 2022.
 recorded presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (4.0MB
               )
                [poster.pdf]
               (1.6MB
               )
- Visually Grounded Task and Motion Planning for Mobile Manipulation.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuke Zhu, Peter
            Stone, and Shiqi Zhang.
 In International Conference on Robotics
            and Automation (ICRA), May 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
- Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation.
 Yifeng
            Zhu, Peter Stone, and Yuke
            Zhu.
 IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.3MB
               )
- VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors.
 Yifeng
            Zhu, Abhishek Joshi, Peter Stone, and Yuke
            Zhu.
 In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.4MB
               )
- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
 Michael
            Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
 Operations
            Research, March 2021.
 Details
                  
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               (692.5kB
               )
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
 Roberto Capobianco, Varun Kompella, James
            Ault, Guni Sharon, Stacy
            Jong, Spencer Fox, Lauren
            Meyers, Peter R. Wurman, and Peter
            Stone.
 The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
 Contains
            material that was previously published in an AAMAS
            2021 paper and a AAAI 2020 Fall
            Symposium paper.
 Article available from  JAIR website.
 Simulator
            source code.
 Details
                  
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               (1.6MB
               )
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
 Jiaxun
            Cui, William Macke, Harel
            Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
            Stone.
 In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2021.
 Project page, with videos
 Details
                  
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            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pptx]
               (1.5MB
               )
- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
 Yunshu Du, Garrett
            Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
            E. Taylor.
 Neural Computing and Applications, May 2021.
 Details
                  
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            Download: 
            [pdf]
               (2.2MB
               )
- Adversarial Intrinsic Motivation for Reinforcement Learning.
 Ishan Durugkar,
            Mauricio Tec, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
            December 2021.
 slides and video presentation
 Details
                  
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            Download: 
            [pdf]
               (5.1MB
               )
- Machine versus Human Attention in Deep Reinforcement Learning Tasks.
 Sihang Guo, Ruohan
            Zhang, Bo Liu, Yifeng Zhu,
            Mary Hayhoe, Dana Ballard, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2021.
 Details
                  
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            Download: 
            [pdf]
               (1.6MB
               )
- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
 Josiah
            P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
            Warnell, and Peter Stone.
 Special Issue on Reinforcement Learning
            for Real Life, Machine Learning, 2021, May 2021.
 Details
                  
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            Download: 
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               (3.0MB
               )
- Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy.
 Josiah
            P. Hanna, Scott Niekum, and Peter
            Stone.
 Machine Learning (MLJ), 110:1267–1317, May 2021.
 Details
                  
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            Download: 
            [pdf]
               (3.7MB
               )
- Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation.
 Blake Holman, Abrar
            Anwar, Akash Singh, Mauricio Tec, Justin
            Hart, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA), May 2021.
 Details
                  
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            Download: 
            [pdf]
               (5.7MB
               )
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
 Eddy Hudson, Garrett
            Warnell, and Peter Stone.
 In Autonomous Robots and Multirobot Systems
            Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
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            Download: 
            [pdf]
               (393.0kB
               )
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
 Yuqian
            Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
 In
            Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
 Details
                  
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            Download: 
            [pdf]
               (1.8MB
               )
                [slides.pdf]
               (1.8MB
               )
- A Lifelong Learning Approach to Mobile Robot Navigation.
 Bo Liu, Xuesu Xiao, and Peter Stone.
 IEEE
            Robotics and Automation Letters (RA-L), 6(2), April 2021.
 Presented at IEEE International Conference on Robotics
            and Automation (ICRA),
 Video presentation
 Details
                  
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            Download: 
            [pdf]
               (3.6MB
               )
- Conflict-Averse Gradient Descent for Multi-task learning.
 Bo Liu, Xingchao
            Liu, Xiaojie Jin, Peter Stone, and Qiang Liu.
 In Conference on Neural
            Information Processing Systems (NeurIPS), 2021, December 2021.
 slides
            and 9-minute presentation
 github repository
 Details
                  
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            Download: 
            [pdf]
               (9.7MB
               )
- Team  Orienteering  Coverage  Planning  with  Uncertain  Reward.
 Bo Liu,
            Xuesu Xiao, and Peter Stone.
 In
            International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
 Details
                  
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            Download: 
            [pdf]
               (3.9MB
               )
- Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition.
 Bo
            Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke
            Zhu, and Animashree Anandkumar.
 In Proceedings of the 38th International Conference on Machine Learning, PMLR 139,
            2021 (ICML), July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
                [poster.pdf]
               (1.1MB
               )
- Reasoning about Human Behavior in Ad Hoc Teamwork.
 Jennifer Suriadinata, William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
 Video
            Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (926.2kB
               )
- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (742.7kB
               )
- APPLR: Adaptive Planner Parameter Learning from Reinforcement.
 Zifan Xu,
            Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett
            Warnell, Bo Liu, Zizhao Wang,
            and Peter Stone.
 In Proceedings of the 2021 IEEE International Conference
            on Robotics and Automation (ICRA 2021), June 2021.
 Video
            presentation
 Project webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (27.4MB
               )
- Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning.
 Zifan
            Xu, Xuesu Xiao, Garrett
            Warnell, Anirudh Nair, and Peter Stone.
 In Proceedings of the 2021
            IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), October 2021.
 Video
            presentation
 Details
                  
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            Download: 
            [pdf]
               (4.5MB
               )
- A Scavenger Hunt for Service Robots.
 Harel Yedidsion,
            Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
            Stone.
 In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
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               (1.5MB
               )
- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
 Harel
            Yedidsion, Shani Alkoby, and Peter
            Stone.
 Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
 arXiv
 Details
                  
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               (478.9kB
               )
- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
 Siddarth Desai, Ishan
            Durugkar, Haresh Karnan, Garrett
            Warnell, Josiah Hanna, and Peter
            Stone.
 In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
            December 2020.
 Poster
 Details
                  
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               (1.3MB
               )
- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
 Siddharth Desai, Haresh
            Karnan, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 11-minute video
            presentation.
 Details
                  
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               (1.9MB
               )
- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
 Ishan
            Durugkar, Elad Liebman, and Peter
            Stone.
 In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
            2020.
 Details
                  
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               (3.9MB
               )
- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
 Justin Hart,
            Reuth Mirsky, Xuesu Xiao,
            Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
            Stone.
 In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
 Video presentation
 Details
                  
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               (3.2MB
               )
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
 Haresh
            Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 14-minute video
            presentation.
 Details
                  
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               (506.6kB
               )
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
 Shih-Yun Lo, Shiqi
            Zhang, and Peter Stone.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, October 2020.
 Contains material that was previously published in an AAMAS-18
            paper (awarded the Best Robotics Paper Award at AAMAS 2018)
 Also
            available from  JAIR website
 Details
                  
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               (4.0MB
               )
- Learning and Reasoning for Robot Dialog and Navigation Tasks.
 Keting Lu, Shiqi
            Zhang, Peter Stone, and Xiaoping
            Chen.
 In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
            107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
 Official version from ACL
            Digital Library, including a link to the conference presentation
 Details
                  
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               (3.6MB
               )
- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
 Sanmit
            Narvekar, Bei Peng, Matteo Leonetti, Jivko
            Sinapov, Matthew E. Taylor, and Peter
            Stone.
 Journal of Machine Learning Research, 21(181):1–50, 2020.
 Details
                  
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               (1.4MB
               )
- Generalizing Curricula for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In 4th Lifelong Learning Workshop at the International
            Conference on Machine Learning (ICML 2020), July 2020.
 Details
                  
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            Download: 
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               (330.4kB
               )
                [slides.pdf]
               (3.8MB
               )
- Learning to Improve Multi-Robot Hallway Navigation.
 Jin-Soo Park, Brian Tsang, Harel
            Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
 In Proceedings of the 4th Conference on Robot Learning (CoRL),
            November 2020.
 Video presentation
 Details
                  
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               (1.3MB
               )
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
 Brahma
            Pavse, Faraz Torabi, Josiah
            Hanna, Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
 Video
            of the experiments; 13-minute video presentation.
 Details
                  
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               (405.1kB
               )
                [slides.pptx]
               (115.4MB
               )
- Reducing Sampling Error in Batch Temporal Difference Learning.
 Brahma Pavse,
            Ishan Durugkar, Josiah Hanna,
            and Peter Stone.
 In Proceedings of the 37th International Conference
            on Machine Learning (ICML), July 2020.
 The paper and talk is available from the ICML
            2020 virtual conference page.
 Details
                  
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            Download: 
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               (738.4kB
               )
                [slides.pdf]
               (5.2MB
               )
- On Sampling Error in Batch Action-Value Prediction Algorithms.
 Brahma S. Pavse,
            Josiah P. Hanna, Ishan Durugkar,
            and Peter Stone.
 In In the Offline Reinforcement Learning Workshop at
            Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
 5-minute
            Video Presentation
 Details
                  
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               (327.2kB
               )
- Deep R-Learning for Continual Area Sweeping.
 Rishi Shah, Yuqian Jiang, Justin
            Hart, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
 1-minute
            video demonstration; 13-minute Video
            presentation.
 Details
                  
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            Download: 
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               (374.2kB
               )
                [slides.pdf]
               (1.1MB
               )
- Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks.
 Lemeng Wu, Bo
            Liu, Peter Stone, and Qiang Liu.
 In Advances in Neural Information
            Processing Systems 34 (2020), December 2020.
 Details
                  
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            Download: 
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               (8.1MB
               )
                [slides.pdf]
               (744.8kB
               )
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
 Xuesu
            Xiao, Bo Liu, Garrett
            Warnell, Jonathan Fink, and Peter Stone.
 IEEE Robotics and Automation
            Letters (RA-L), June 2020.
 Presented at International Conference on Intelligent Robots and Systems ({IROS})\\  
             5-minute Video presentation; 15-minute
            Video presentation
 Project webpage
 Details
                  
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               (2.2MB
               )
                [slides.pdf]
               (21.1MB
               )
- Ad hoc Teamwork with Behavior Switching Agents.
 Manish Ravula, Shani Alkobi and Peter
            Stone.
 In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (350.4kB
               )
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
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            Download: 
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               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Reducing Sampling Error in Policy Gradient Learning.
 Josiah Hanna
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 This paper contains material that was previously
            presented at the 2018 NeurIPS Deep Reinforcement Learning Workshop.
 Details
                  
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               (1.5MB
               )
                [slides.pdf]
               (3.1MB
               )
- Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems.
 Yuqian
            Jiang, Shiqi Zhang, Piyush
            Khandelwal, and Peter Stone.
 Frontiers of Information Technology
            and Electronic Engineering, 20(3):363–373, Springer, March 2019.
 Official version from Publisher's
            Webpage
 Details
                  
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               (412.1kB
               )
- Multi-Robot Planning with Conflicts and Synergies.
 Yuqian Jiang, Harel
            Yedidsion, Shiqi Zhang, Guni
            Sharon, and Peter Stone.
 Autonomous Robots, Springer, March 2019.
 Official version from Publisher's Webpage
 Details
                  
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               (2.0MB
               )
- Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
 Yuqian
            Jiang, Fangkai Yang, Shiqi
            Zhang, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
 Details
                  
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               (925.2kB
               )
- Open-World Reasoning for Service Robots.
 Yuqian Jiang, Nick
            Walker, Justin Hart, and Peter Stone.
 In
            Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
 Accompanying video
 Details
                  
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               (813.5kB
               )
- The right music at the right time: adaptive personalized playlists based on sequence modeling.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone Peter Stone.
 Management Information Systems Quarterly, 43(3):765–786, Society for Information Management
            and The Management Information Systems Research Center, 2019.
 Available from publisher's
            website.
 Details
                  
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               (4.0MB
               )
- UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions.
 Patrick
            MacAlpine, Faraz Torabi, Brahma
            Pavse, and Peter Stone.
 In Stephan Chalup, Tim Niemueller, Jackrit Suthakorn,
            and Mary-Anne Williams, editors, RoboCup 2019: Robot World Cup XXIII, Lecture Notes in Artificial Intelligence, pp.
            540–52, Springer, 2019.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2019
 Details
                  
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               (233.2kB
               )
                [ps]
               (3.8MB
               )
- UT Austin Villa: RoboCup 2018 3D Simulation League Champions.
 Patrick
            MacAlpine, Faraz Torabi, Brahma
            Pavse, John Sigmon, and Peter Stone.
 In Dirk Holz, Katie
            Genter, Maarouf Saad, and Oskar von Stryk, editors,
            RoboCup 2018: Robot Soccer World Cup XXII, Lecture Notes in Artificial Intelligence, pp. 462–75, Springer, 2019.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2018
 Details
                  
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               (486.2kB
               )
                [ps]
               (6.0MB
               )
- Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report.
 Rishi Shah, Yuqian
            Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta,
            Rachel Schlossman, Marika Murphy, Justin Hart, Luis
            Sentis, and Peter Stone.
 In AAAI Fall Symposium on Artificial Intelligence
            and Human-Robot Interaction for Service Robots in Human Environments (AI-HRI 2019), November 2019.
 Details
                  
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               (4.5MB
               )
- Agents teaching agents: a survey on inter-agent transfer learning.
 Felipe Leno
            Da Silva, Garrett Warnell, Anna
            Helena Reali Costa, and Peter Stone.
 Autonomous Agents and Multi-Agent
            Systems, Dec 2019.
 Official version from JAAMAS
 Details
                  
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               (572.4kB
               )
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
 Felipe
            Leno Da Silva, Anna Helena Reali Costa, and Peter
            Stone.
 In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
 Details
                  
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               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (6.1MB
               )
- Desiderata for Planning Systems in General-Purpose Service Robots.
 Nick Walker,
            Yuqian Jiang, Maya Cakmak, and
            Peter Stone.
 In Proceedings of the ICAPS Workshop on Planning and Robotics
            (PlanRob 2019), July 2019.
 Details
                  
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               (651.5kB
               )
- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
 Harel
            Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
            Stone, and Raymond Mooney.
 In International Conference on Social
            Robotics (ICSR), pp. 133–143, November 2019.
 Details
                  
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               (958.6kB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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            Download: 
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               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Bringing Smart Transport to Texans:  Ensuring the Benefits of a	Connected and Autonomous Transport System in Texas ---
            Final Report.
 Kara Kockelman, Stephen Boyles, Purser
            Sturgeon, Christian Claudel, Lisa Loftus-Otway, Wendy Wagner, Duncan Stewart, Guni
            Sharon, Michael Albert, Peter
            Stone, Josiah Hanna, Yantao Huang, Krishna Murthy Gurumurthy, Dongxu
            He, Abduallah Mohamed, Rahul Patel, Tian Lei, Michele Simoni, and Sadegh Yarmohammadisatri.
 Technical Report 0-6838-3,
            The University of Texas at Austin Center for Transportation Research, 2018.
 Available
            online
 Details
                  
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            (unavailable)
- Overlapping Layered Learning.
 Patrick MacAlpine and Peter
            Stone.
 Artificial Intelligence, 254:21–43, Elsevier, January 2018.
 Official version from Publisher's
            Webpage
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/overlappingLayeredLearning.html
 Details
                  
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               (1.2MB
               )
                [ps]
               (3.8MB
               )
- UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions.
 Patrick
            MacAlpine and Peter Stone.
 In Claude Sammut, Oliver Obst, Flavio Tonidandel,
            and Hidehisa Akyama, editors, RoboCup 2017: Robot Soccer World Cup XXI, Lecture Notes in Artificial Intelligence, pp.
            473–85, Springer, 2018.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2017
 Details
                  
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               (973.5kB
               )
                [ps]
               (19.4MB
               )
- Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science.
 Decebal Constantin Mocanu, Elena
            Mocanu, Peter Stone, Phuong
            H. Nguyen, Madeleine Gibescu, and Antonio
            Liotta.
 Nature Communications, 9(2383), June 2018.
 Official version from Publisher's
            Webpage.
 Details
                  
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               (1.5MB
               )
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
 Tarun
            Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
            and Peter Stone.
 Transportation Research Part B: Methodological,
            110:104–21, 2018.
 Official version from Publisher's
            Webpage
 Details
                  
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               (1.6MB
               )
- Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?.
 Michael
            Albert, Vincent Conitzer, and Peter Stone.
 In Proceedings of the
            16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), May 2017.
 Details
                  
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               (348.6kB
               )
                [slides.pdf]
               (2.8MB
               )
- Automated Design of Robust Mechanisms.
 Michael Albert, Vincent
            Conitzer, and Peter Stone.
 In Proceedings of the Thirty-First AAAI Conference
            on Artificial Intelligence (AAAI-17), Feb 2017.
 Details
                  
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               (366.4kB
               )
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               (2.7MB
               )
- Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial.
 Stefano
            Albrecht, Somchaya Liemhetcharat, and Peter Stone.
 Autonomous Agents
            and Multi-Agent Systems, 31(4):765–66, July 2017.
 Official version from Publisher's
            Webpage
 Details
                  
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               (304.3kB
               )
- Reasoning about Hypothetical Agent Behaviours and their Parameters.
 Stefano Albrecht
            and Peter Stone.
 In Proceedings of the 16th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
 Available from IFAAMAS
            and from ACM
 Details
                  
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               (608.2kB
               )
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               (1.2MB
               )
- Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale
            Ad Hoc Teamwork Robotics Competition.
 Katie Genter, Tim
            Laue, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems
            (JAAMAS), 31(4):790–820, Springer, July 2017.
 Official version from Publisher's
            Webpage
 Details
                  
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               (1.2MB
               )
- CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression.
 Santiago Gonzalez,
            Vijay Chidambaram, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '17),
            July 2017.
 Details
                  
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               (241.6kB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            Hanna, Philip Thomas, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
 Details
                  
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               (1.2MB
               )
                [slides.pdf]
               (1.1MB
               )
- Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
 Josiah
            Hanna, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2017.
 Details
                  
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               (663.8kB
               )
                [ps]
               (572.6kB
               )
                [slides.pdf]
               (1.3MB
               )
- Grounded Action Transformation for Robot Learning in Simulation.
 Josiah
            Hanna and Peter Stone.
 In Proceedings of the 31st AAAI Conference
            on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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               (1.3MB
               )
                [slides.pdf]
               (1.3MB
               )
- Machine Learning Capabilities of a Simulated Cerebellum.
 Matthew Hausknecht,
            Wen-Ke Li, Michael Mauk, and Peter Stone.
 "IEEE
            Transactions on Neural Networks and Learning Systems", 28(3):510–22, March 2017.
 Details
                  
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               (1.1MB
               )
- Intrinsically motivated model learning for developing curious robots.
 Todd
            Hester and Peter Stone.
 Artificial Intelligence, 247:170–86,
            June 2017.
 from journal website.
 Details
                  
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               (1.4MB
               )
- BWIBots: A platform for bridging the gap between AI and human--robot interaction research.
 Piyush
            Khandelwal, Shiqi Zhang, Jivko
            Sinapov, Matteo Leonetti, Jesse Thomason,
            Fangkai Yang, Ilaria Gori, Maxwell Svetlik, Priyanka Khante, Vladimir
            Lifschitz, J. K. Aggarwal, Raymond Mooney, and Peter
            Stone.
 The International Journal of Robotics Research, 36(5--7):635–59, 2017.
 Accompanying videos
            at https://youtu.be/2UJG4-ejVww
 Details
                  
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            [pdf]
               (4.4MB
               )
- Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests.
 Piyush
            Khandelwal and Peter Stone.
 In International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2017.
 Details
                  
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               (1.8MB
               )
- An Assessment of Autonomous Vehicles:  Traffic Impacts and  Infrastructure Needs --- Final Report.
 Kara Kockelman,
            Stephen Boyles, Peter
            Stone, Dan Fagnant, Rahul  Patel, Michael W.
            Levin, Guni Sharon, Michele Simoni, Michael
             Albert, Hagen Fritz, Rebecca Hutchinson, Prateek Bansal, Gelb  Domnenko, Pavle Bujanovic, Bumsik Kim, Elaham Pourrahmani,
            Sudesh  Agrawal, Tianxin Li, Josiah Hanna, Aqshems Nichols, and Jia Li.
 Technical
            Report 0-6847-1, The University of Texas at Austin Center for Transportation Research, 2017.
 Available
            online
 Details
                  
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            Download: 
            
            (unavailable)
- Designing Better Playlists with Monte Carlo Tree Search.
 Elad Liebman,
            Piyush Khandelwal, Maytal
            Saar-Tsechansky, and Peter Stone.
 In Proceedings of the Twenty-Ninth
            Conference On Innovative Applications Of Artificial Intelligence (IAAI-17), February 2017.
 Details
                  
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               (377.0kB
               )
- Leveraging Commonsense Reasoning and Multimodal Perception for Robot    Spoken Dialog Systems.
 Dongcai Lu, Shiqi
            Zhang, Peter Stone, and Xiaoping
            Chen.
 In Proceedings of the IEEE/RSJ International Conference on    Intelligent Robots and Systems (IROS), September
            2017.
 Details
                  
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               (1.6MB
               )
- Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges.
 Patrick
            MacAlpine and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 168–86, Springer International Publishing, 2017.
 Details
                  
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               (518.7kB
               )
                [ps]
               (2.6MB
               )
                [slides.pdf]
               (45.5MB
               )
- UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions.
 Patrick
            MacAlpine and Peter Stone.
 In Sven Behnke, Daniel
            D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
            Intelligence, pp. 515–28, Springer, 2017.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2016
 Details
                  
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               (555.8kB
               )
                [ps]
               (14.4MB
               )
- Prioritized Role Assignment for Marking.
 Patrick MacAlpine and Peter Stone.
 In Sven Behnke, Daniel
            D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
            Intelligence, pp. 306–18, Springer Verlag, Berlin, 2017.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2016/html/marking.html
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               )
                [slides.pdf]
               (157.3MB
               )
- UT Austin Villa RoboCup 3D Simulation Base Code Release.
 Patrick MacAlpine
            and Peter Stone.
 In Sven Behnke, Daniel
            D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial
            Intelligence, pp. 135–43, Springer Verlag, Berlin, 2017.
 Code release at https://github.com/LARG/utaustinvilla3d
 Details
                  
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                [ps]
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               )
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               (107.1MB
               )
- Fast and Precise Black and White Ball Detection for RoboCup Soccer.
 Jacob
            Menashe, Josh Kelle, Katie Genter, Josiah
            Hanna, Elad Liebman, Sanmit
            Narvekar, Ruohan Zhang, and Peter
            Stone.
 In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
 Details
                  
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               (254.2kB
               )
                [ps]
               (716.1kB
               )
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               (1.5MB
               )
- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
 Sanmit
            Narvekar, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
            2017.
 Details
                  
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               (826.2kB
               )
                [slides.pdf]
               (5.8MB
               )
- Network-wide Adaptive Tolling for Connected and Automated vehicles.
 Guni
            Sharon, Michael W. Levin, Josiah
            P. Hanna, Tarun Rambha, Stephen
            D. Boyles, and Peter Stone.
 Transportation Research Part C, 84:142–157,
            September 2017.
 Transportation Research Part C.
 Audio slides.
 Contains material
            that was previously published in an AAMAS-17 paper.
 Details
                  
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               )
                [ps]
               (4.2MB
               )
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
 Guni
            Sharon and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
 Details
                  
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               (1.1MB
               )
                [ps]
               (7.1MB
               )
                [slides.pptx]
               (140.9MB
               )
- Automatic Curriculum Graph Generation for Reinforcement Learning Agents.
 Maxwell Svetlik, Matteo
            Leonetti, Jivko Sinapov, Rishi Shah, Nick
            Walker, and Peter Stone.
 In Proceedings of the 31st AAAI Conference
            on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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               (2.0MB
               )
- Multirobot Symbolic Planning under Temporal Uncertainty.
 Shiqi Zhang,
            Yuqian Jiang, Guni Sharon, and Peter
            Stone.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS),
            May 2017.
 Accompanying videos at https://youtu.be/ADbH3sppLHQ
 Details
                  
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               (2.3MB
               )
- Dynamically Constructed (PO)MDPs for Adaptive Robot Planning.
 Shiqi
            Zhang, Piyush Khandelwal, and Peter
            Stone.
 In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
 Details
                  
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               (3.2MB
               )
- Autonomous Intersection Management for Semi-Autonomous Vehicles.
 Tsz-Chiu
            Au, Shun Zhang, and Peter
            Stone.
 In Dusan Teodorovi'c, editors, Handbook of Transportation, pp. 88–104, Routledge, 2016.
 Details
                  
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               (2.6MB
               )
- Making Friends on the Fly: Cooperating with New Teammates.
 Samuel Barrett,
            Avi Rosenfeld, Sarit Kraus,
            and Peter Stone.
 Artificial Intelligence, October 2016.
 Official version from journal website.
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               (917.9kB
               )
- State Aggregation through Reasoning in Answer Set Programming.
 Ginevra Gaudioso, Matteo
            Leonetti, and Peter Stone.
 In Proceedings of the IJCAI Workshop on
            Autonomous Mobile Service Robots (WSR 16), July 2016.
 Details
                  
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               (776.6kB
               )
- Ad Hoc Teamwork Behaviors for Influencing a Flock.
 Katie Genter and
            Peter Stone.
 Acta Polytechnica, 56(1), 2016.
 Details
                  
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               (421.5kB
               )
                [ps]
               (1.6MB
               )
- Adding Influencing Agents to a Flock.
 Katie Genter and Peter
            Stone.
 In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-16),
            May 2016.
 Details
                  
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               (1.2MB
               )
                [ps]
               (4.5MB
               )
                [slides.pdf]
               (433.7kB
               )
- Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication.
 Jonathan Grizou, Samuel
            Barrett, Manuel Lopes, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
 Details
                  
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               (339.0kB
               )
- Minimum Cost Matching for Autonomous Carsharing.
 Josiah P. Hanna,
            Michael Albert, Donna
            Chen, and Peter Stone.
 In Proceedings of the 9th IFAC Symposium on
            Intelligent Autonomous Vehicles (IAV 2016), June 2016.
 Details
                  
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               (117.5kB
               )
                [ps]
               (355.2kB
               )
                [slides.pdf]
               (4.7MB
               )
- Deep Reinforcement Learning in Parameterized Action Space.
 Matthew Hausknecht
            and Peter Stone.
 In Proceedings of the International Conference on Learning
            Representations (ICLR), May 2016.
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               (468.3kB
               )
- Grounded Semantic Networks for Learning Shared Communication Protocols.
 Matthew
            Hausknecht and Peter Stone.
 In Deep Reinforcement Learning, NIPS
            Workshop, December 2016.
 Details
                  
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               (899.9kB
               )
- On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning.
 Matthew
            Hausknecht and Peter Stone.
 In Deep Reinforcement Learning: Frontiers
            and Challenges, IJCAI Workshop, July 2016.
 Details
                  
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               (2.5MB
               )
- Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork.
 Matthew
            Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan,
            and Peter Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop,
            May 2016.
 Details
                  
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               (253.9kB
               )
- Deep Imitation Learning for Parameterized Action Spaces.
 Matthew Hausknecht,
            Yilun Chen, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
 Details
                  
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               (483.4kB
               )
- Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines.
 Kazunori
            Iwata, Elad Liebman, Peter Stone,
            Toyoshiro Nakashima, Yoshiyuki Anan, and Naohiro Ishii.
 In Roger
            Lee, editors, Computer and Information Science 2015, Studies in Computational Intelligence, Springer Verlag, Berlin,
            2016.
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               (807.5kB
               )
- On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search.
 Piyush
            Khandelwal, Elad Liebman, Scott
            Niekum, and Peter Stone.
 In Proceedings of The 33rd International
            Conference on Machine Learning, pp. 1319–1328, June 2016.
 Details
                  
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               )
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               (1.7MB
               )
- Bringing Smart Transport to Texans:  Ensuring the Benefits of a	Connected and Autonomous Transport System in Texas ---
            Final Report.
 Kara Kockelman, Stephen Boyles, Paul
            Avery, Christian Claudel, Lisa	Loftus-Otway, Daniel Fagnant, Prateek Bansal, Michael
            Levin, Yong Zhao, Jun Liu, Lewis Clements, Wendy Wagner, Duncan Stewart, Guni
            Sharon, Michael Albert, Peter
            Stone, Josiah Hanna, Rahul Patel, Hagen Fritz, Tejas Choudhary, Tianxin
            Li, Aqshems Nichols, Kapil Sharma, and Michele Simoni.
 Technical Report 0-6838-2, The University of Texas at Austin Center
            for Transportation Research, 2016.
 Available online
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- A synthesis of automated planning and reinforcement learning for efficient, robust decision-making.
 Matteo
            Leonetti, Luca Iocchi, and Peter Stone.
 Artificial Intelligence,
            241:103 – 130, September 2016.
 Details
                  
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               (3.2MB
               )
- A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer.
 David
            L. Leottau, Javier Ruiz-del-Solar, Patrick
            MacAlpine, and Peter Stone.
 In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
            and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2016.
 Details
                  
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               (625.8kB
               )
- Impact of Music on Decision Making in Quantitative Tasks.
 Elad Liebman,
            Peter Stone, and Corey
            N. White.
 In 17th International Society for Music Information retrieval Conference (ISMIR), August 2016.
 Details
                  
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               (591.1kB
               )
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               (678.6kB
               )
- UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.
 Patrick
            MacAlpine, Josiah Hanna, Jason
            Liang, and Peter Stone.
 In Luis Almeida, Jianmin Ji, Gerald Steinbauer,
            and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2016.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2015
 Details
                  
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               )
                [ps]
               (7.2MB
               )
- Adaptation of Surrogate Tasks for Bipedal Walk Optimization.
 Patrick
            MacAlpine, Elad Liebman, and Peter
            Stone.
 In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.
 Details
                  
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               (172.1kB
               )
                [ps]
               (739.5kB
               )
                [slides.pdf]
               (165.0MB
               )
- Source Task Creation for Curriculum Learning.
 Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti,
            and Peter Stone.
 In Proceedings of the 15th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
 Details
                  
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               (630.0kB
               )
                [slides.pdf]
               (10.2MB
               )
- Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors.
 Jivko
            Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone.
 In Proceedings
            of the 25th International Joint Conference on Artificial  Intelligence (IJCAI), July 2016.
 Details
                  
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               (6.6MB
               )
                [slides.pdf]
               (5.2MB
               )
- Learning Multi-Modal Grounded Linguistic Semantics by Playing I Spy.
 Jesse Thomason,
            Jivko Sinapov, Maxwell Svetlik, Peter
            Stone, and Raymond Mooney.
 In Proceedings of the 25th international
            joint conference on Artificial Intelligence (IJCAI), July 2016.
 Demo Video
 Details
                  
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               (3.1MB
               )
                [slides.pdf]
               (1.0MB
               )
- An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis.
 Daniel
            Urieli and Peter Stone.
 In Proceedings of the 15th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
 Details
                  
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               (11.9MB
               )
- Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market.
 Daniel
            Urieli and Peter Stone.
 In Proceedings of the 30th Conference on
            Artificial Intelligence (AAAI 2016), February 2016.
 Details
                  
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               (1.2MB
               )
- Robot Scavenger Hunt: A Standardized Framework for Evaluating  Intelligent Mobile Robots.
 Shiqi
            Zhang, Dongcai Lu, Xiaoping Chen, and Peter
            Stone.
 In Proceedings of the International Joint Conference on Artificial  Intelligence (IJCAI), July 2016.
 Details
                  
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               (326.5kB
               )
- Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork.
 Samuel
            Barrett and Peter Stone.
 In Proceedings of the Twenty-Ninth AAAI
            Conference on Artificial Intelligence, January 2015.
 Details
                  
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               (993.2kB
               )
                [ps]
               (2.8MB
               )
- Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League.
 Mike Depinet, Patrick MacAlpine,
            and Peter Stone.
 In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian
            Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot Soccer World Cup XVIII, Lecture Notes in Artificial
            Intelligence, Springer Verlag, Berlin, 2015.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/learningFromObservation.html
 Details
                  
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               (905.3kB
               )
                [ps]
               (42.3MB
               )
- When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing.
 Fei
            Fang, Peter Stone, and Milind
            Tambe.
 In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
 Winner of Computational Sustainability Track Outstanding Paper Award at IJCAI 2015
 Details
                  
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               (456.7kB
               )
                [ps]
               (983.9kB
               )
                [slides.pptx]
               (6.2MB
               )
- Determining Placements of Influencing Agents in a Flock.
 Katie Genter,
            Shun Zhang, and Peter Stone.
 In
            Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
 Details
                  
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            Download: 
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               (426.7kB
               )
                [ps]
               (1.4MB
               )
                [slides.pdf]
               (1.6MB
               )
- The Impact of Determinism on Learning Atari 2600 Games.
 Matthew Hausknecht
            and Peter Stone.
 In AAAI Workshop on Learning for General Competency
            in Video Games, January 2015.
 Details
                  
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               (65.1kB
               )
- Deep Recurrent Q-Learning for Partially Observable MDPs.
 Matthew Hausknecht
            and Peter Stone.
 In AAAI Fall Symposium on Sequential Decision Making
            for Intelligent Agents (AAAI-SDMIA15), November 2015.
 Details
                  
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            Download: 
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               (1.5MB
               )
                [slides.pdf]
               (3.8MB
               )
- Leading the Way: An Efficient Multi-robot Guidance System.
 Piyush Khandelwal,
            Samuel Barrett, and Peter Stone.
 In
            International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
 Accompanying videos at
            https://www.youtube.com/watch?v=os1BjHgM5ao&feature=youtu.be
 Details
                  
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               (694.2kB
               )
- Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance.
 W. Bradley Knox and Peter Stone.
 Artificial
            Intelligence, 225(), August 2015.
 Artificial
            Intelligence
 Contains material that was previously published in a IUI 2013 paper and a RoMan 2012 paper that was nominated as a CoTeSys Cognitive Robotics BEST PAPER AWARD FINALIST.
 Details
                  
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               (3.9MB
               )
- Representative Selection in Nonmetric Datasets.
 Elad Liebman, Benny Chor, and Peter Stone.
 "Applied
            Artificial Intelligence", 29:807–838, 2015.
 Details
                  
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               (846.3kB
               )
- How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification.
 Elad
            Liebman, Peter Stone, and Corey
            N. White.
 In 16th International Society for Music Information retrieval Conference (ISMIR), October 2015.
 Details
                  
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            [pdf]
               (832.6kB
               )
                [ps]
               (6.3MB
               )
                [slides.pdf]
               (2.0MB
               )
- DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone.
 In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2015.
 Details
                  
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               (1.5MB
               )
                [ps]
               (38.4MB
               )
                [slides.pdf]
               (2.6MB
               )
- UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions.
 Patrick
            MacAlpine, Mike Depinet, Jason
            Liang, and Peter Stone.
 In Reinaldo A. C. Bianchi, H. Levent Akin, Subramanian Ramamoorthy, and Komei Sugiura, editors, RoboCup-2014: Robot
            Soccer World Cup XVIII, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2015.
 Accompanying videos
            at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2014
 Details
                  
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               (235.7kB
               )
                [ps]
               (1.9MB
               )
- UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning.
 Patrick
            MacAlpine, Mike Depinet, and Peter
            Stone.
 In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pp. 2842–48,
            January 2015.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2014/html/overlappingLayeredLearning.html
 Details
                  
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               (714.7kB
               )
                [ps]
               (2.5MB
               )
                [slides.pdf]
               (105.3MB
               )
- SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning.
 Patrick
            MacAlpine, Eric Price, and Peter
            Stone.
 In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/scram.html
 Details
                  
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               (260.3kB
               )
                [ps]
               (676.5kB
               )
                [slides.pdf]
               (40.3MB
               )
- Monte Carlo Hierarchical Model Learning.
 Jacob Menashe and Peter Stone.
 In Proceedings of the 14th International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2015.
 Details
                  
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            Download: 
            [pdf]
               (693.2kB
               )
                [ps]
               (18.4MB
               )
- Learning Inter-Task Transferability in the Absence of Target  Task Samples.
 Jivko
            Sinapov, Sanmit Narvekar, Matteo
            Leonetti, and Peter Stone.
 In Proceedings of the International Conference
            on Autonomous  Agents and Multiagent Systems (AAMAS), 2015.
 Details
                  
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            [pdf]
               (337.2kB
               )
- Learning to Interpret Natural Language Commands through Human-Robot    Dialog.
 Jesse
            Thomason, Shiqi Zhang, Raymond
            Mooney, and Peter Stone.
 In Proceedings of the 2015 International
            Joint Conference on    Artificial Intelligence (IJCAI), July 2015.
 Demo
 Details
                  
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               (1.4MB
               )
                [slides.pdf]
               (1.1MB
               )
- Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy.
 Shiqi
            Zhang, Fangkai Yang, Piyush
            Khandelwal, and Peter Stone.
 In Proceedings of the 13th International
            Conference on Logic     Programming and Non-monotonic Reasoning (LPNMR), September 2015.
 Demo Video
 Details
                  
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               (2.6MB
               )
                [slides.pdf]
               (1.3MB
               )
- CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied      to Dialog with a Mobile Robot.
 Shiqi
            Zhang and Peter Stone.
 In Proceedings of the 29th Conference on Artificial
            Intelligence (AAAI), January 2015.
 Details
                  
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            Download: 
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               (306.0kB
               )
                [ps]
               (1.5MB
               )
- Modeling Uncertainty in Leading Ad Hoc Teams.
 Noa Agmon, Samuel
            Barrett, and Peter Stone.
 In Proc. of 13th Int. Conf. on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2014.
 Details
                  
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            Download: 
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               (255.6kB
               )
                [ps]
               (1.7MB
               )
- Communicating with Unknown Teammates.
 Samuel Barrett, Noa
            Agmon, Noam Hazon, Sarit Kraus,
            and Peter Stone.
 In Proceedings of the Twenty-First European Conference
            on Artificial Intelligence, August 2014.
 Details
                  
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            Download: 
            [pdf]
               (215.9kB
               )
                [ps]
               (2.6MB
               )
                [slides.pdf]
               (1.4MB
               )
- Influencing a Flock via Ad Hoc Teamwork.
 Katie Genter and Peter
            Stone.
 In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
 Details
                  
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               (358.4kB
               )
                [ps]
               (1.4MB
               )
                [slides.pdf]
               (15.3MB
               )
- A Neuroevolution Approach to General Atari Game Playing.
 Matthew Hausknecht,
            Joel Lehman, Risto Miikkulainen, and Peter Stone.
 IEEE Transactions on Computational Intelligence and AI in Games,
            2014.
 Details
                  
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               (1.3MB
               )
                [ps]
               (3.1MB
               )
- Planning in Action Language $\cal BC$ while Learning Action Costs    for Mobile Robots.
 Piyush
            Khandelwal, Fangkai Yang, Matteo
            Leonetti, Vladimir    Lifschitz, and Peter
            Stone.
 In International Conference on Automated Planning and Scheduling    (ICAPS), June 2014.
 Details
                  
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               (2.5MB
               )
                [ps]
               (6.0MB
               )
- Multi-robot Human Guidance using Topological Graphs.
 Piyush Khandelwal
            and Peter Stone.
 In AAAI Spring 2014 Symposium on Qualitative Representations
            for Robots (AAAI-SSS), March 2014.
 Details
                  
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               (1.1MB
               )
                [ps]
               (7.6MB
               )
- The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork.
 Patrick
            MacAlpine, Katie Genter, Samuel
            Barrett, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS), September 2014.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2013/html/dropin.html
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               )
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               (30.4MB
               )
- TacTex'13: A Champion Adaptive Power Trading Agent.
 Daniel Urieli
            and Peter Stone.
 In Proceedings of the Twenty-Eighth Conference on Artificial
            Intelligence (AAAI 2014), July 2014.
 Details
                  
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               (257.8kB
               )
                [ps]
               (7.3MB
               )
                [slides.pdf]
               (3.8MB
               )
- Planning in Answer Set Programming while Learning Action Costs for    Mobile Robots.
 Fangkai
            Yang, Piyush Khandelwal, Matteo
            Leonetti, and Peter Stone.
 In AAAI Spring 2014 Symposium on Knowledge
            Representation and Reasoning in Robotics (AAAI-SSS), March 2014.
 Details
                  
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               (5.3MB
               )
- The 2012 UT Austin Villa Code Release.
 Samuel Barrett, Katie
            Genter, Yuchen He, Todd
            Hester, Piyush Khandelwal, Jacob
            Menashe, and Peter Stone.
 In RoboCup-2013: Robot Soccer World Cup
            XVII, Springer Verlag, 2013.
 Details
                  
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               (2.1MB
               )
- UT Austin Villa 2012: Standard Platform League World Champions.
 Samuel
            Barrett, Katie Genter, Yuchen
            He, Todd Hester, Piyush Khandelwal,
            Jacob Menashe, and Peter Stone.
 In
            Xiaoping Chen, Peter
            Stone, Luis Enrique Sucar, and Tijn
            Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2013.
 Details
                  
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               (740.4kB
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                [ps]
               (15.0MB
               )
- Teamwork with Limited Knowledge of Teammates.
 Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld.
 In Proceedings of the Twenty-Seventh AAAI Conference on
            Artificial Intelligence, July 2013.
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               (190.1kB
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               (2.0MB
               )
- Auction-based autonomous intersection management.
 Dustin Carlino,
            Stephen D. Boyles, and Peter
            Stone.
 In Proceedings of the 16th IEEE Intelligent Transportation Systems Conference (ITSC), October 2013.
 Details
                  
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               (318.1kB
               )
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               (1.4MB
               )
- Multiagent Learning in the Presence of Memory-Bounded Agents.
 Doran
            Chakraborty and Peter Stone.
 Autonomous Agents and Multiagent Systems
            (JAAMAS), Springer, 2013.
 Details
                  
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               (676.7kB
               )
                [ps]
               (447.9kB
               )
- Cooperating with a Markovian Ad Hoc Teammate.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the 12th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
 Details
                  
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                [ps]
               (408.2kB
               )
- Targeted Opponent Modeling of Memory-Bounded Agents.
 Doran
            Chakraborty, Noa Agmon, and Peter
            Stone.
 In Proceedings of the Adaptive Learning Agents Workshop (ALA), May 2013.
 Details
                  
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               )
- Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back.
 Alon
            Farchy, Samuel Barrett, Patrick
            MacAlpine, and Peter Stone.
 In Proc. of 12th Int. Conf. on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2013.
 The videos referenced in the paper: original
            and optimized.
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               (36.5MB
               )
- Role-Based Ad Hoc Teamwork.
 Katie Genter, Noa
            Agmon, and Peter Stone.
 In Gita Sukthankar, Robert P. Goldman, Christopher
            Geib, David V. Pyhadath, and Hung Hai Bui, editors, Plan, Activity, and Intent Recognition: Theory and Practice, pp.
            251–272, Elsevier, Philadelphia, PA, USA, 2013.
 Details
                  
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               )
- Ad Hoc Teamwork for Leading a Flock.
 Katie Genter, Noa
            Agmon, and Peter Stone.
 In Proceedings of the 12th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), May 2013.
 Details
                  
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               )
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               (28.3MB
               )
- Improving Efficiency of Leading a Flock in Ad Hoc Teamwork Settings.
 Katie
            Genter, Noa Agmon, and Peter Stone.
 In
            AAMAS Autonomous Robots and Multirobot Systems (ARMS) Workshop, May 2013.
 Details
                  
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               (413.8kB
               )
                [slides.pdf]
               (13.0MB
               )
- TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots.
 Todd
            Hester and Peter Stone.
 Machine Learning, 90(3):385–429,
            2013.
 Official version
            from journal website.
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               (987.8kB
               )
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               (3.2MB
               )
- The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots.
 Todd
            Hester and Peter Stone.
 In Sven Behnke, Arnoud Visser, Rong Xiong, and
            Manuela Veloso, editors, RoboCup-2013: Robot Soccer World Cup XVII, Lecture
            Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
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                [ps]
               (2.9MB
               )
- Learning Exploration Strategies in Model-Based Reinforcement Learning.
 Todd
            Hester, Manuel Lopes, and Peter
            Stone.
 In The Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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               )
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               (2.4MB
               )
- Training a Robot via Human Feedback: A Case Study.
 W. Bradley Knox, Peter
            Stone, and Cynthia Breazeal.
 In International Conference on
            Social Robotics, October 2013.
 BEST PAPER AWARD WINNER at ICSR 2013
 An
            associated video summarizing the paper (direct
            link).
 Details
                  
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               )
- UT Austin Villa: RoboCup 2012 3D Simulation League Champion.
 Patrick
            MacAlpine, Nick Collins, Adrian
            Lopez-Mobilia, and Peter Stone.
 In Xiaoping
            Chen, Peter Stone, Luis Enrique
            Sucar, and Tijn Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup
            XVI, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
 Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/results_3d/#highlights
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               )
- Positioning to Win: A Dynamic Role Assignment and FormationPositioning System.
 Patrick
            MacAlpine, Francisco Barrera, and Peter
            Stone.
 In Xiaoping Chen, Peter
            Stone, Luis Enrique Sucar, and Tijn
            Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2013.
 Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/positioning.html
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               )
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               (44.0MB
               )
- Simultaneous Learning and Reshaping of an Approximated Optimization Task.
 Patrick
            MacAlpine, Elad Liebman, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
 Details
                  
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               (435.1kB
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                [ps]
               (2.1MB
               )
                [slides.pdf]
               (35.2MB
               )
- UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy.
 Jacob
            Menashe, Katie Genter, Samuel
            Barrett, and Peter Stone.
 In The Eighth Workshop on Humanoid Soccer
            Robots at Humanoids 2013, October 2013.
 Details
                  
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               )
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               (3.1MB
               )
- Teaching and leading an ad hoc teammate: Collaboration without pre-coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, Jeffrey S. Rosenschein, and Noa
            Agmon.
 Artificial Intelligence, 203:35–65, Elsevier, October 2013.
 Official
            version from journal website.
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               )
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               (734.2kB
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- Model-Selection for Non-Parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy
            System.
 Daniel Urieli and Peter
            Stone.
 In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML'13),
            Sep 2013.
 Official publisher version
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               (2.3MB
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               (1.4MB
               )
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               (3.6MB
               )
- A Learning Agent for Heat-Pump Thermostat Control.
 Daniel Urieli
            and Peter Stone.
 In Proceedings of the 12th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
 Details
                  
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               (426.6kB
               )
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               (4.6MB
               )
- Leading Ad Hoc Agents in Joint Action Settings with Multiple Teammates.
 Noa
            Agmon and Peter Stone.
 In Proc. of 11th Int. Conf. on Autonomous
            Agents and Multiagent Systems (AAMAS), June 2012.
 Details
                  
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               )
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               (757.7kB
               )
- On Coordination in Practical Multi-Robot Patrol.
 Noa Agmon, Chien-Liang
            Fok, Yehuda Emaliah, Peter
            Stone, Christine Julien, and Sriram
            Vishwanath.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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               )
- Setpoint Scheduling for Autonomous Vehicle Controllers.
 Tsz-Chiu Au,
            Michael Quinlan, and Peter
            Stone.
 In Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 2012.
 Details
                  
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               )
- Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions.
 Aijun
            Bai, Xiaoping Chen, Patrick
            MacAlpine, Daniel Urieli, Samuel
            Barrett, and Peter Stone.
 In Thomas Roefer, Norbert Michael Mayer, Jesus
            Savage, and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence,
            Springer Verlag, Berlin, 2012.
 Details
                  
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- An Analysis Framework for Ad Hoc Teamwork Tasks.
 Samuel Barrett
            and Peter Stone.
 In Proceedings of the 11th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
 Details
                  
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               (177.6kB
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               )
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               )
- Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing.
 Samuel
            Barrett, Katie Genter, Todd Hester,
            Piyush Khandelwal, Michael
            Quinlan, Peter Stone, and Mohan
            Sridharan.
 Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI
            Laboratory, 2012.
 Details
                  
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               (1.1MB
               )
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               )
- Approximately Orchestrated Routing and Transportation Analyzer: Large-scale Traffic Simulation for Autonomous Vehicles.
 Dustin Carlino, Mike
            Depinet, Piyush Khandelwal, and Peter
            Stone.
 In Proceedings of the 15th IEEE Intelligent Transportation Systems Conference (ITSC), September 2012.
 Details
                  
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               (727.1kB
               )
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               (14.3MB
               )
- RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control.
 Todd
            Hester, Michael Quinlan, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
 Details
                  
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               (359.7kB
               )
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               (1.9MB
               )
- PAC Subset Selection in Stochastic Multi-armed Bandits.
 Shivaram
            Kalyanakrishnan, Ambuj Tewari, Peter
            Auer, and Peter Stone.
 In Proceedings of the 29th International Conference
            on Machine Learning (ICML), pp. 655–662, Omnipress, New York, NY, USA, June-July 2012.
 Details
                  
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               )
- A Low Cost Ground Truth Detection System Using the Kinect.
 Piyush Khandelwal
            and Peter Stone.
 In Thomas Roefer, Norbert Michael Mayer, Jesus Savage,
            and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2012.
 Details
                  
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               )
- How Humans Teach Agents: A New Experimental Perspective.
 W. Bradley Knox,
            Brian D. Glass, Bradley
            C. Love, W. Todd Maddox, and Peter
            Stone.
 International Journal of Social Robotics, 4:409–421, Springer Netherlands, October 2012. 10.1007/s12369-012-0163-x
 International Journal of Social Robotics
 Download article from publisher
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- The Nature of Belief-Directed Exploratory Choice in Human Decision-Making.
 W.
            Bradley Knox, A. Ross Otto, Peter
            Stone, and Bradley Love.
 Frontiers in Psychology, 2(398), January 2012.
 Frontiers in Psychology
 Download
            article from publisher (free)
 A follow-up
            commentary by Erica Yu.
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            (unavailable)
- Reinforcement Learning from Simultaneous Human and MDP Reward.
 W. Bradley Knox
            and Peter Stone.
 In Proceedings of the 11th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
 AAMAS 2012
 Details
                  
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               )
- Learning from feedback on actions past and intended.
 W. Bradley Knox,
            Cynthia Breazeal, and Peter
            Stone.
 In Proceedings of 7th ACM/IEEE International Conference on Human-Robot Interaction, Late-Breaking Reports
            Session (HRI), March 2012.
 HRI 2012
 Details
                  
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               )
- Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition.
 Patrick MacAlpine, Samuel Barrett,
            Daniel Urieli, Victor
            Vu, and Peter Stone.
 In Proceedings of the Twenty-Sixth AAAI Conference
            on Artificial Intelligence (AAAI), July 2012.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html
 Details
                  
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               )
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               (2.0MB
               )
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               (204.2MB
               )
- UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition.
 Patrick
            MacAlpine, Daniel Urieli, Samuel
            Barrett, Shivaram Kalyanakrishnan, Francisco
            Barrera, Adrian Lopez-Mobilia, Nicolae \cStiurc\ua,
            Victor Vu, and Peter
            Stone.
 In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
 Accompanying
            videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/components.html
 Details
                  
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               )
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               (2.7MB
               )
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               (135.4MB
               )
- Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk.
 Patrick
            MacAlpine and Peter Stone.
 In AAMAS Adaptive Learning Agents (ALA)
            Workshop, June 2012.
 Video available at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/holonomicwalk.html
 Details
                  
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               (525.6kB
               )
                [ps]
               (2.2MB
               )
                [slides.pdf]
               (159.5MB
               )
- Multiagent Patrol Generalized to Complex Environmental Conditions.
 Noa Agmon,
            Daniel Urieli, and Peter Stone.
 In
            Proceedings of the Twenty-Fifth Conference on ArtificialIntelligence (AAAI), August 2011.
 Extended
            version, book
            chapter
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               )
                [ps]
               (1.9MB
               )
- Enforcing Liveness in Autonomous Traffic Management.
 Tsz-Chiu Au, Neda Shahidi, and Peter
            Stone.
 In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
 Details
                  
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               (1.1MB
               )
                [ps]
               (31.7MB
               )
- Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain.
 Samuel
            Barrett, Peter Stone, and Sarit
            Kraus.
 In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
 Details
                  
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               (361.8kB
               )
                [ps]
               (11.4MB
               )
                [slides.pdf]
               (616.4kB
               )
- Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards.
 Samuel
            Barrett and Peter Stone.
 In Tenth International Conference on Autonomous
            Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
 Details
                  
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               (136.1kB
               )
                [ps]
               (384.8kB
               )
- Austin Villa 2010 Standard Platform Team Report.
 Samuel Barrett,
            Katie Genter, Matthew Hausknecht,
            Todd Hester, Piyush Khandelwal,
            Juhyun Lee, Michael
            Quinlan, Aibo Tian, Peter Stone,
            and Mohan Sridharan.
 Technical Report UT-AI-TR-11-01, The University of Texas
            at Austin, Department of Computer Sciences, AI Laboratory, 2011.
 Details
                  
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               (1.3MB
               )
                [ps]
               (38.0MB
               )
- Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the Twenty Eighth
            International Conference on Machine Learning (ICML), 2011.
 Details
                  
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               (223.3kB
               )
                [ps]
               (521.1kB
               )
- Dynamic Lane Reversal in Traffic Management.
 Matthew Hausknecht,
            Tsz-Chiu Au, Peter Stone, David
            Fajardo, and Travis Waller.
 In Proceedings of IEEE Intelligent Transportation
            Systems Conference (ITSC), 2011.
 Details
                  
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               (127.0kB
               )
                [ps]
               (4.3MB
               )
- Autonomous Intersection Management: Multi-Intersection Optimization.
 Matthew
            Hausknecht, Tsz-Chiu Au, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2011.
 Details
                  
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               (252.7kB
               )
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               (1.9MB
               )
- Learning and Using Models.
 Todd Hester and Peter
            Stone.
 In Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Springer
            Verlag, Berlin, Germany, 2011.
 Details
                  
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               (474.7kB
               )
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               )
- Characterizing Reinforcement Learning Methods through Parameterized Learning Problems.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 Machine Learning (MLJ), 84(1--2):205–247,
            July 2011.
 Publisher's
            on-line version
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               (858.5kB
               )
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               (2.4MB
               )
- On Learning with Imperfect Representations.
 Shivaram Kalyanakrishnan
            and Peter Stone.
 In Proceedings of the 2011 IEEE Symposium on Adaptive
            Dynamic Programming and Reinforcement Learning, pp. 17–24, IEEE, April 2011.
 Details
                  
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               (163.8kB
               )
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               (196.0kB
               )
- Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report.
 W. Bradley
            Knox and Peter Stone.
 In IJCAI 2011 Workshop on Agents Learning Interactively
            from Human Teachers (ALIHT), July 2011.
 IJCAI 2011 Workshop
            on Agents Learning Interactively  from Human Teachers (ALIHT)
 Details
                  
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               )
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               (41.6MB
               )
- Comparing Agents: Success against People in Security Domains.
 Raz Lin,
            Sarit Kraus, Noa Agmon, Samuel
            Barrett, and Peter Stone.
 In Proceedings of the Twenty-Fifth AAAI
            Conference on Artificial Intelligence, August 2011.
 Details
                  
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               (387.5kB
               )
- UT Austin Villa 2011 3D Simulation Team Report.
 Patrick MacAlpine,
            Daniel Urieli, Samuel Barrett,
            Shivaram Kalyanakrishnan, Francisco
            Barrera, Adrian Lopez-Mobilia, Nicolae\cStiurc\ua,
            Victor Vu, and Peter
            Stone.
 Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
            2011.
 Details
                  
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               (1.2MB
               )
                [ps]
               (5.3MB
               )
- A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations.
 David
            Pardoe and Peter Stone.
 In Proceedings of the 10th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
 Details
                  
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               (313.6kB
               )
                [ps]
               (280.8kB
               )
- An Introduction to Inter-task Transfer for Reinforcement Learning.
 Matthew
            E. Taylor and Peter Stone.
 AI Magazine, 32(1):15–34,
            2011.
 Details
                  
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               )
                [ps]
               (773.0kB
               )
- On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer.
 Daniel
            Urieli, Patrick MacAlpine, Shivaram
            Kalyanakrishnan, Yinon Bentor, and Peter
            Stone.
 In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), pp. 769–776, IFAAMAS,
            May 2011.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2010/html/skilloptimization2010.html
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               )
                [slides.pptx]
               (3.8MB
               )
- Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning.
 Shimon
            Whiteson, Brian Tanner, Matthew
            E. Taylor, and Peter Stone.
 In IEEE Symposium on Adaptive Dynamic
            Programming and Reinforcement Learning (ADPRL), April 2011.
 2011
            IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL)
 Details
                  
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               (165.3kB
               )
- Controlled Kicking under Uncertainty.
 Samuel Barrett, Katie
            Genter, Todd Hester, Michael
            Quinlan, and Peter Stone.
 In The Fifth Workshop on Humanoid Soccer
            Robots at Humanoids 2010, December 2010.
 Details
                  
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               (357.3kB
               )
                [ps]
               (17.7MB
               )
- Transfer Learning for Reinforcement Learning on a Physical Robot.
 Samuel
            Barrett, Matt E. Taylor, and Peter
            Stone.
 In Ninth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents
            Workshop (AAMAS - ALA), May 2010.
 AAMAS ALA 2010
 Details
                  
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               (688.8kB
               )
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               )
- Convergence, Targeted Optimality and Safety in Multiagent Learning.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the Twenty-seventh
            International Conference on Machine Learning (ICML), June 2010.
 Details
                  
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               (196.9kB
               )
                [ps]
               (474.1kB
               )
- Real Time Targeted Exploration in Large Domains.
 Todd Hester and Peter Stone.
 In The Ninth International Conference on Development and Learning
            (ICDL), August 2010.
 ICDL 2010
 Details
                  
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               (253.9kB
               )
                [ps]
               (554.1kB
               )
- Generalized Model Learning for Reinforcement Learning on a Humanoid Robot.
 Todd
            Hester, Michael Quinlan, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2010.
 Video available at
            http://www.cs.utexas.edu/~AustinVilla/?p=research/rl_kick
 Details
                  
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               (1.5MB
               )
                [ps]
               (25.3MB
               )
- Efficient Selection of Multiple Bandit Arms: Theory and Practice.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 In Proceedings of the Twenty-seventh
            International Conference on Machine Learning (ICML), 2010.
 Details
                  
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               (257.1kB
               )
                [ps]
               (679.3kB
               )
- Vision Calibration and Processing on a Humanoid Soccer Robot.
 Piyush
            Khandelwal, Matthew Hausknecht, Juhyun
            Lee, Aibo Tian, and Peter Stone.
 In
            The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
 Details
                  
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               (402.6kB
               )
                [ps]
               (14.8MB
               )
- Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning.
 W. Bradley
            Knox and Peter Stone.
 In Proc. of 9th Int. Conf. on Autonomous Agents
            and Multiagent Systems (AAMAS 2010), May 2010.
 Winner of the Pragnesh Jay Modi BEST STUDENT PAPER AWARD (and
            best paper award nominee).
 The TAMER project page with videos
            of TAMER in action.
 AAMAS-2010
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               )
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               (3.5MB
               )
- Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge.
 David
            Pardoe, Peter Stone, Maytal
            Saar-Tsechansky, Tayfun Keskin, and Kerem Tomak.
 Informs Journal
            on Computing, 22(3):353–370, 2010.
 Details
                  
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               (530.9kB
               )
                [ps]
               (9.2MB
               )
- Boosting for Regression Transfer.
 David Pardoe and Peter
            Stone.
 In Proceedings of the 27th International Conference on Machine Learning (ICML), June 2010.
 Some
            of the data used in the experiments.
 Details
                  
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               (600.5kB
               )
                [ps]
               (1.7MB
               )
- TacTex09: A Champion Bidding Agent for Ad Auctions.
 David Pardoe,
            Doran Chakraborty, and Peter
            Stone.
 In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010),
            May 2010.
 Details
                  
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               (564.3kB
               )
                [ps]
               (1.0MB
               )
- Bringing Simulation to Life: A Mixed Reality Autonomous Intersection.
 Michael
            Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
            2010.
 Video available at http://www.cs.utexas.edu/~aim/video/MixedReality.wmv
 Details
                  
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               (1.3MB
               )
                [ps]
               (10.6MB
               )
- MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training.
 Adam
            Setapen, Michael Quinlan, and Peter
            Stone.
 In Ninth International Conference on Autonomous Agents and Multiagent Systems - Agents Learning Interactively
            from Human Teachers Workshop (AAMAS - ALIHT), May 2010.
 supplemental
            video cited in the paper.
 Details
                  
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               (533.2kB
               )
                [ps]
               (9.7MB
               )
- The Essence of Soccer, Can Robots Play Too?.
 Peter Stone, Michael
            Quinlan, and Todd Hester.
 In Ted Richards, editors, Soccer and Philosophy:
             Beautiful Thoughts on theBeautiful Game, Popular Culture and Philosophy, pp. 75–88, Open Court Publishing Company,
            2010.
 Appears in Soccer and Philosophy (available from amazon.com)
 Details
                  
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               (121.3kB
               )
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               (514.1kB
               )
- Ad Hoc Autonomous Agent Teams:  Collaboration without Pre-Coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, and Jeffrey S. Rosenschein .
 In Proceedings of the Twenty-Fourth
            Conference on Artificial Intelligence, July 2010.
 AAAI
            2010
 Details
                  
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               (119.0kB
               )
                [ps]
               (266.6kB
               )
                [slides.pdf]
               (8.1MB
               )
- To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams.
 Peter
            Stone and Sarit Kraus.
 In The Ninth International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), International Foundation for Autonomous Agents and Multiagent Systems, May 2010.
 supplemental material cited in the paper,
            including a proof and an algorithm.
 AAMAS 2010
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                [ps]
               (285.3kB
               )
- Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning.
 Shimon Whiteson, Matthew
            E. Taylor, and Peter Stone.
 Journal of Autonomous Agents and
            Multi-Agent Systems, 21(1):1–27, 2010.
 Details
                  
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               (760.6kB
               )
                [ps]
               (1.9MB
               )
- TT-UT Austin Villa 2009: Naos across Texas.
 Todd Hester, Michael
            Quinlan, Peter Stone, and Mohan
            Sridharan.
 Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
            2009.
 Details
                  
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               (787.9kB
               )
                [ps]
               (7.0MB
               )
- Connectivity-based Localization in Robot Networks.
 Tobias Jung,
            Mazda Ahmadi, and Peter
            Stone.
 In International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09), June 2009.
 Details
                  
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               (176.8kB
               )
                [ps]
               (514.7kB
               )
- Color Learning and Illumination Invariance on Mobile Robots: A Survey.
 Mohan
            Sridharan and Peter Stone.
 Robotics and Autonomous Systems (RAS)
            Journal, 57(60-7):629–44, June 2009.
 Details
                  
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               (1.3MB
               )
                [ps]
               (6.0MB
               )
- Instance-Based Action Models for Fast Action Planning.
 Mazda
            Ahmadi and Peter Stone.
 In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi,
            and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence, pp.
            1–16, Springer Verlag, Berlin, 2008.
 BEST PAPER AWARD WINNER at RoboCup International Symposium.
 Official
            version from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (466.3kB
               )
                [ps]
               (3.0MB
               )
- Multiagent Interactions in Urban Driving.
 Patrick Beeson, Jack
            O'Quin, Bartley Gillan, Tarun Nimmagadda, Mickey Ristroph, David Li, and Peter
            Stone.
 Journal of Physical Agents, 2(1):15–30, March 2008. Special issue on Multi-Robot Systems
 JoPhA
 Details
                  
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               (2.1MB
               )
                [ps]
               (6.6MB
               )
- A Neural Network-Based Approach to Robot Motion Control.
 Uli Grasemann, Daniel
            Stronger, and Peter Stone.
 In Ubbo Visser, Fernando Ribeiro, Takeshi
            Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence,
            pp. 480–87, Springer Verlag, Berlin, 2008.
 Details
                  
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               (280.9kB
               )
                [ps]
               (1.6MB
               )
- Negative Information and Line Observations for Monte Carlo Localization.
 Todd
            Hester and Peter Stone.
 In IEEE International Conference on Robotics
            and Automation, May 2008.
 ICRA 2008
 Details
                  
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               (128.7kB
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                [ps]
               (501.7kB
               )
- Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting.
 Juhyun
            Lee, W. Bradley Knox, and Peter
            Stone.
 Journal of Physical Agents, 2(2):41–50, July 2008. Special Issue on Human Interaction with Domestic
            Robots
 Available from journal's web page.
 Details
                  
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               (2.4MB
               )
                [ps]
               (3.4MB
               )
- Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents.
 Daniel
            Stronger and Peter Stone.
 International Journal on Artificial Intelligence
            Tools, 17(1):159–174, February 2008.
 official
            published version
 Details
                  
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               (236.4kB
               )
                [ps]
               (1.0MB
               )
- Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot.
 Daniel
            Stronger and Peter Stone.
 In IEEE International Conference on Robotics
            and Automation, May 2008.
 ICRA 2008
 Details
                  
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               (182.1kB
               )
                [ps]
               (902.7kB
               )
- IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks.
 Mazda
            Ahmadi, Matthew E. Taylor, and Peter
            Stone.
 In The Sixth International Joint Conference on Autonomous Agents and  Multiagent Systems, May 2007.
 BEST PAPER AWARD NOMINEE.
 AAMAS-2007
 Details
                  
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               )
                [ps]
               (1.0MB
               )
- The Chin Pinch:  A Case Study in Skill Learning on a Legged Robot.
 Peggy
            Fidelman and Peter Stone.
 In Gerhard Lakemeyer, Elizabeth
            Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
            in Artificial Intelligence, pp. 59–71, Springer Verlag, Berlin, 2007.
 Some videos
            referenced in the paper.
 Details
                  
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               )
                [ps]
               (1.6MB
               )
- Autonomous Learning of Stable Quadruped Locomotion.
 Manish
            Saggar, Thomas D'Silva, Nate Kohl, and Peter
            Stone.
 In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
            Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
            98–109, Springer Verlag, Berlin, 2007.
 BEST PAPER AWARD NOMINEE at RoboCup International Symposium.
 Some videos referenced in the paper.
 Details
                  
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               (1.1MB
               )
                [ps]
               (26.8MB
               )
- Structure Based Color Learning on a Mobile Robot under Changing Illumination.
 Mohan
            Sridharan and Peter Stone.
 Autonomous Robots, 23(3):161–182,
            2007.
 Official versionfrom
            the Autonomous Robots publisher's webpage.
 Details
                  
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               (2.0MB
               )
                [ps]
               (8.6MB
               )
- Planning Actions to Enable Color Learning on a Mobile Robot.
 Mohan Sridharan
            and Peter Stone.
 International Journal of Information and Systems Sciences,
            3(3):510–25, 2007.
 official
            published version
 Details
                  
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- Action Selection for Illumination Invariant Color Learning.
 Mohan Sridharan
            and Peter Stone.
 In The IEEE International Conference on Intelligent
            Robots and Systems (IROS), 2007.
 Details
                  
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               (176.5kB
               )
                [ps]
               (490.5kB
               )
- Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination.
 Mohan
            Sridharan and Peter Stone.
 In The 20th International Joint Conference
            on Artificial Intelligence, pp. 2212–2217, January 2007.
 IJCAI-07
 Details
                  
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               (129.5kB
               )
                [ps]
               (184.9kB
               )
- Intelligent Autonomous Robotics:  A Robot Soccer Case Study,
 Peter
            Stone.
 Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan \& Claypool Publishers, 2007.
 Available from Synthesis page.
 ISBN: 9781598291262
 Details
                  
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- Learning and Multiagent Reasoning for Autonomous Agents.
 Peter Stone.
 In
            The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
 IJCAI-07
 Details
                  
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               (308.5kB
               )
                [ps]
               (379.3kB
               )
- DARPA Urban Challenge Technical Report: Austin Robot Technology.
 Peter
            Stone, Patrick Beeson, Tekin
            Mericli, and Ryan Madigan.
 June 2007. Available from http://www.darpa.mil/grandchallenge/rules.asp
 Details
                  
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               (2.7MB
               )
- Selective Visual Attention for Object Detection on a Legged Robot.
 Daniel
            Stronger and Peter Stone.
 In Gerhard Lakemeyer, Elizabeth
            Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
            in Artificial Intelligence, pp. 158–170, Springer Verlag, Berlin, 2007.
 Some videos
            referenced in the paper.
 Details
                  
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               (159.7kB
               )
                [ps]
               (342.4kB
               )
- A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot.
 Daniel
            Stronger and Peter Stone.
 In IEEE International Conference on Robotics
            and Automation, pp. 3915–3920, April 2007.
 Details
                  
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               (271.4kB
               )
                [ps]
               (2.2MB
               )
- Keeping in Touch: Maintaining Biconnected Structure by Homogeneous Robots.
 Mazda
            Ahmadi and Peter Stone.
 In Proceedings of the Twenty-First National
            Conference on Artificial Intelligence, pp. 580–85, July 2006.
 AAAI
            2006.
 Additional details on the distributed "biconnected check" can be found in Keeping
            in Touch: A Distributed Check for Biconnected Structure by Homogeneous Robots in the 2006 International Symposium
            on Distributed Autonomous Robotic Systems (DARS 2006).
 Details
                  
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               (105.0kB
               )
                [ps]
               (128.8kB
               )
- A Multi-Robot System for Continuous Area Sweeping Tasks.
 Mazda
            Ahmadi and Peter Stone.
 In Proceedings of the IEEE International
            Conference on Robotics and Automation, pp. 1724–1729, May 2006.
 Some videos
            of the robot referenced in the paper.
 ICRA 2006
 Details
                  
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               (171.3kB
               )
                [ps]
               (314.6kB
               )
- Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data.
 Mohan
            Sridharan and Peter Stone.
 In The Ninth International Conference
            on Control, Automation, Robotics and Vision, December 2006.
 ICARCV
            2006
 Details
                  
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               (444.1kB
               )
                [ps]
               (2.3MB
               )
- From Pixels to Multi-Robot Decision-Making:  A Study in Uncertainty.
 Peter
            Stone, Mohan Sridharan, Daniel
            Stronger, Gregory Kuhlmann, Nate Kohl,
            Peggy Fidelman, and Nicholas
            K. Jong.
 Robotics and Autonomous Systems , 54(11):933–43, November 2006. Special issue on Planning
            Under Uncertainty in Robotics.
 Official versionfrom the RAS
            publisher's webpage.
 Details
                  
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               (260.5kB
               )
                [ps]
               (3.6MB
               )
- Keepaway Soccer:  From Machine Learning Testbed to Benchmark.
 Peter Stone,
            Gregory Kuhlmann, Matthew E. Taylor,
            and Yaxin Liu.
 In Itsuki
            Noda, Adam Jacoff, Ansgar Bredenfeld, and Yasutake Takahashi, editors, RoboCup-2005: Robot Soccer World Cup IX,
            pp. 93–105, Springer Verlag, Berlin, 2006.
 Some simulations
            of keepaway referenced in the paper and keepaway software.
 Official version from Publisher's
            Webpage© Springer-Verlag
 Details
                  
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               (567.7kB
               )
                [ps]
               (2.3MB
               )
- The UT Austin Villa 2006 RoboCup Four-Legged Team.
 Peter Stone, Peggy Fidelman, Nate Kohl, Gregory
            Kuhlmann, Tekin Mericli, Mohan Sridharan,
            and Shao-en Yu.
 Technical Report UT-AI-TR-06-337, The University of Texas at Austin, Department of Computer Sciences, AI
            Laboratory, 2006.
 At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2006.html#06-337
 Details
                  
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               (123.7kB
               )
                [ps]
               (127.2kB
               )
- Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot.
 Daniel
            Stronger and Peter Stone.
 Connection Science, 18(2):97–119,
            2006. Special Issue on Developmental Robotics.
 Connection
            Science Journal. Contains material that was previously published in an ICRA-2005
            paper.
 Details
                  
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               (372.6kB
               )
                [ps]
               (1.4MB
               )
- Continuous Area Sweeping: A Task Definition and Initial Approach.
 Mazda
            Ahmadi and Peter Stone.
 In The 12th International Conference on Advanced
            Robotics, July 2005.
 Some videos of
            the robot referenced in the paper.
 ICAR 2005
 Details
                  
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            [pdf]
               (186.7kB
               )
                [ps]
               (243.1kB
               )
- Autonomous Color Learning on a Mobile Robot.
 Mohan Sridharan and Peter Stone.
 In Proceedings of the Twentieth National Conference on Artificial
            Intelligence, July 2005.
 Some videos of
            the robot referenced in the paper.
 AAAI 2005
 Details
                  
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            Download: 
            [pdf]
               (901.5kB
               )
                [ps]
               (6.4MB
               )
- Real-Time Vision on a Mobile Robot Platform.
 Mohan Sridharan and Peter Stone.
 In IEEE/RSJ International Conference on Intelligent Robots
            and Systems (IROS), August 2005.
 Some videos
            of the robot referenced in the paper.
 IROS-2005
 Details
                  
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               (396.1kB
               )
                [ps]
               (5.0MB
               )
- Practical Vision-Based Monte Carlo Localization on a Legged Robot.
 Mohan
            Sridharan, Gregory Kuhlmann, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation, April 2005.
 ICRA
            2005
 Details
                  
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               (217.6kB
               )
                [ps]
               (2.0MB
               )
                [slides.pdf]
               (2.5MB
               )
- The UT Austin Villa 2005 RoboCup Four-Legged Team.
 Peter Stone, Kurt Dresner, Peggy
            Fidelman, Nate Kohl, Gregory Kuhlmann,
            Mohan Sridharan, and Daniel
            Stronger.
 Technical Report UT-AI-TR-05-325, The University of Texas at Austin, Department of Computer Sciences, AI
            Laboratory, 2005.
 At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2005.html#05-325
 Details
                  
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               (186.2kB
               )
                [ps]
               (243.4kB
               )
- The UT Austin Villa 2004 RoboCup Four-Legged Team:  Coming of Age.
 Peter
            Stone, Kurt Dresner, Peggy
            Fidelman, Nicholas K. Jong, Nate
            Kohl, Gregory Kuhlmann, Mohan
            Sridharan, and Daniel Stronger.
 Technical Report
            UT-AI-TR-04-313, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2004.
 At http://www.cs.utexas.edu/ftp/pub/AI-Lab/index/html/Abstracts.2004.html#04-313
 Details
                  
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               (555.3kB
               )
                [ps]
               (1.6MB
               )
IBM
      
      
         - Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
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               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Selecting Compliant Agents for Opt-in Micro-Tolling.
 Josiah Hanna,
            Guni Sharon, Stephen
            Boyles, and Peter Stone.
 In Proceedings of the 33rd AAAI Conference
            on Artificial Intelligence (AAAI), January 2019.
 Details
                  
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               (2.2MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (1.0MB
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- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Autonomous Return on Investment Analysis of Additional Processing Resources.
 Jonathan
            Wildstrom, Peter Stone, and Emmett
            Witchel.
 International Journal on Autonomic Computing, 1(3):280–296, Inderscience Publishers, Inderscience
            Publishers, Geneva, SWITZERLAND, 2010.
 IJAC
 Details
                  
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- Learning and Multiagent Reasoning for Autonomous Agents.
 Peter Stone.
 In
            The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
 IJCAI-07
 Details
                  
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               (308.5kB
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               (379.3kB
               )
- Evolutionary Function Approximation for Reinforcement Learning.
 Shimon
            Whiteson and Peter Stone.
 Journal of Machine Learning Research,
            7:877–917, May 2006.
 Available from journal's web
            page.
 Details
                  
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               (1.7MB
               )
                [ps]
               (6.1MB
               )
- Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning.
 Shimon
            Whiteson and Peter Stone.
 In Proceedings of the Twenty-First National
            Conference on Artificial Intelligence, pp. 518–23, July 2006.
 AAAI
            2006
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               )
- On-Line Evolutionary Computation for Reinforcement Learning in Stochastic Domains.
 Shimon
            Whiteson and Peter Stone.
 In Proceedings of the Genetic and Evolutionary
            Computation Conference, pp. 1577–84, July 2006.
 GECCO 2006
 Details
                  
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               (1.4MB
               )
- Adapting to Workload Changes Through On-The-Fly Reconfiguration.
 Jonathan
            Wildstrom, Peter Stone, Emmett
            Witchel, and Mike Dahlin.
 Technical Report UT-AI-TR-06-330, The University
            of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2006.
 At ftp://ftp.cs.utexas.edu/pub/AI-Lab/tech-reports/UT-AI-TR-06-330.pdf
 Details
                  
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- Automatic Feature Selection via Neuroevolution.
 Shimon
            Whiteson, Peter Stone, Kenneth
            O. Stanley, Risto Miikkulainen, and Nate
            Kohl.
 In Proceedings of the Genetic and Evolutionary Computation Conference, June 2005.
 Details
                  
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                [ps]
               (1.6MB
               )
- Towards Self-Configuring Hardware for Distributed Computer Systems.
 Jonathan
            Wildstrom, Peter Stone, Emmett
            Witchel, Raymond J. Mooney, and Mike
            Dahlin.
 In The Second International Conference on Autonomic Computing, pp. 241–249, June 2005.
 ICAC-05
 A revised version of the paper appeared on IBM's Developer
            Works website
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- Adaptive Job Routing and Scheduling.
 Shimon Whiteson
            and Peter Stone.
 Engineering Applications of Artificial Intelligence,
            17(7):855–69, October 2004. Special issue on Autonomic Computing and Automation
 Available from the publisher's
            webpage
 The version from this page corrects a minor error in the published version.
 An earlier version appeared
            in the proceedings of The Sixteenth Innovative Applications of Artificial
            Intelligence Conference (IAAI 2004)
 Details
                  
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               )
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               (1.1MB
               )
DARPA
      
      
         - L3M+P: Lifelong Planning with Large Language Models.
 Krish Agarwal, Yuqian Jiang,
            Jiaheng Hu, Bo Liu, and Peter
            Stone.
 In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.
 Details
                  
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               (1.2MB
               )
- Proto Successor Measure: Representing the Behavior Space of an RL Agent.
 Siddhant Agarwal, Harshit Sikchi, Peter
            Stone, and Amy Zhang.
 In International Conference on Machine Learning, June 2025.
 Details
                  
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               (911.1kB
               )
- Multi-Agent Inverse Reinforcement Learning in Real World Unstructured Pedestrian Crowds.
 Rohan
            Chandra, Haresh Karnan, Negar Mehr, Peter
            Stone, and Joydeep Biswas.
 In IEEE/RSJ International Conference on Intelligent
            Robots and Systems (IROS), October 2025.
 Details
                  
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               (695.7kB
               )
- Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks.
 Viraj Joshi, Zifan
            Xu, Bo Liu, Peter Stone, and
            Amy Zhang.
 In Reinforcement Learning Conference (RLC), August 2025.
 Details
                  
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               (3.5MB
               )
- Reinforcement Learning within the Classical Robotics Stack: A Case Study in Robot Soccer.
 Adam Labiosa, Zhihan Wang,
            Siddhant Agarwal, William Cong, Geethika Hemkumar, Abhinav Narayan Harish, Benjamin Hong, Josh Kelle, Chen Li, Yuhao Li, Zisen
            Shao, Peter Stone, and Josiah
            Hanna.
 In International Conference on Robotics and Automation (ICRA), May 2025.
 Details
                  
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               (1.1MB
               )
- Longhorn: State Space Models are Amortized Online Learners.
 Bo Liu,
            Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, and qiang liu.
 In International
            Conference on Learning Representations, April 2025.
 Details
                  
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               (877.2kB
               )
- PRESTO: Fast Motion Planning Using Diffusion Models Based on Key-Configuration Environment Representation.
 Mingyo
            Seo, Yoonyoung Cho, Yoonchang Sung, Peter
            Stone, Yuke Zhu, and Beomjoon Kim.
 In IEEE International Conference
            on Robotics and Automation (ICRA), May 2025.
 Details
                  
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            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pdf]
               (2.1MB
               )
                [poster.pdf]
               (1.3MB
               )
- Dyn-O: Building Structured World Models with Object-Centric Representations.
 Zizhao
            Wang, Kaixin Wang, Li Zhao, Peter Stone, and Jiang Bian.
 In Annual
            Conference on Neural Information Processing Systems, December 2025.
 Details
                  
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               (22.9MB
               )
- LLM-GROP: Visually grounded robot task and motion planning with large language models.
 Xiaohan Zhang, Yan Ding,
            Yohei Hayamizu, Zainab Altaweel, Yifeng Zhu, Yuke
            Zhu, Peter Stone, Chris Paxton, and Shiqi
            Zhang.
 The International Journal of Robotics Research, 2025.
 Details
                  
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               (2.5MB
               )
- Telemoma: A Modular and Versatile Teleoperation System for Mobile Manipulation.
 Shivin Dass, Wensi Ai, Yuqian
            Jiang, Samik Singh, Jiaheng Hu,
            Ruohan Zhang, Peter Stone,
            Ben Abbatematteo, and Roberto Martin-Martin.
 In ICRA Workshop on Mobile Manipulation and Embodied Intelligence,
            May 2024.
 Details
                  
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               (2.9MB
               )
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
 Haresh,
            Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
 In
            International Conference on Robotics and Automation, May 2024.
 Details
                  
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               (4.3MB
               )
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
 Amir Hossain Raj, Zichao
            Hu, Haresh Karnan, Rohan Chandra,
            Amirreza Payandeh, Luisa Mao, Peter Stone, Joydeep
            Biswas, and and Xuesu Xiao.
 In International Conference on Robotics
            and Automation, May 2024.
 Details
                  
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               (2.0MB
               )
- Task Phasing: Automated Curriculum Learning from Demonstrations.
 Vaibhav Bajaj, Guni
            Sharon, and Peter Stone.
 In Proceedings of the 33rd International
            Conference on Automated Planning and Scheduling (ICAPS 2023), July 2023.
 Accompanying code
 Details
                  
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               (416.0kB
               )
- A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems.
 Megan M. Baker, Alexander New, Mario
            Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Ese Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan  C. Brown,
            Zachary Daniels, Anurag Daram, Fabien Delattre, Ryan Dellana, Eric  Eaton,
            Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra  Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris,
            Dhireesha Kudithipudi,  Erik Learned-Miller, Seungwon Lee,
            Michael L. Littman, Sandeep Madireddy,  Jorge A. Mendez, Eric Q. Nguyen, Christine
            D. Piatko, Praveen K. Pilly, Aswin  Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan,
            Neale Ratzlaff, Andrea  Soltoggio, Peter Stone, Indranil Sur, Zhipeng
            Tang, Saket Tiwari, Kyle  Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel
            Yedidsion, Shangqun  Yu, and Gautam K. Vallabha.
 Neural Networks, pp. 274–96, March 2023.
 Available
            from https://arxiv.org/abs/2301.07799
 Official version on publisher's website
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- "What's That Robot Doing Here?": Factors Influencing Perceptions Of Incidental Encounters With Autonomous Quadruped Robots.
 Elliott
            Hauser, Yao-Cheng Chan, Geethika Hemkumar, Daksh Dua, Parth Chonkar, Efren Mendoza Enriquez, Tiffany Kao, Shikhar Gupta, Huihai
            Wang, Justin Hart, Reuth Mirsky,
            Joydeep Biswas, Junfeng Jiao, and Peter
            Stone.
 In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23), pp.
            1–15, July 2023.
 Available online at https://dl.acm.org/doi/10.1145/3597512.3599707
 Details
                  
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- Causal Policy Gradient for Whole-Body Mobile Manipulation.
 Jiaheng Hu,
            Peter Stone, and Roberto Martin-Martin.
 In Robotics: Science and Systems
            (RSS), July 2023.
 Details
                  
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               (4.0MB
               )
- VaryNote: A Method to Automatically Vary the Number of Notes in           Symbolic Music.
 Juan M. Huerta, Bo
            Liu, and Peter Stone.
 In The 16th International Symposium on Computer
            Music Multidisciplinary Research, (CMMR), Springer, November 2023.
 the
            conference presentation
 Details
                  
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               (1.4MB
               )
                [slides.pdf]
               (2.3MB
               )
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
 Haresh
            Karnan, Elvin Yang, Daniel Farkash, Garrett
            Warnell, Joydeep Biswas, and Peter
            Stone.
 In The Conference on Robot Learning (CoRL), November 2023.
 Poster,
            Video, Project Website
 Details
                  
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               (25.7MB
               )
- Reward (Mis)design for Autonomous Driving.
 W. Bradley Knox, Alessandro Allievi,
            Holger Banzhaf, Felix Schmitt, and Peter Stone.
 Artificial Intelligence,
            316:103829, 2023.
 Paper webpage
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               (696.3kB
               )
                [ps]
               (5.6MB
               )
- Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning.
 Bo
            Liu, Yihao Feng, Qiang Liu, and Peter Stone.
 In Thirty-Seventh AAAI
            Conference on Artificial Intelligence (AAAI), Februray 2023.
 Details
                  
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               (1.8MB
               )
- Towards a Real-Time, Low-Resource, End-to-end Object Detection Pipeline for Robot Soccer.
 Sai Kiran Narayanaswami,
            Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit
            Narvekar, and Peter Stone.
 In Amy Eguchi, Nuno Lau, Maike Paetzel-Prussman,
            and Thanapat Wanichanon, editors, RoboCup 2022: Robot World Cup XXV, pp. 62–74, Springer International Publishing,
            2023.
 The book
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               (572.2kB
               )
- Program Embeddings for Rapid Mechanism Evaluation.
 Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
            and Peter Stone.
 In ICRA Workshop on Multi-Robot Learning, May 2023.
 Details
                  
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               (1.3MB
               )
                [poster.pdf]
               (916.2kB
               )
- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
 Jinsoo Park, Xuesu
            Xiao, Garrett Warnell, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 6-minute video
            presentation
 Details
                  
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            [pdf]
               (4.6MB
               )
                [slides.pptx]
               (21.3MB
               )
                [poster.pdf]
               (1.1MB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
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               (4.8MB
               )
- Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search.
 Yoonchang
            Sung and Peter Stone.
 In Robotics: Science and Systems (RSS2023),
            July 2023.
 Video presentation
 Details
                  
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            [pdf]
               (6.9MB
               )
                [slides.pdf]
               (8.1MB
               )
                [poster.pdf]
               (6.9MB
               )
- D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning.
 Caroline
            Wang, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2023.
 Details
                  
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               (1.6MB
               )
                [slides.pdf]
               (2.4MB
               )
                [poster.pdf]
               (1.4MB
               )
- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
 Caroline
            Wang, Ishan Durugkar, Elad Liebman,
            and Peter Stone.
 In Proceedings of the 37th AAAI Conference on Artificial
            Intelligence (AAAI-23), February 2023.
 Details
                  
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               (801.2kB
               )
                [slides.pdf]
               (3.7MB
               )
                [poster.pdf]
               (1.4MB
               )
- Model-Based Meta Automatic Curriculum Learning.
 Zifan Xu, Yulin
            Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian
            Jiang, Bo Liu, and Peter Stone.
 In
            The Second Conference on Lifelong Learning Agents (CoLLAs), August 2023.
 Video
            presentation
 Details
                  
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            Download: 
            [pdf]
               (1.0MB
               )
                [slides.pptx]
               (6.6MB
               )
- Benchmarking Reinforcement Learning Techniques for Autonomous Navigation.
 Zifan
            Xu, Bo Liu, Xuesu Xiao, Anirudh
            Nair, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 Details
                  
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               (4.8MB
               )
- Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.
 Xiaohan Zhang, Saeid Amiri,
            Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
 Autonomous
            Robots, March 2023.
 Official version
            on publisher's website
 Details
                  
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               (2.6MB
               )
- Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu,
            Peter Stone, and Shiqi Zhang.
 In
            International Conference on Intelligent Robots and Systems (IROS), October 2023.
 Project
            website (includes poster and 5-minute video presentation)
 Details
                  
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            [pdf]
               (4.0MB
               )
                [slides.pdf]
               (6.6MB
               )
- Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles.
 Jiaxun
            Cui, Hang Qiu, Dian Chen, Peter
            Stone, and Yuke Zhu.
 In IEEE/CVF Conference on Computer Vision and
            Pattern Recognition (CVPR), June 2022.
 Project website
 Details
                  
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            [pdf]
               (3.5MB
               )
- Quantifying Human Rationality in Ad-hoc Teamwork.
 Yair Hanina, Reuth
            Mirsky, William Macke, and Peter
            Stone.
 In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.
 Details
                  
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            Download: 
            [pdf]
               (404.2kB
               )
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
 Eddy Hudson, Garrett
            Warnell, Faraz Torabi, and Peter
            Stone.
 In International Conference on Robotics and Automation (ICRA), May 2022.
 Presentation
            Video
 Details
                  
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            Download: 
            [pdf]
               (2.5MB
               )
- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
 Haresh Karnan, Anirudh Nair, Xuesu Xiao,
            Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
            Hart, Joydeep Biswas, and Peter Stone.
 Robotics
            and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
 Dataset;
            Poster; Video Presentation
 Details
                  
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            [pdf]
               (4.2MB
               )
- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
 Haresh
            Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 In
            International Conference on Intelligent Robots and Systems, 2022, October 2022.
 Details
                  
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            [pdf]
               (3.0MB
               )
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
 Haresh
            Karnan, Garrett Warnell, Xuesu
            Xiao, and Peter Stone.
 In International Conference on Robotics and
            Automation, 2022, May 2022.
 Poster,
            Video
 Details
                  
               BibTeX
                  
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            [pdf]
               (1.5MB
               )
- Adversarial Imitation Learning from Video using a State Observer.
 Haresh
            Karnan, Garrett Warnell, Faraz
            Torabi, and Peter Stone.
 In International Conference on Robotics
            and Automation, 2022, May 2022.
 Video
 Details
                  
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            Download: 
            [pdf]
               (933.2kB
               )
- Effective Mutation Rate Adaptation through Group Elite Selection.
 Akarsh Kumar, Bo
            Liu, Risto Miikkulainen, and Peter
            Stone.
 In Proceedings of the Genetic and Evolutionary Computation Conference, July 2022.
 Details
                  
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            [pdf]
               (9.7MB
               )
- BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.
 Bo
            Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu.
 In Conference
            on Neural Information Processing Systems, 2022, December 2022.
 Details
                  
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            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (1.6MB
               )
                [poster.pdf]
               (885.6kB
               )
- Continual Learning and Private Unlearning.
 Bo Liu, Qiang Liu, and Peter Stone.
 In Proceedings of the 1st Conference on Lifelong Learning Agents
            (CoLLA), August 2022.
 Details
                  
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            Download: 
            [pdf]
               (440.4kB
               )
                [slides.pdf]
               (710.5kB
               )
- Value Function Decomposition for Iterative Design of Reinforcement Learning Agents.
 James MacGlashan, Evan Archer,
            Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2022.
 5-minute
            Video Presentation; the
            slides
 Details
                  
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            [pdf]
               (11.6MB
               )
- A Survey of Ad Hoc Teamwork Research.
 Reuth Mirsky, Ignacio
            Carlucho, Arrasy Rahman, Eliott Fosong, William
            Macke, Mohan Sridharan, Peter
            Stone, and Stefano Albrecht.
 In Baumeister, Dorothea and Rothe, Jörg, editors,
            Multi-Agent Systems, pp. 275–93, Springer International Publishing, Cham, 2022.
 Details
                  
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            [pdf]
               (198.8kB
               )
- Task Factorization in Curriculum Learning.
 Reuth Mirsky,
            Shahaf S. Shperberg, Yulin Zhang, Zifan
            Xu, Yuqian Jiang, Jiaxun Cui, and Peter
            Stone.
 In ICML workshop on Decision Awareness in Reinforcement Learning (DARL), July 2022.
 recorded
            presentation
 Details
                  
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            [pdf]
               (1011.6kB
               )
- Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings.
 Kingsley Nweye, Bo
            Liu, Nagy Zoltan, and Peter Stone.
 Journal of Energy and AI, 2022,
            September 2022.
 Details
                  
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            [pdf]
               (5.9MB
               )
- A Rule-based Shield: Accumulating Safety Rules from Catastrophic Action Effects.
 Shahaf Shperberg, Bo
            Liu, Allessandro Allievi, and Peter Stone.
 In Proceedings of the
            1st Conference on Lifelong Learning Agents (CoLLA), August 2022.
 Details
                  
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            [pdf]
               (8.9MB
               )
- Dynamic Sparse Training for Deep Reinforcement Learning.
 Ghada Sokar, Elena
            Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy,
            and Peter Stone.
 In Proceedings of the 31st International Joint Conference
            on Artificial Intelligence, July 2022.
 arXiv version with the appendix
 Details
                  
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            [pdf]
               (3.7MB
               )
                [slides.pptx]
               (16.7MB
               )
- Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning.
 Yoonchang
            Sung, Zizhao Wang, and Peter Stone.
 In
            Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Details
                  
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            Download: 
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               (742.0kB
               )
                [poster.pdf]
               (5.7MB
               )
- Causal Dynamics Learning for Task-Independent State Abstraction.
 Zizhao
            Wang, Xuesu Xiao, Zifan Xu, Yuke
            Zhu, and Peter Stone.
 In Proceedings of the 39th International Conference
            on Machine Learning (ICML2022), July 2022.
 recorded presentation
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               (4.0MB
               )
                [poster.pdf]
               (1.6MB
               )
- Visually Grounded Task and Motion Planning for Mobile Manipulation.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuke Zhu, Peter
            Stone, and Shiqi Zhang.
 In International Conference on Robotics
            and Automation (ICRA), May 2022.
 Project page
 Code
 Details
                  
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               (3.4MB
               )
- Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation.
 Yifeng
            Zhu, Peter Stone, and Yuke
            Zhu.
 IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.
 Project page
 Code
 Details
                  
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               (9.3MB
               )
- VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors.
 Yifeng
            Zhu, Abhishek Joshi, Peter Stone, and Yuke
            Zhu.
 In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Project page
 Code
 Details
                  
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               )
- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
 Michael
            Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
 Operations
            Research, March 2021.
 Details
                  
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               (692.5kB
               )
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
 Roberto Capobianco, Varun Kompella, James
            Ault, Guni Sharon, Stacy
            Jong, Spencer Fox, Lauren
            Meyers, Peter R. Wurman, and Peter
            Stone.
 The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
 Contains
            material that was previously published in an AAMAS
            2021 paper and a AAAI 2020 Fall
            Symposium paper.
 Article available from  JAIR website.
 Simulator
            source code.
 Details
                  
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               (1.6MB
               )
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
 Jiaxun
            Cui, William Macke, Harel
            Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
            Stone.
 In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2021.
 Project page, with videos
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               )
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               (1.5MB
               )
- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
 Yunshu Du, Garrett
            Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
            E. Taylor.
 Neural Computing and Applications, May 2021.
 Details
                  
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               (2.2MB
               )
- Adversarial Intrinsic Motivation for Reinforcement Learning.
 Ishan Durugkar,
            Mauricio Tec, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
            December 2021.
 slides and video presentation
 Details
                  
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               (5.1MB
               )
- Capturing Skill State in Curriculum Learning for Human Skill Acquisition.
 Keya
            Ghonasgi, Reuth Mirsky, Sanmit
            Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D.
            Deshpande.
 In International Conference on Intelligent Robots and Systems (IROS), September 2021.
 Video
            presentation
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               (1.6MB
               )
- Machine versus Human Attention in Deep Reinforcement Learning Tasks.
 Sihang Guo, Ruohan
            Zhang, Bo Liu, Yifeng Zhu,
            Mary Hayhoe, Dana Ballard, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2021.
 Details
                  
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               (1.6MB
               )
- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
 Josiah
            P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
            Warnell, and Peter Stone.
 Special Issue on Reinforcement Learning
            for Real Life, Machine Learning, 2021, May 2021.
 Details
                  
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               (3.0MB
               )
- Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy.
 Josiah
            P. Hanna, Scott Niekum, and Peter
            Stone.
 Machine Learning (MLJ), 110:1267–1317, May 2021.
 Details
                  
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               (3.7MB
               )
- Incorporating Gaze into Social Navigation.
 Justin Hart, Reuth
            Mirsky, Xuesu Xiao, and Peter
            Stone.
 In RSS Workshop on Social Robot Navigation, July 2021.
 Details
                  
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               (4.8MB
               )
                [slides.pdf]
               (3.5MB
               )
- Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation.
 Blake Holman, Abrar
            Anwar, Akash Singh, Mauricio Tec, Justin
            Hart, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA), May 2021.
 Details
                  
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            Download: 
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               (5.7MB
               )
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
 Eddy Hudson, Garrett
            Warnell, and Peter Stone.
 In Autonomous Robots and Multirobot Systems
            Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
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               (393.0kB
               )
- Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle.
 Yu-Sian Jiang, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the 35th AAAI Conference
            on Artificial Intelligence (AAAI), Feb 2021.
 Details
                  
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               (911.3kB
               )
                [poster.pdf]
               (1.1MB
               )
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
 Yuqian
            Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
 In
            Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
 Details
                  
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               (1.8MB
               )
                [slides.pdf]
               (1.8MB
               )
- A Lifelong Learning Approach to Mobile Robot Navigation.
 Bo Liu, Xuesu Xiao, and Peter Stone.
 IEEE
            Robotics and Automation Letters (RA-L), 6(2), April 2021.
 Presented at IEEE International Conference on Robotics
            and Automation (ICRA),
 Video presentation
 Details
                  
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               (3.6MB
               )
- Conflict-Averse Gradient Descent for Multi-task learning.
 Bo Liu, Xingchao
            Liu, Xiaojie Jin, Peter Stone, and Qiang Liu.
 In Conference on Neural
            Information Processing Systems (NeurIPS), 2021, December 2021.
 slides
            and 9-minute presentation
 github repository
 Details
                  
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               (9.7MB
               )
- Team  Orienteering  Coverage  Planning  with  Uncertain  Reward.
 Bo Liu,
            Xuesu Xiao, and Peter Stone.
 In
            International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
 Details
                  
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               (3.9MB
               )
- Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition.
 Bo
            Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke
            Zhu, and Animashree Anandkumar.
 In Proceedings of the 38th International Conference on Machine Learning, PMLR 139,
            2021 (ICML), July 2021.
 Details
                  
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               (2.2MB
               )
                [poster.pdf]
               (1.1MB
               )
- Expected Value of Communication for Planning in Ad Hoc Teamwork.
 William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.
 Details
                  
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               (869.9kB
               )
                [slides.pdf]
               (2.3MB
               )
                [poster.pdf]
               (1.8MB
               )
- Is the Cerebellum a Model-Based Reinforcement Learning Agent?.
 Bharath Masetty, Reuth
            Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter
            Stone.
 In Adaptive and Learning Agents Workshop at AAMAS, May 2021.
 Video
            presentation
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               )
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               (1.5MB
               )
- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
 Reuth
            Mirsky and Peter Stone.
 In ICSR workshop on Adaptive Social Interaction
            and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
 Details
                  
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               (194.4kB
               )
- The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care.
 Reuth
            Mirsky and Peter Stone.
 In Proceedings of the 20th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
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            Download: 
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               (679.2kB
               )
- Reasoning about Human Behavior in Ad Hoc Teamwork.
 Jennifer Suriadinata, William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
 Video
            Presentation
 Details
                  
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               (926.2kB
               )
- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2021.
 Video presentation
 Details
                  
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               (742.7kB
               )
- APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback.
 Zizhao
            Wang, Xuesu Xiao, Bo Liu,
            Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), October 2021.
 5-minute
            Video Presentation;  15-minute Video Presentation
 Details
                  
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            Download: 
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               (1.1MB
               )
                [slides.pdf]
               (2.7MB
               )
- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
 Zizhao
            Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
            Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
 In Proceedings
            of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
 1-minute
            Video Summary;   15-minute Video Presentation
 Details
                  
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               (2.9MB
               )
                [slides.pdf]
               (2.7MB
               )
- APPLI: Adaptive Planner Parameter Learning From Interventions.
 Zizhao Wang,
            Xuesu Xiao, Bo Liu, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
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               (4.2MB
               )
- APPLR: Adaptive Planner Parameter Learning from Reinforcement.
 Zifan Xu,
            Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett
            Warnell, Bo Liu, Zizhao Wang,
            and Peter Stone.
 In Proceedings of the 2021 IEEE International Conference
            on Robotics and Automation (ICRA 2021), June 2021.
 Video
            presentation
 Project webpage
 Details
                  
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               (3.4MB
               )
                [slides.pptx]
               (27.4MB
               )
- Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning.
 Zifan
            Xu, Xuesu Xiao, Garrett
            Warnell, Anirudh Nair, and Peter Stone.
 In Proceedings of the 2021
            IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), October 2021.
 Video
            presentation
 Details
                  
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               (4.5MB
               )
- A Scavenger Hunt for Service Robots.
 Harel Yedidsion,
            Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
            Stone.
 In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
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               (1.5MB
               )
- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
 Harel
            Yedidsion, Shani Alkoby, and Peter
            Stone.
 Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
 arXiv
 Details
                  
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               (478.9kB
               )
- Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks.
 Ruohan
            Zhang, Faraz Torabi, Garrett
            Warnell, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems,
            35(31), June 2021.
 official online version
 Details
                  
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               (3.8MB
               )
- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
 Siddarth Desai, Ishan
            Durugkar, Haresh Karnan, Garrett
            Warnell, Josiah Hanna, and Peter
            Stone.
 In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
            December 2020.
 Poster
 Details
                  
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               (1.3MB
               )
- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
 Siddharth Desai, Haresh
            Karnan, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 11-minute video
            presentation.
 Details
                  
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               (1.9MB
               )
- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
 Ishan
            Durugkar, Elad Liebman, and Peter
            Stone.
 In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
            2020.
 Details
                  
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               (3.9MB
               )
- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
 Justin Hart,
            Reuth Mirsky, Xuesu Xiao,
            Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
            Stone.
 In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
 Video presentation
 Details
                  
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               (3.2MB
               )
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
 Haresh
            Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 14-minute video
            presentation.
 Details
                  
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               (506.6kB
               )
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
 Shih-Yun Lo, Shiqi
            Zhang, and Peter Stone.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, October 2020.
 Contains material that was previously published in an AAMAS-18
            paper (awarded the Best Robotics Paper Award at AAMAS 2018)
 Also
            available from  JAIR website
 Details
                  
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            Download: 
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               (4.0MB
               )
- Learning and Reasoning for Robot Dialog and Navigation Tasks.
 Keting Lu, Shiqi
            Zhang, Peter Stone, and Xiaoping
            Chen.
 In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
            107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
 Official version from ACL
            Digital Library, including a link to the conference presentation
 Details
                  
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               (3.6MB
               )
- A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork.
 Reuth
            Mirsky, William Macke, Andy Wang, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 29th International
            Joint Conference on Artificial Intelligence, July 2020.
 15-minute
            presentation
 Details
                  
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            Download: 
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               (1.2MB
               )
                [slides.pdf]
               (1.4MB
               )
- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
 Sanmit
            Narvekar, Bei Peng, Matteo Leonetti, Jivko
            Sinapov, Matthew E. Taylor, and Peter
            Stone.
 Journal of Machine Learning Research, 21(181):1–50, 2020.
 Details
                  
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               (1.4MB
               )
- Generalizing Curricula for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In 4th Lifelong Learning Workshop at the International
            Conference on Machine Learning (ICML 2020), July 2020.
 Details
                  
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            Download: 
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               (330.4kB
               )
                [slides.pdf]
               (3.8MB
               )
- Learning to Improve Multi-Robot Hallway Navigation.
 Jin-Soo Park, Brian Tsang, Harel
            Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
 In Proceedings of the 4th Conference on Robot Learning (CoRL),
            November 2020.
 Video presentation
 Details
                  
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               (1.3MB
               )
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
 Brahma
            Pavse, Faraz Torabi, Josiah
            Hanna, Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
 Video
            of the experiments; 13-minute video presentation.
 Details
                  
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            Download: 
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               (405.1kB
               )
                [slides.pptx]
               (115.4MB
               )
- Reducing Sampling Error in Batch Temporal Difference Learning.
 Brahma Pavse,
            Ishan Durugkar, Josiah Hanna,
            and Peter Stone.
 In Proceedings of the 37th International Conference
            on Machine Learning (ICML), July 2020.
 The paper and talk is available from the ICML
            2020 virtual conference page.
 Details
                  
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               (738.4kB
               )
                [slides.pdf]
               (5.2MB
               )
- On Sampling Error in Batch Action-Value Prediction Algorithms.
 Brahma S. Pavse,
            Josiah P. Hanna, Ishan Durugkar,
            and Peter Stone.
 In In the Offline Reinforcement Learning Workshop at
            Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
 5-minute
            Video Presentation
 Details
                  
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               (327.2kB
               )
- Deep R-Learning for Continual Area Sweeping.
 Rishi Shah, Yuqian Jiang, Justin
            Hart, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
 1-minute
            video demonstration; 13-minute Video
            presentation.
 Details
                  
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            Download: 
            [pdf]
               (374.2kB
               )
                [slides.pdf]
               (1.1MB
               )
- Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks.
 Lemeng Wu, Bo
            Liu, Peter Stone, and Qiang Liu.
 In Advances in Neural Information
            Processing Systems 34 (2020), December 2020.
 Details
                  
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            Download: 
            [pdf]
               (8.1MB
               )
                [slides.pdf]
               (744.8kB
               )
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
 Xuesu
            Xiao, Bo Liu, Garrett
            Warnell, Jonathan Fink, and Peter Stone.
 IEEE Robotics and Automation
            Letters (RA-L), June 2020.
 Presented at International Conference on Intelligent Robots and Systems ({IROS})\\  
             5-minute Video presentation; 15-minute
            Video presentation
 Project webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
                [slides.pdf]
               (21.1MB
               )
- Ad hoc Teamwork with Behavior Switching Agents.
 Manish Ravula, Shani Alkobi and Peter
            Stone.
 In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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            Download: 
            [pdf]
               (350.4kB
               )
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Multi-Robot Planning with Conflicts and Synergies.
 Yuqian Jiang, Harel
            Yedidsion, Shiqi Zhang, Guni
            Sharon, and Peter Stone.
 Autonomous Robots, Springer, March 2019.
 Official version from Publisher's Webpage
 Details
                  
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            Download: 
            [pdf]
               (2.0MB
               )
- Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
 Yuqian
            Jiang, Fangkai Yang, Shiqi
            Zhang, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
 Details
                  
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            Download: 
            [pdf]
               (925.2kB
               )
- Open-World Reasoning for Service Robots.
 Yuqian Jiang, Nick
            Walker, Justin Hart, and Peter Stone.
 In
            Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
 Accompanying video
 Details
                  
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               (813.5kB
               )
- The right music at the right time: adaptive personalized playlists based on sequence modeling.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone Peter Stone.
 Management Information Systems Quarterly, 43(3):765–786, Society for Information Management
            and The Management Information Systems Research Center, 2019.
 Available from publisher's
            website.
 Details
                  
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            [pdf]
               (4.0MB
               )
- Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report.
 Rishi Shah, Yuqian
            Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta,
            Rachel Schlossman, Marika Murphy, Justin Hart, Luis
            Sentis, and Peter Stone.
 In AAAI Fall Symposium on Artificial Intelligence
            and Human-Robot Interaction for Service Robots in Human Environments (AI-HRI 2019), November 2019.
 Details
                  
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               (4.5MB
               )
- Agents teaching agents: a survey on inter-agent transfer learning.
 Felipe Leno
            Da Silva, Garrett Warnell, Anna
            Helena Reali Costa, and Peter Stone.
 Autonomous Agents and Multi-Agent
            Systems, Dec 2019.
 Official version from JAAMAS
 Details
                  
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               (572.4kB
               )
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
 Felipe
            Leno Da Silva, Anna Helena Reali Costa, and Peter
            Stone.
 In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
 Details
                  
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            Download: 
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               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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            Download: 
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
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- Desiderata for Planning Systems in General-Purpose Service Robots.
 Nick Walker,
            Yuqian Jiang, Maya Cakmak, and
            Peter Stone.
 In Proceedings of the ICAPS Workshop on Planning and Robotics
            (PlanRob 2019), July 2019.
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               (651.5kB
               )
- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
 Harel
            Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
            Stone, and Raymond Mooney.
 In International Conference on Social
            Robotics (ICSR), pp. 133–143, November 2019.
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               (958.6kB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
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               )
- Automatic Curriculum Graph Generation for Reinforcement Learning Agents.
 Maxwell Svetlik, Matteo
            Leonetti, Jivko Sinapov, Rishi Shah, Nick
            Walker, and Peter Stone.
 In Proceedings of the 31st AAAI Conference
            on Artificial Intelligence (AAAI), February 2017.
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               (2.0MB
               )
- Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing.
 Samuel
            Barrett, Katie Genter, Todd Hester,
            Piyush Khandelwal, Michael
            Quinlan, Peter Stone, and Mohan
            Sridharan.
 Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI
            Laboratory, 2012.
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               )
                [ps]
               (32.8MB
               )
- Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the Twenty Eighth
            International Conference on Machine Learning (ICML), 2011.
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               )
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               (521.1kB
               )
- Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker.
 Matthew
            Hausknecht and Peter Stone.
 In Javier
            Ruiz-del-Solar, Eric Chown, and Paul G. Plöger, editors, RoboCup-2010: Robot Soccer World Cup XIV, Lecture
            Notes in Artificial Intelligence, pp. 254–65, Springer Verlag, Berlin, 2011.
 Video and source code available at
            http://www.cs.utexas.edu/~AustinVilla/?p=research/aibo_kick
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               )
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               (2.8MB
               )
- A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations.
 David
            Pardoe and Peter Stone.
 In Proceedings of the 10th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
 Details
                  
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               (313.6kB
               )
                [ps]
               (280.8kB
               )
- An Introduction to Inter-task Transfer for Reinforcement Learning.
 Matthew
            E. Taylor and Peter Stone.
 AI Magazine, 32(1):15–34,
            2011.
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               (237.0kB
               )
                [ps]
               (773.0kB
               )
- On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer.
 Daniel
            Urieli, Patrick MacAlpine, Shivaram
            Kalyanakrishnan, Yinon Bentor, and Peter
            Stone.
 In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), pp. 769–776, IFAAMAS,
            May 2011.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2010/html/skilloptimization2010.html
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               )
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               )
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               )
- Motion Planning Algorithms for Autonomous Intersection Management.
 Tsz-Chiu
            Au and Peter Stone.
 In AAAI 2010 Workshop on Bridging The Gap Between
            Task And Motion Planning (BTAMP), 2010.
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               (417.4kB
               )
                [ps]
               (2.0MB
               )
- Controlled Kicking under Uncertainty.
 Samuel Barrett, Katie
            Genter, Todd Hester, Michael
            Quinlan, and Peter Stone.
 In The Fifth Workshop on Humanoid Soccer
            Robots at Humanoids 2010, December 2010.
 Details
                  
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               (357.3kB
               )
                [ps]
               (17.7MB
               )
- Transfer Learning for Reinforcement Learning on a Physical Robot.
 Samuel
            Barrett, Matt E. Taylor, and Peter
            Stone.
 In Ninth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents
            Workshop (AAMAS - ALA), May 2010.
 AAMAS ALA 2010
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               )
- Convergence, Targeted Optimality and Safety in Multiagent Learning.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the Twenty-seventh
            International Conference on Machine Learning (ICML), June 2010.
 Details
                  
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               (196.9kB
               )
                [ps]
               (474.1kB
               )
- Real Time Targeted Exploration in Large Domains.
 Todd Hester and Peter Stone.
 In The Ninth International Conference on Development and Learning
            (ICDL), August 2010.
 ICDL 2010
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               (253.9kB
               )
                [ps]
               (554.1kB
               )
- Gaussian processes for sample efficient reinforcement learning with RMAX-like exploration.
 Tobias
            Jung and Peter Stone.
 In The European Conference on Machine Learning
            (ECML), September 2010.
 Details
                  
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               (417.0kB
               )
                [ps]
               (6.5MB
               )
                [slides.pdf]
               (505.6kB
               )
- Learning Complementary Multiagent Behaviors: A Case Study.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 In Jacky Baltes, Michail G. Lagoudakis,
            Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot Soccer World Cup XIII, pp. 153–165, Springer
            Verlag, 2010.
 BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
 Some simulations
            referenced in the paper.
 Details
                  
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               )
                [ps]
               (1.4MB
               )
- Three Humanoid Soccer Platforms: Comparison and Synthesis.
 Shivaram
            Kalyanakrishnan, Todd Hester, Michael
            Quinlan, Yinon Bentor, and Peter
            Stone.
 In Jacky Baltes, Michail G. Lagoudakis, Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot
            Soccer World Cup XIII, pp. 140–152, Springer Verlag, 2010.
 Details
                  
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               (379.0kB
               )
                [ps]
               (5.3MB
               )
- Efficient Selection of Multiple Bandit Arms: Theory and Practice.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 In Proceedings of the Twenty-seventh
            International Conference on Machine Learning (ICML), 2010.
 Details
                  
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               (257.1kB
               )
                [ps]
               (679.3kB
               )
- Vision Calibration and Processing on a Humanoid Soccer Robot.
 Piyush
            Khandelwal, Matthew Hausknecht, Juhyun
            Lee, Aibo Tian, and Peter Stone.
 In
            The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
 Details
                  
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               (402.6kB
               )
                [ps]
               (14.8MB
               )
- Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning.
 W. Bradley
            Knox and Peter Stone.
 In Proc. of 9th Int. Conf. on Autonomous Agents
            and Multiagent Systems (AAMAS 2010), May 2010.
 Winner of the Pragnesh Jay Modi BEST STUDENT PAPER AWARD (and
            best paper award nominee).
 The TAMER project page with videos
            of TAMER in action.
 AAMAS-2010
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               (422.9kB
               )
                [ps]
               (3.5MB
               )
- Boosting for Regression Transfer.
 David Pardoe and Peter
            Stone.
 In Proceedings of the 27th International Conference on Machine Learning (ICML), June 2010.
 Some
            of the data used in the experiments.
 Details
                  
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               )
                [ps]
               (1.7MB
               )
- TacTex09: A Champion Bidding Agent for Ad Auctions.
 David Pardoe,
            Doran Chakraborty, and Peter
            Stone.
 In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010),
            May 2010.
 Details
                  
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               (564.3kB
               )
                [ps]
               (1.0MB
               )
- MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training.
 Adam
            Setapen, Michael Quinlan, and Peter
            Stone.
 In Ninth International Conference on Autonomous Agents and Multiagent Systems - Agents Learning Interactively
            from Human Teachers Workshop (AAMAS - ALIHT), May 2010.
 supplemental
            video cited in the paper.
 Details
                  
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               (533.2kB
               )
                [ps]
               (9.7MB
               )
- Ad Hoc Autonomous Agent Teams:  Collaboration without Pre-Coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, and Jeffrey S. Rosenschein .
 In Proceedings of the Twenty-Fourth
            Conference on Artificial Intelligence, July 2010.
 AAAI
            2010
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               )
                [ps]
               (266.6kB
               )
                [slides.pdf]
               (8.1MB
               )
- To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams.
 Peter
            Stone and Sarit Kraus.
 In The Ninth International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), International Foundation for Autonomous Agents and Multiagent Systems, May 2010.
 supplemental material cited in the paper,
            including a proof and an algorithm.
 AAMAS 2010
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               )
                [ps]
               (285.3kB
               )
- Improving Particle Filter Performance Using SSE Instructions.
 Peter
            Djeu, Michael Quinlan, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
            2009.
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               (176.8kB
               )
                [ps]
               (2.7MB
               )
- A Task Specification Language for Bootstrap Learning.
 Ian
            Fasel, Michael Quinlan, and Peter
            Stone.
 In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.
 AAAI
            Spring 2009 Symposium: Agents that Learn from Human Teachers
 Details
                  
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               )
                [ps]
               (1.9MB
               )
- Generalized Model Learning for Reinforcement Learning in Factored Domains.
 Todd
            Hester and Peter Stone.
 In The Eighth International Conference on
            Autonomous Agents and Multiagent Systems (AAMAS), May 2009.
 AAMAS
            2009
 Details
                  
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               (181.5kB
               )
                [ps]
               (425.5kB
               )
- An Empirical Comparison of Abstraction in Models of Markov Decision Processes.
 Todd
            Hester and Peter Stone.
 In Proceedings of the ICML/UAI/COLT Workshop
            on Abstraction in Reinforcement Learning, June 2009.
 ICML ARL 2009
 Details
                  
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               (127.0kB
               )
                [ps]
               (363.0kB
               )
- Compositional Models for Reinforcement Learning.
 Nicholas
            K. Jong and Peter Stone.
 In The European Conference on Machine Learning
            and Principles and Practice of Knowledge Discovery in Databases, September 2009.
 Details
                  
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               (173.0kB
               )
                [ps]
               (431.7kB
               )
- Feature Selection for Value Function Approximation Using Bayesian Model Selection.
 Tobias
            Jung and Peter Stone.
 In The European Conference on Machine Learning
            and Principles and Practice of Knowledge Discovery in Databases, September 2009.
 Details
                  
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               (746.9kB
               )
                [ps]
               (2.3MB
               )
                [slides.pdf]
               (957.5kB
               )
- Connectivity-based Localization in Robot Networks.
 Tobias Jung,
            Mazda Ahmadi, and Peter
            Stone.
 In International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09), June 2009.
 Details
                  
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               (176.8kB
               )
                [ps]
               (514.7kB
               )
- An Empirical Analysis of Value Function-Based and Policy Search Reinforcement Learning.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 In The Eighth International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), pp. 749–756, International Foundation for Autonomous Agents
            and Multiagent Systems, May 2009.
 AAMAS 2009
 Details
                  
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               (366.4kB
               )
                [ps]
               (1.7MB
               )
- The UT Austin Villa 3D Simulation Soccer Team 2008.
 Shivaram Kalyanakrishnan,
            Yinon Bentor, and Peter Stone.
 Technical
            Report AI09-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2009.
 Details
                  
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               (292.6kB
               )
                [ps]
               (983.9kB
               )
- Interactively Shaping Agents via Human Reinforcement: The TAMER Framework.
 W. Bradley
            Knox and Peter Stone.
 In The Fifth International Conference on Knowledge
            Capture, September 2009.
 The TAMER project page with
            videos of TAMER in action.
 K-CAP
            2009
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               (540.2kB
               )
                [ps]
               (3.7MB
               )
- Design Principles for Creating Human-Shapable Agents.
 W. Bradley Knox,
            Ian Fasel, and Peter
            Stone.
 In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.
 AAAI
            Spring 2009 Symposium: Agents that Learn from Human Teachers
 Details
                  
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               (400.8kB
               )
                [ps]
               (2.1MB
               )
- Transfer Learning for Reinforcement Learning Domains: A Survey.
 Matthew
            E. Taylor and Peter Stone.
 Journal of Machine Learning Research,
            10(1):1633–1685, 2009.
 Official	version
            from journal website.
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               (399.8kB
               )
                [ps]
               (579.4kB
               )
- Hierarchical Model-Based Reinforcement Learning: Rmax + MAXQ.
 Nicholas
            K. Jong and Peter Stone.
 In Proceedings of the Twenty-Fifth
            International Conference on Machine Learning, July 2008.
 ICML 2008
 Details
                  
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               (157.5kB
               )
                [ps]
               (370.2kB
               )
- The Utility of Temporal Abstraction in Reinforcement Learning.
 Nicholas
            K. Jong, Todd Hester, and Peter
            Stone.
 In The Seventh International Joint Conference on Autonomous Agents and  Multiagent Systems, May 2008.
 AAMAS-2008
 Details
                  
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               (136.4kB
               )
                [ps]
               (325.7kB
               )
- Model-based Reinforcement Learning in a Complex Domain.
 Shivaram
            Kalyanakrishnan, Peter Stone, and Yaxin
            Liu.
 In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World
            Cup XI, Lecture Notes in Artificial Intelligence, pp. 171–83, Springer Verlag, Berlin, 2008.
 Details
                  
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               (200.9kB
               )
                [ps]
               (515.0kB
               )
- TAMER: Training an Agent Manually via Evaluative Reinforcement.
 W. Bradley
            Knox and Peter Stone.
 In IEEE 7th International Conference on Development
            and Learning, August 2008.
 ICDL-2008
 Also available in IEEE
            Xplore, 9-12 Aug. 2008 Pages:292 - 297
 Details
                  
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               (1.1MB
               )
                [ps]
               (12.8MB
               )
- Online Kernel Selection for Bayesian Reinforcement Learning.
 Joseph
            Reisinger, Peter Stone, and Risto
            Miikkulainen.
 In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
 ICML 2008
 Details
                  
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               (434.0kB
               )
                [ps]
               (1.7MB
               )
- Transferring Instances for Model-Based Reinforcement Learning.
 Matthew E. Taylor,
            Nicholas K. Jong, and Peter
            Stone.
 In Machine Learning and Knowledge Discovery in Databases, pp. 488–505, September 2008.
 Official
            version from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (304.9kB
               )
                [ps]
               (860.1kB
               )
- Autonomous Transfer for Reinforcement Learning.
 Matthew E. Taylor,
            Gregory Kuhlmann, and Peter
            Stone.
 In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
 AAMAS-2008
 Details
                  
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               (233.3kB
               )
                [ps]
               (391.7kB
               )
- Transfer Learning and Intelligence: an Argument and Approach.
 Matthew E. Taylor,
            Gregory Kuhlmann, and Peter
            Stone.
 In Proceedings of the First Conference on Artificial General Intelligence, March 2008.
 AGI-2008
 Google
            video version of the conference presentation.
 Details
                  
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               (149.0kB
               )
                [ps]
               (202.5kB
               )
- IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks.
 Mazda
            Ahmadi, Matthew E. Taylor, and Peter
            Stone.
 In The Sixth International Joint Conference on Autonomous Agents and  Multiagent Systems, May 2007.
 BEST PAPER AWARD NOMINEE.
 AAMAS-2007
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               (261.6kB
               )
                [ps]
               (1.0MB
               )
- General Game Learning using Knowledge Transfer.
 Bikramjit Banerjee
            and Peter Stone.
 In The 20th International Joint Conference on Artificial
            Intelligence, pp. 672–677, January 2007.
 IJCAI-07
 Details
                  
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               (118.1kB
               )
                [ps]
               (198.5kB
               )
- The Chin Pinch:  A Case Study in Skill Learning on a Legged Robot.
 Peggy
            Fidelman and Peter Stone.
 In Gerhard Lakemeyer, Elizabeth
            Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
            in Artificial Intelligence, pp. 59–71, Springer Verlag, Berlin, 2007.
 Some videos
            referenced in the paper.
 Details
                  
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               (186.9kB
               )
                [ps]
               (1.6MB
               )
- Model-Based Function Approximation for Reinforcement Learning.
 Nicholas
            K. Jong and Peter Stone.
 In The Sixth International Joint Conference
            on Autonomous Agents and  Multiagent Systems, May 2007.
 Details
                  
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               (321.1kB
               )
                [ps]
               (1.0MB
               )
- Model-Based Exploration in Continuous State Spaces.
 Nicholas
            K. Jong and Peter Stone.
 In The Seventh Symposium on Abstraction,
            Reformulation, and Approximation, July 2007.
 Details
                  
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               (324.3kB
               )
                [ps]
               (1.1MB
               )
- Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study.
 Shivaram
            Kalyanakrishnan, Yaxin Liu, and Peter
            Stone.
 In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
            Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
            72–85, Springer Verlag, Berlin, 2007.
 BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
 Some simulations referenced in the paper.
 Details
                  
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               (992.2kB
               )
                [ps]
               (1.6MB
               )
- Batch Reinforcement Learning in a Complex Domain.
 Shivaram Kalyanakrishnan
            and Peter Stone.
 In The Sixth International Joint Conference on Autonomous
            Agents and  Multiagent Systems, pp. 650–657, ACM, New York, NY, USA, May 2007.
 BEST PAPER AWARD NOMINEE.
 AAMAS-2007
 Details
                  
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               (186.4kB
               )
                [ps]
               (384.8kB
               )
- The UT Austin Villa 3D Simulation Soccer Team 2007.
 Shivaram Kalyanakrishnan
            and Peter Stone.
 Technical Report AI-07-348, The University of Texas at
            Austin, Department of Computer Sciences, AI Laboratory, 2007.
 Supplementary resources at the UT
            Austin Villa 3D Simulation page.
 Details
                  
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               (273.4kB
               )
                [ps]
               (5.7MB
               )
- Graph-Based Domain Mapping for Transfer Learning in General Games.
 Gregory
            Kuhlmann and Peter Stone.
 In Proceedings of The Eighteenth European
            Conference on Machine Learning, September 2007.
 Details
                  
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               (377.0kB
               )
                [ps]
               (601.6kB
               )
- Autonomous Learning of Stable Quadruped Locomotion.
 Manish
            Saggar, Thomas D'Silva, Nate Kohl, and Peter
            Stone.
 In Gerhard Lakemeyer, Elizabeth Sklar, Domenico Sorenti, and
            Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes in Artificial Intelligence, pp.
            98–109, Springer Verlag, Berlin, 2007.
 BEST PAPER AWARD NOMINEE at RoboCup International Symposium.
 Some videos referenced in the paper.
 Details
                  
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               (1.1MB
               )
                [ps]
               (26.8MB
               )
- Intelligent Autonomous Robotics:  A Robot Soccer Case Study,
 Peter
            Stone.
 Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan \& Claypool Publishers, 2007.
 Available from Synthesis page.
 ISBN: 9781598291262
 Details
                  
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- Learning and Multiagent Reasoning for Autonomous Agents.
 Peter Stone.
 In
            The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
 IJCAI-07
 Details
                  
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               (308.5kB
               )
                [ps]
               (379.3kB
               )
- Selective Visual Attention for Object Detection on a Legged Robot.
 Daniel
            Stronger and Peter Stone.
 In Gerhard Lakemeyer, Elizabeth
            Sklar, Domenico Sorenti, and Tomoichi Takahashi, editors, RoboCup-2006: Robot Soccer World Cup X, Lecture Notes
            in Artificial Intelligence, pp. 158–170, Springer Verlag, Berlin, 2007.
 Some videos
            referenced in the paper.
 Details
                  
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               (159.7kB
               )
                [ps]
               (342.4kB
               )
- Transfer Learning via Inter-Task Mappings for Temporal Difference Learning.
 Matthew
            E. Taylor, Peter Stone, and Yaxin
            Liu.
 Journal of Machine Learning Research, 8(1):2125–2167, 2007.
 Available from journal's
            web page.
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               )
- Temporal Difference and Policy Search Methods for         Reinforcement Learning: An Empirical Comparison.
 Matthew
            E. Taylor, Shimon Whiteson, and Peter
            Stone.
 In Proceedings of the Twenty-Second          Conference on Artificial Intelligence, pp. 1675–1678,
            July 2007. Nectar Track
 AAAI         2007
 Details
                  
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               (190.4kB
               )
- Cross-Domain Transfer for Reinforcement Learning.
 Matthew E. Taylor
            and Peter Stone.
 In Proceedings of the Twenty-Fourth International  
                   Conference on Machine Learning, June 2007.
 ICML   
                  2007
 Details
                  
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               )
- Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning.
 Matthew
            E. Taylor, Shimon Whiteson, and Peter
            Stone.
 In The Sixth International Joint Conference on Autonomous Agents and  Multiagent Systems, May 2007.
 AAMAS-2007
 Details
                  
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               )
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               (525.2kB
               )
- Representation Transfer for Reinforcement Learning.
 Matthew E. Taylor
            and Peter Stone.
 In AAAI 2007 Fall Symposium on Computational       
            Approaches to Representation Change during Learning and        Development, November 2007.
 2007
                   AAAI Fall Symposium: Computational Approaches to        Representation Change during Learning and Development
 Details
                  
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               (375.1kB
               )
- Accelerating Search with Transferred Heuristics.
 Matthew E. Taylor,
            Gregory Kuhlmann, and Peter
            Stone.
 In ICAPS-07 workshop on AI Planning and Learning, September 2007.
 ICAPS
            2007 workshop on AI Planning and Learning
 Details
                  
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               )
                [ps]
               (215.4kB
               )
- Empirical Studies in Action Selection for Reinforcement Learning.
 Shimon
            Whiteson, Matthew E. Taylor, and Peter
            Stone.
 Adaptive Behavior, 15(1):33–50, March 2007.
 Details
                  
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               )
                [ps]
               (1.5MB
               )
- Adaptive Tile Coding for Value Function Approximation.
 Shimon
            Whiteson, Matthew E. Taylor, and Peter
            Stone.
 Technical Report AI-TR-07-339, University of Texas at Austin, 2007.
 Details
                  
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               (329.4kB
               )
                [ps]
               (942.5kB
               )
- Value Function Transfer for General Game Playing.
 Bikramjit Banerjee,
            Gregory Kuhlmann, and Peter
            Stone.
 In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.
 ICML
            2006 workshop on Structural Knowledge Transfer for Machine Learning
 Details
                  
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               (172.9kB
               )
                [ps]
               (464.0kB
               )
- Automatic Heuristic Construction in a Complete General Game Player.
 Gregory
            Kuhlmann, Kurt Dresner, and Peter
            Stone.
 In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1457–62,
            July 2006.
 AAAI 2006
 Details
                  
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               (124.1kB
               )
                [ps]
               (156.2kB
               )
- Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping.
 Yaxin
            Liu and Peter Stone.
 In Proceedings of the Twenty-First National
            Conference on Artificial Intelligence, pp. 415–20, July 2006.
 AAAI
            2006
 Details
                  
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               (151.7kB
               )
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               (1.6MB
               )
- From Pixels to Multi-Robot Decision-Making:  A Study in Uncertainty.
 Peter
            Stone, Mohan Sridharan, Daniel
            Stronger, Gregory Kuhlmann, Nate Kohl,
            Peggy Fidelman, and Nicholas
            K. Jong.
 Robotics and Autonomous Systems , 54(11):933–43, November 2006. Special issue on Planning
            Under Uncertainty in Robotics.
 Official versionfrom the RAS
            publisher's webpage.
 Details
                  
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               )
                [ps]
               (3.6MB
               )
- Keepaway Soccer:  From Machine Learning Testbed to Benchmark.
 Peter Stone,
            Gregory Kuhlmann, Matthew E. Taylor,
            and Yaxin Liu.
 In Itsuki
            Noda, Adam Jacoff, Ansgar Bredenfeld, and Yasutake Takahashi, editors, RoboCup-2005: Robot Soccer World Cup IX,
            pp. 93–105, Springer Verlag, Berlin, 2006.
 Some simulations
            of keepaway referenced in the paper and keepaway software.
 Official version from Publisher's
            Webpage© Springer-Verlag
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               )
                [ps]
               (2.3MB
               )
- Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot.
 Daniel
            Stronger and Peter Stone.
 Connection Science, 18(2):97–119,
            2006. Special Issue on Developmental Robotics.
 Connection
            Science Journal. Contains material that was previously published in an ICRA-2005
            paper.
 Details
                  
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               )
                [ps]
               (1.4MB
               )
- Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning.
 Matthew
            Taylor, Shimon Whiteson, and Peter
            Stone.
 In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1321–28, July 2006.
 BEST PAPER AWARD at GECCO 2006
 Details
                  
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               )
                [ps]
               (562.2kB
               )
- State Abstraction Discovery from Irrelevant State Variables.
 Nicholas
            K. Jong and Peter Stone.
 In Proceedings of the Nineteenth International
            Joint Conference on Artificial Intelligence, pp. 752–757, August 2005.
 Details
                  
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               (102.1kB
               )
                [ps]
               (249.8kB
               )
                [slides.pdf]
               (323.4kB
               )
- Bayesian Models of Nonstationary Markov Decision Problems.
 Nicholas
            K. Jong and Peter Stone.
 In IJCAI 2005 workshop on Planning
            and Learning in A Priori Unknown or Dynamic Domains, August 2005.
 Workshop
            webpage.
 Details
                  
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               (42.4kB
               )
- Improving Action Selection in MDP's via Knowledge Transfer.
 Alexander
            A. Sherstov and Peter Stone.
 In Proceedings of the Twentieth
            National Conference on Artificial Intelligence, July 2005.
 AAAI
            2005
 Details
                  
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               (205.5kB
               )
                [ps]
               (774.2kB
               )
- Real-Time Vision on a Mobile Robot Platform.
 Mohan Sridharan and Peter Stone.
 In IEEE/RSJ International Conference on Intelligent Robots
            and Systems (IROS), August 2005.
 Some videos
            of the robot referenced in the paper.
 IROS-2005
 Details
                  
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               (396.1kB
               )
                [ps]
               (5.0MB
               )
- Practical Vision-Based Monte Carlo Localization on a Legged Robot.
 Mohan
            Sridharan, Gregory Kuhlmann, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation, April 2005.
 ICRA
            2005
 Details
                  
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               (217.6kB
               )
                [ps]
               (2.0MB
               )
                [slides.pdf]
               (2.5MB
               )
- Value Functions for RL-Based Behavior Transfer: A Comparative Study.
 Matthew
            E. Taylor, Peter Stone, and Yaxin
            Liu.
 In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
 AAAI
            2005
 Details
                  
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               (147.3kB
               )
                [ps]
               (449.9kB
               )
- Behavior Transfer for Value-Function-Based Reinforcement Learning.
 Matthew
            E. Taylor and Peter Stone.
 In The Fourth International Joint
            Conference on Autonomous Agents and  Multiagent Systems, pp. 53–59, ACM Press, New York, NY, July 2005.
 AAMAS-2005
 Details
                  
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               )
                [ps]
               (620.1kB
               )
FHWA
      
      
         - Task Phasing: Automated Curriculum Learning from Demonstrations.
 Vaibhav Bajaj, Guni
            Sharon, and Peter Stone.
 In Proceedings of the 33rd International
            Conference on Automated Planning and Scheduling (ICAPS 2023), July 2023.
 Accompanying code
 Details
                  
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               )
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
 Haresh
            Karnan, Elvin Yang, Daniel Farkash, Garrett
            Warnell, Joydeep Biswas, and Peter
            Stone.
 In The Conference on Robot Learning (CoRL), November 2023.
 Poster,
            Video, Project Website
 Details
                  
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               (25.7MB
               )
- Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning.
 Bo
            Liu, Yihao Feng, Qiang Liu, and Peter Stone.
 In Thirty-Seventh AAAI
            Conference on Artificial Intelligence (AAAI), Februray 2023.
 Details
                  
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               (1.8MB
               )
- Model-Based Meta Automatic Curriculum Learning.
 Zifan Xu, Yulin
            Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian
            Jiang, Bo Liu, and Peter Stone.
 In
            The Second Conference on Lifelong Learning Agents (CoLLAs), August 2023.
 Video
            presentation
 Details
                  
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               (1.0MB
               )
                [slides.pptx]
               (6.6MB
               )
- Benchmarking Reinforcement Learning Techniques for Autonomous Navigation.
 Zifan
            Xu, Bo Liu, Xuesu Xiao, Anirudh
            Nair, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 Details
                  
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               (4.8MB
               )
- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
 Haresh
            Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 In
            International Conference on Intelligent Robots and Systems, 2022, October 2022.
 Details
                  
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               (3.0MB
               )
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
 Haresh
            Karnan, Garrett Warnell, Xuesu
            Xiao, and Peter Stone.
 In International Conference on Robotics and
            Automation, 2022, May 2022.
 Poster,
            Video
 Details
                  
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               (1.5MB
               )
- Adversarial Imitation Learning from Video using a State Observer.
 Haresh
            Karnan, Garrett Warnell, Faraz
            Torabi, and Peter Stone.
 In International Conference on Robotics
            and Automation, 2022, May 2022.
 Video
 Details
                  
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               (933.2kB
               )
- Effective Mutation Rate Adaptation through Group Elite Selection.
 Akarsh Kumar, Bo
            Liu, Risto Miikkulainen, and Peter
            Stone.
 In Proceedings of the Genetic and Evolutionary Computation Conference, July 2022.
 Details
                  
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               (9.7MB
               )
- Continual Learning and Private Unlearning.
 Bo Liu, Qiang Liu, and Peter Stone.
 In Proceedings of the 1st Conference on Lifelong Learning Agents
            (CoLLA), August 2022.
 Details
                  
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               (440.4kB
               )
                [slides.pdf]
               (710.5kB
               )
- Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings.
 Kingsley Nweye, Bo
            Liu, Nagy Zoltan, and Peter Stone.
 Journal of Energy and AI, 2022,
            September 2022.
 Details
                  
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               (5.9MB
               )
- A Rule-based Shield: Accumulating Safety Rules from Catastrophic Action Effects.
 Shahaf Shperberg, Bo
            Liu, Allessandro Allievi, and Peter Stone.
 In Proceedings of the
            1st Conference on Lifelong Learning Agents (CoLLA), August 2022.
 Details
                  
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               (8.9MB
               )
- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
 Josiah
            P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
            Warnell, and Peter Stone.
 Special Issue on Reinforcement Learning
            for Real Life, Machine Learning, 2021, May 2021.
 Details
                  
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               (3.0MB
               )
- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
 Zizhao
            Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
            Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
 In Proceedings
            of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
 1-minute
            Video Summary;   15-minute Video Presentation
 Details
                  
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               (2.9MB
               )
                [slides.pdf]
               (2.7MB
               )
- APPLI: Adaptive Planner Parameter Learning From Interventions.
 Zizhao Wang,
            Xuesu Xiao, Bo Liu, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
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               (4.2MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Intrinsically motivated model learning for developing curious robots.
 Todd
            Hester and Peter Stone.
 Artificial Intelligence, 247:170–86,
            June 2017.
 from journal website.
 Details
                  
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               (1.4MB
               )
- Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance.
 W. Bradley Knox and Peter Stone.
 Artificial
            Intelligence, 225(), August 2015.
 Artificial
            Intelligence
 Contains material that was previously published in a IUI 2013 paper and a RoMan 2012 paper that was nominated as a CoTeSys Cognitive Robotics BEST PAPER AWARD FINALIST.
 Details
                  
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               (3.9MB
               )
- The 2012 UT Austin Villa Code Release.
 Samuel Barrett, Katie
            Genter, Yuchen He, Todd
            Hester, Piyush Khandelwal, Jacob
            Menashe, and Peter Stone.
 In RoboCup-2013: Robot Soccer World Cup
            XVII, Springer Verlag, 2013.
 Details
                  
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               (376.3kB
               )
                [ps]
               (2.1MB
               )
- UT Austin Villa 2012: Standard Platform League World Champions.
 Samuel
            Barrett, Katie Genter, Yuchen
            He, Todd Hester, Piyush Khandelwal,
            Jacob Menashe, and Peter Stone.
 In
            Xiaoping Chen, Peter
            Stone, Luis Enrique Sucar, and Tijn
            Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2013.
 Details
                  
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               (740.4kB
               )
                [ps]
               (15.0MB
               )
- Teamwork with Limited Knowledge of Teammates.
 Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld.
 In Proceedings of the Twenty-Seventh AAAI Conference on
            Artificial Intelligence, July 2013.
 Details
                  
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               (190.1kB
               )
                [ps]
               (2.0MB
               )
- Auction-based autonomous intersection management.
 Dustin Carlino,
            Stephen D. Boyles, and Peter
            Stone.
 In Proceedings of the 16th IEEE Intelligent Transportation Systems Conference (ITSC), October 2013.
 Details
                  
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               (318.1kB
               )
                [ps]
               (1.4MB
               )
- Multiagent Learning in the Presence of Memory-Bounded Agents.
 Doran
            Chakraborty and Peter Stone.
 Autonomous Agents and Multiagent Systems
            (JAAMAS), Springer, 2013.
 Details
                  
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               (676.7kB
               )
                [ps]
               (447.9kB
               )
- Cooperating with a Markovian Ad Hoc Teammate.
 Doran
            Chakraborty and Peter Stone.
 In Proceedings of the 12th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
 Details
                  
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               (202.3kB
               )
                [ps]
               (408.2kB
               )
- Targeted Opponent Modeling of Memory-Bounded Agents.
 Doran
            Chakraborty, Noa Agmon, and Peter
            Stone.
 In Proceedings of the Adaptive Learning Agents Workshop (ALA), May 2013.
 Details
                  
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               (629.0kB
               )
                [ps]
               (1.6MB
               )
- Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back.
 Alon
            Farchy, Samuel Barrett, Patrick
            MacAlpine, and Peter Stone.
 In Proc. of 12th Int. Conf. on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2013.
 The videos referenced in the paper: original
            and optimized.
 Details
                  
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               (486.2kB
               )
                [ps]
               (36.5MB
               )
- Ad Hoc Teamwork for Leading a Flock.
 Katie Genter, Noa
            Agmon, and Peter Stone.
 In Proceedings of the 12th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), May 2013.
 Details
                  
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               (246.7kB
               )
                [ps]
               (563.3kB
               )
                [slides.pdf]
               (28.3MB
               )
- Improving Efficiency of Leading a Flock in Ad Hoc Teamwork Settings.
 Katie
            Genter, Noa Agmon, and Peter Stone.
 In
            AAMAS Autonomous Robots and Multirobot Systems (ARMS) Workshop, May 2013.
 Details
                  
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               (179.8kB
               )
                [ps]
               (413.8kB
               )
                [slides.pdf]
               (13.0MB
               )
- TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots.
 Todd
            Hester and Peter Stone.
 Machine Learning, 90(3):385–429,
            2013.
 Official version
            from journal website.
 Details
                  
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               (987.8kB
               )
                [ps]
               (3.2MB
               )
- UT Austin Villa: RoboCup 2012 3D Simulation League Champion.
 Patrick
            MacAlpine, Nick Collins, Adrian
            Lopez-Mobilia, and Peter Stone.
 In Xiaoping
            Chen, Peter Stone, Luis Enrique
            Sucar, and Tijn Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup
            XVI, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.
 Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/results_3d/#highlights
 Details
                  
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               (654.8kB
               )
                [ps]
               (6.7MB
               )
- Positioning to Win: A Dynamic Role Assignment and FormationPositioning System.
 Patrick
            MacAlpine, Francisco Barrera, and Peter
            Stone.
 In Xiaoping Chen, Peter
            Stone, Luis Enrique Sucar, and Tijn
            Van der Zant, editors, RoboCup-2012: Robot Soccer World Cup XVI, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2013.
 Accompanying video at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/positioning.html
 Details
                  
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               (255.9kB
               )
                [ps]
               (722.6kB
               )
                [slides.pdf]
               (44.0MB
               )
- Simultaneous Learning and Reshaping of an Approximated Optimization Task.
 Patrick
            MacAlpine, Elad Liebman, and Peter
            Stone.
 In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
 Details
                  
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               (435.1kB
               )
                [ps]
               (2.1MB
               )
                [slides.pdf]
               (35.2MB
               )
- UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy.
 Jacob
            Menashe, Katie Genter, Samuel
            Barrett, and Peter Stone.
 In The Eighth Workshop on Humanoid Soccer
            Robots at Humanoids 2013, October 2013.
 Details
                  
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               (350.2kB
               )
                [ps]
               (24.1MB
               )
                [slides.pdf]
               (3.1MB
               )
- Leading Ad Hoc Agents in Joint Action Settings with Multiple Teammates.
 Noa
            Agmon and Peter Stone.
 In Proc. of 11th Int. Conf. on Autonomous
            Agents and Multiagent Systems (AAMAS), June 2012.
 Details
                  
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               (229.4kB
               )
                [ps]
               (757.7kB
               )
- On Coordination in Practical Multi-Robot Patrol.
 Noa Agmon, Chien-Liang
            Fok, Yehuda Emaliah, Peter
            Stone, Christine Julien, and Sriram
            Vishwanath.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
 Details
                  
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               (412.4kB
               )
                [ps]
               (5.4MB
               )
- Evasion Planning for Autonomous Vehicles at Intersections.
 Tsz-Chiu Au,
            Chien-Liang Fok, Sriram
            Vishwanath, Christine Julien, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2012.
 Details
                  
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               (1.3MB
               )
                [ps]
               (18.7MB
               )
- Setpoint Scheduling for Autonomous Vehicle Controllers.
 Tsz-Chiu Au,
            Michael Quinlan, and Peter
            Stone.
 In Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 2012.
 Details
                  
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               (684.9kB
               )
                [ps]
               (2.7MB
               )
- Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions.
 Aijun
            Bai, Xiaoping Chen, Patrick
            MacAlpine, Daniel Urieli, Samuel
            Barrett, and Peter Stone.
 In Thomas Roefer, Norbert Michael Mayer, Jesus
            Savage, and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence,
            Springer Verlag, Berlin, 2012.
 Details
                  
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               (257.0kB
               )
                [ps]
               (829.5kB
               )
- An Analysis Framework for Ad Hoc Teamwork Tasks.
 Samuel Barrett
            and Peter Stone.
 In Proceedings of the 11th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
 Details
                  
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               (177.6kB
               )
                [ps]
               (1.1MB
               )
                [slides.pdf]
               (1.6MB
               )
- Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing.
 Samuel
            Barrett, Katie Genter, Todd Hester,
            Piyush Khandelwal, Michael
            Quinlan, Peter Stone, and Mohan
            Sridharan.
 Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI
            Laboratory, 2012.
 Details
                  
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               (1.1MB
               )
                [ps]
               (32.8MB
               )
- Approximately Orchestrated Routing and Transportation Analyzer: Large-scale Traffic Simulation for Autonomous Vehicles.
 Dustin Carlino, Mike
            Depinet, Piyush Khandelwal, and Peter
            Stone.
 In Proceedings of the 15th IEEE Intelligent Transportation Systems Conference (ITSC), September 2012.
 Details
                  
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            Download: 
            [pdf]
               (727.1kB
               )
                [ps]
               (14.3MB
               )
- Automated Intersection Control: Performance of a Future Innovation Versus Current Traffic Signal Control.
 David
            Fajardo, Tsz-Chiu Au, Travis Waller,
            Peter Stone, and David Yang.
 Transportation
            Research Record (TRR), 2259:223–32, 2012.
 Details
                  
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               (591.8kB
               )
- A Platform for Evaluating Autonomous Intersection Management Policies.
 Chien-Liang
            Fok, Maykel Hanna, Seth Gee, Tsz-Chiu
            Au, Peter Stone, Christine
            Julien, and Sriram Vishwanath.
 In Proceedings
            of the ACM/IEEE Third International Conference on Cyber-Physical Systems (ICCPS), April 2012.
 Details
                  
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               (5.7MB
               )
                [ps]
               (61.7MB
               )
- RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control.
 Todd
            Hester, Michael Quinlan, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
 Details
                  
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               (359.7kB
               )
                [ps]
               (1.9MB
               )
- PAC Subset Selection in Stochastic Multi-armed Bandits.
 Shivaram
            Kalyanakrishnan, Ambuj Tewari, Peter
            Auer, and Peter Stone.
 In Proceedings of the 29th International Conference
            on Machine Learning (ICML), pp. 655–662, Omnipress, New York, NY, USA, June-July 2012.
 Details
                  
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               (230.2kB
               )
                [ps]
               (519.5kB
               )
- A Low Cost Ground Truth Detection System Using the Kinect.
 Piyush Khandelwal
            and Peter Stone.
 In Thomas Roefer, Norbert Michael Mayer, Jesus Savage,
            and Uluc Saranli, editors, RoboCup-2011: Robot Soccer World Cup XV, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2012.
 Details
                  
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            [pdf]
               (323.7kB
               )
                [ps]
               (2.7MB
               )
- Learning from feedback on actions past and intended.
 W. Bradley Knox,
            Cynthia Breazeal, and Peter
            Stone.
 In Proceedings of 7th ACM/IEEE International Conference on Human-Robot Interaction, Late-Breaking Reports
            Session (HRI), March 2012.
 HRI 2012
 Details
                  
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               (447.6kB
               )
                [ps]
               (3.9MB
               )
- Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition.
 Patrick MacAlpine, Samuel Barrett,
            Daniel Urieli, Victor
            Vu, and Peter Stone.
 In Proceedings of the Twenty-Sixth AAAI Conference
            on Artificial Intelligence (AAAI), July 2012.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html
 Details
                  
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               (461.2kB
               )
                [ps]
               (2.0MB
               )
                [slides.pdf]
               (204.2MB
               )
- UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition.
 Patrick
            MacAlpine, Daniel Urieli, Samuel
            Barrett, Shivaram Kalyanakrishnan, Francisco
            Barrera, Adrian Lopez-Mobilia, Nicolae \cStiurc\ua,
            Victor Vu, and Peter
            Stone.
 In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
 Accompanying
            videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/components.html
 Details
                  
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               (646.3kB
               )
                [ps]
               (2.7MB
               )
                [slides.pdf]
               (135.4MB
               )
- Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk.
 Patrick
            MacAlpine and Peter Stone.
 In AAMAS Adaptive Learning Agents (ALA)
            Workshop, June 2012.
 Video available at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2012/html/holonomicwalk.html
 Details
                  
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               (525.6kB
               )
                [ps]
               (2.2MB
               )
                [slides.pdf]
               (159.5MB
               )
- Enforcing Liveness in Autonomous Traffic Management.
 Tsz-Chiu Au, Neda Shahidi, and Peter
            Stone.
 In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
 Details
                  
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            [pdf]
               (1.1MB
               )
                [ps]
               (31.7MB
               )
- Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain.
 Samuel
            Barrett, Peter Stone, and Sarit
            Kraus.
 In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
 Details
                  
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               (361.8kB
               )
                [ps]
               (11.4MB
               )
                [slides.pdf]
               (616.4kB
               )
- Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards.
 Samuel
            Barrett and Peter Stone.
 In Tenth International Conference on Autonomous
            Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
 Details
                  
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               (136.1kB
               )
                [ps]
               (384.8kB
               )
- Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker.
 Matthew
            Hausknecht and Peter Stone.
 In Javier
            Ruiz-del-Solar, Eric Chown, and Paul G. Plöger, editors, RoboCup-2010: Robot Soccer World Cup XIV, Lecture
            Notes in Artificial Intelligence, pp. 254–65, Springer Verlag, Berlin, 2011.
 Video and source code available at
            http://www.cs.utexas.edu/~AustinVilla/?p=research/aibo_kick
 Details
                  
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               (324.4kB
               )
                [ps]
               (2.8MB
               )
- Dynamic Lane Reversal in Traffic Management.
 Matthew Hausknecht,
            Tsz-Chiu Au, Peter Stone, David
            Fajardo, and Travis Waller.
 In Proceedings of IEEE Intelligent Transportation
            Systems Conference (ITSC), 2011.
 Details
                  
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            [pdf]
               (127.0kB
               )
                [ps]
               (4.3MB
               )
- Autonomous Intersection Management: Multi-Intersection Optimization.
 Matthew
            Hausknecht, Tsz-Chiu Au, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2011.
 Details
                  
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               (252.7kB
               )
                [ps]
               (1.9MB
               )
- Learning and Using Models.
 Todd Hester and Peter
            Stone.
 In Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Springer
            Verlag, Berlin, Germany, 2011.
 Details
                  
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               (474.7kB
               )
                [ps]
               (1.0MB
               )
- On Learning with Imperfect Representations.
 Shivaram Kalyanakrishnan
            and Peter Stone.
 In Proceedings of the 2011 IEEE Symposium on Adaptive
            Dynamic Programming and Reinforcement Learning, pp. 17–24, IEEE, April 2011.
 Details
                  
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               (163.8kB
               )
                [ps]
               (196.0kB
               )
- Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report.
 W. Bradley
            Knox and Peter Stone.
 In IJCAI 2011 Workshop on Agents Learning Interactively
            from Human Teachers (ALIHT), July 2011.
 IJCAI 2011 Workshop
            on Agents Learning Interactively  from Human Teachers (ALIHT)
 Details
                  
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               (372.4kB
               )
                [ps]
               (41.6MB
               )
- Comparing Agents: Success against People in Security Domains.
 Raz Lin,
            Sarit Kraus, Noa Agmon, Samuel
            Barrett, and Peter Stone.
 In Proceedings of the Twenty-Fifth AAAI
            Conference on Artificial Intelligence, August 2011.
 Details
                  
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            Download: 
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               (387.5kB
               )
- UT Austin Villa 2011 3D Simulation Team Report.
 Patrick MacAlpine,
            Daniel Urieli, Samuel Barrett,
            Shivaram Kalyanakrishnan, Francisco
            Barrera, Adrian Lopez-Mobilia, Nicolae\cStiurc\ua,
            Victor Vu, and Peter
            Stone.
 Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory,
            2011.
 Details
                  
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               (1.2MB
               )
                [ps]
               (5.3MB
               )
- A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations.
 David
            Pardoe and Peter Stone.
 In Proceedings of the 10th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
 Details
                  
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            Download: 
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               (313.6kB
               )
                [ps]
               (280.8kB
               )
- On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer.
 Daniel
            Urieli, Patrick MacAlpine, Shivaram
            Kalyanakrishnan, Yinon Bentor, and Peter
            Stone.
 In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), pp. 769–776, IFAAMAS,
            May 2011.
 Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2010/html/skilloptimization2010.html
 Details
                  
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               (530.9kB
               )
                [ps]
               (1.6MB
               )
                [slides.pptx]
               (3.8MB
               )
- Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning.
 Shimon
            Whiteson, Brian Tanner, Matthew
            E. Taylor, and Peter Stone.
 In IEEE Symposium on Adaptive Dynamic
            Programming and Reinforcement Learning (ADPRL), April 2011.
 2011
            IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL)
 Details
                  
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               (165.3kB
               )
- Generalized Model Learning for Reinforcement Learning on a Humanoid Robot.
 Todd
            Hester, Michael Quinlan, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation (ICRA), May 2010.
 Video available at
            http://www.cs.utexas.edu/~AustinVilla/?p=research/rl_kick
 Details
                  
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               (1.5MB
               )
                [ps]
               (25.3MB
               )
- Learning Complementary Multiagent Behaviors: A Case Study.
 Shivaram
            Kalyanakrishnan and Peter Stone.
 In Jacky Baltes, Michail G. Lagoudakis,
            Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot Soccer World Cup XIII, pp. 153–165, Springer
            Verlag, 2010.
 BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
 Some simulations
            referenced in the paper.
 Details
                  
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               (200.5kB
               )
                [ps]
               (1.4MB
               )
- Three Humanoid Soccer Platforms: Comparison and Synthesis.
 Shivaram
            Kalyanakrishnan, Todd Hester, Michael
            Quinlan, Yinon Bentor, and Peter
            Stone.
 In Jacky Baltes, Michail G. Lagoudakis, Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot
            Soccer World Cup XIII, pp. 140–152, Springer Verlag, 2010.
 Details
                  
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               (379.0kB
               )
                [ps]
               (5.3MB
               )
- Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning.
 W. Bradley
            Knox and Peter Stone.
 In Proc. of 9th Int. Conf. on Autonomous Agents
            and Multiagent Systems (AAMAS 2010), May 2010.
 Winner of the Pragnesh Jay Modi BEST STUDENT PAPER AWARD (and
            best paper award nominee).
 The TAMER project page with videos
            of TAMER in action.
 AAMAS-2010
 Details
                  
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               (422.9kB
               )
                [ps]
               (3.5MB
               )
- Multi-Agent Social Simulation.
 Itsuki Noda, Peter
            Stone, Tomohisa Yamashita, and Koichi Kurumatani.
 In Nakashima, H., Aghajan, H., \& Augusto, J. C., editors, Handbook
            of Ambient Intelligence and Smart Environments, pp. 703–729, Springer Verlag, 2010.
 Official version from
            publisher's webage
 Details
                  
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            Download: 
            
            (unavailable)
- Boosting for Regression Transfer.
 David Pardoe and Peter
            Stone.
 In Proceedings of the 27th International Conference on Machine Learning (ICML), June 2010.
 Some
            of the data used in the experiments.
 Details
                  
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               (600.5kB
               )
                [ps]
               (1.7MB
               )
- TacTex09: A Champion Bidding Agent for Ad Auctions.
 David Pardoe,
            Doran Chakraborty, and Peter
            Stone.
 In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010),
            May 2010.
 Details
                  
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               (564.3kB
               )
                [ps]
               (1.0MB
               )
- Bringing Simulation to Life: A Mixed Reality Autonomous Intersection.
 Michael
            Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
            2010.
 Video available at http://www.cs.utexas.edu/~aim/video/MixedReality.wmv
 Details
                  
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               (1.3MB
               )
                [ps]
               (10.6MB
               )
- The Essence of Soccer, Can Robots Play Too?.
 Peter Stone, Michael
            Quinlan, and Todd Hester.
 In Ted Richards, editors, Soccer and Philosophy:
             Beautiful Thoughts on theBeautiful Game, Popular Culture and Philosophy, pp. 75–88, Open Court Publishing Company,
            2010.
 Appears in Soccer and Philosophy (available from amazon.com)
 Details
                  
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               (121.3kB
               )
                [ps]
               (514.1kB
               )
- Ad Hoc Autonomous Agent Teams:  Collaboration without Pre-Coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, and Jeffrey S. Rosenschein .
 In Proceedings of the Twenty-Fourth
            Conference on Artificial Intelligence, July 2010.
 AAAI
            2010
 Details
                  
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               (119.0kB
               )
                [ps]
               (266.6kB
               )
                [slides.pdf]
               (8.1MB
               )
- To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams.
 Peter
            Stone and Sarit Kraus.
 In The Ninth International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), International Foundation for Autonomous Agents and Multiagent Systems, May 2010.
 supplemental material cited in the paper,
            including a proof and an algorithm.
 AAMAS 2010
 Details
                  
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               (180.6kB
               )
                [ps]
               (285.3kB
               )
- Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning.
 Shimon Whiteson, Matthew
            E. Taylor, and Peter Stone.
 Journal of Autonomous Agents and
            Multi-Agent Systems, 21(1):1–27, 2010.
 Details
                  
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               (760.6kB
               )
                [ps]
               (1.9MB
               )
- Improving Particle Filter Performance Using SSE Instructions.
 Peter
            Djeu, Michael Quinlan, and Peter
            Stone.
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October
            2009.
 Details
                  
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               (176.8kB
               )
                [ps]
               (2.7MB
               )
- A Multiagent Approach to Autonomous Intersection Management.
 Kurt
            Dresner and Peter Stone.
 Journal of Artificial Intelligence Research,
            31:591–656, March 2008.
 Available from journal's
            web page.
 Further details and videos are on the project page.
 Details
                  
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               (1.3MB
               )
                [ps]
               (2.2MB
               )
TXDOT
      
      
         - Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond J. Mooney.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, February 2020.
 Details
                  
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               (4.0MB
               )
- Selecting Compliant Agents for Opt-in Micro-Tolling.
 Josiah Hanna,
            Guni Sharon, Stephen
            Boyles, and Peter Stone.
 In Proceedings of the 33rd AAAI Conference
            on Artificial Intelligence (AAAI), January 2019.
 Details
                  
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               (2.2MB
               )
- Improving Grounded Natural Language Understanding through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond Mooney.
 In Proceedings of the International Conference on
            Robotics and Automation (ICRA 2019), May 2019.
 Details
                  
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            [pdf]
               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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            [pdf]
               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
 Haipeng
            Chen, Bo An, Guni Sharon, Josiah
            P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
 In Proceedings
            of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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               (2.4MB
               )
                [ps]
               (5.9MB
               )
- PRISM:  Pose  Registration  for  Integrated  Semantic  Mapping.
 Justin W. Hart,
            Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter
            Stone.
 In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
            October 2018.
 Details
                  
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            [pdf]
               (4.4MB
               )
- Bringing Smart Transport to Texans:  Ensuring the Benefits of a	Connected and Autonomous Transport System in Texas ---
            Final Report.
 Kara Kockelman, Stephen Boyles, Purser
            Sturgeon, Christian Claudel, Lisa Loftus-Otway, Wendy Wagner, Duncan Stewart, Guni
            Sharon, Michael Albert, Peter
            Stone, Josiah Hanna, Yantao Huang, Krishna Murthy Gurumurthy, Dongxu
            He, Abduallah Mohamed, Rahul Patel, Tian Lei, Michele Simoni, and Sadegh Yarmohammadisatri.
 Technical Report 0-6838-3,
            The University of Texas at Austin Center for Transportation Research, 2018.
 Available
            online
 Details
                  
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            Download: 
            
            (unavailable)
- Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science.
 Decebal Constantin Mocanu, Elena
            Mocanu, Peter Stone, Phuong
            H. Nguyen, Madeleine Gibescu, and Antonio
            Liotta.
 Nature Communications, 9(2383), June 2018.
 Official version from Publisher's
            Webpage.
 Details
                  
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               (1.5MB
               )
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
 Tarun
            Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
            and Peter Stone.
 Transportation Research Part B: Methodological,
            110:104–21, 2018.
 Official version from Publisher's
            Webpage
 Details
                  
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               (1.6MB
               )
- Traffic Optimization For a Mixture of Self-interested and Compliant Agents.
 Guni
            Sharon, Michael Albert, Tarun
            Rambha, Stephen Boyles, and Peter
            Stone.
 In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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            [pdf]
               (1002.7kB
               )
                [ps]
               (5.2MB
               )
                [slides.pptx]
               (11.1MB
               )
- An Assessment of Autonomous Vehicles:  Traffic Impacts and  Infrastructure Needs --- Final Report.
 Kara Kockelman,
            Stephen Boyles, Peter
            Stone, Dan Fagnant, Rahul  Patel, Michael W.
            Levin, Guni Sharon, Michele Simoni, Michael
             Albert, Hagen Fritz, Rebecca Hutchinson, Prateek Bansal, Gelb  Domnenko, Pavle Bujanovic, Bumsik Kim, Elaham Pourrahmani,
            Sudesh  Agrawal, Tianxin Li, Josiah Hanna, Aqshems Nichols, and Jia Li.
 Technical
            Report 0-6847-1, The University of Texas at Austin Center for Transportation Research, 2017.
 Available
            online
 Details
                  
               BibTeX
                  
            Download: 
            
            (unavailable)
- Iterative Human-Aware Mobile Robot Navigation.
 Shih-Yun Lo, Benito Fernandez, and Peter
            Stone.
 In Proceedings of the Human-Centered Robotics workshop of the 13th International Conference on Robotics:
            Science and System (RSS), July 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
- Network-wide Adaptive Tolling for Connected and Automated vehicles.
 Guni
            Sharon, Michael W. Levin, Josiah
            P. Hanna, Tarun Rambha, Stephen
            D. Boyles, and Peter Stone.
 Transportation Research Part C, 84:142–157,
            September 2017.
 Transportation Research Part C.
 Audio slides.
 Contains material
            that was previously published in an AAMAS-17 paper.
 Details
                  
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               (2.8MB
               )
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               (4.2MB
               )
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
 Guni
            Sharon and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
 Details
                  
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               (1.1MB
               )
                [ps]
               (7.1MB
               )
                [slides.pptx]
               (140.9MB
               )
- Minimum Cost Matching for Autonomous Carsharing.
 Josiah P. Hanna,
            Michael Albert, Donna
            Chen, and Peter Stone.
 In Proceedings of the 9th IFAC Symposium on
            Intelligent Autonomous Vehicles (IAV 2016), June 2016.
 Details
                  
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               (117.5kB
               )
                [ps]
               (355.2kB
               )
                [slides.pdf]
               (4.7MB
               )
- Bringing Smart Transport to Texans:  Ensuring the Benefits of a	Connected and Autonomous Transport System in Texas ---
            Final Report.
 Kara Kockelman, Stephen Boyles, Paul
            Avery, Christian Claudel, Lisa	Loftus-Otway, Daniel Fagnant, Prateek Bansal, Michael
            Levin, Yong Zhao, Jun Liu, Lewis Clements, Wendy Wagner, Duncan Stewart, Guni
            Sharon, Michael Albert, Peter
            Stone, Josiah Hanna, Rahul Patel, Hagen Fritz, Tejas Choudhary, Tianxin
            Li, Aqshems Nichols, Kapil Sharma, and Michele Simoni.
 Technical Report 0-6838-2, The University of Texas at Austin Center
            for Transportation Research, 2016.
 Available online
 Details
                  
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            Download: 
            
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Fulbright
      
      
         - Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Teaching and leading an ad hoc teammate: Collaboration without pre-coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, Jeffrey S. Rosenschein, and Noa
            Agmon.
 Artificial Intelligence, 203:35–65, Elsevier, October 2013.
 Official
            version from journal website.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (499.6kB
               )
                [ps]
               (734.2kB
               )
- Leading a Best-Response Teammate in an Ad Hoc Team.
 Peter Stone,
            Gal A. Kaminka, and Jeffrey S. Rosenschein.
 In
            Esther David, Enrico Gerding, David Sarne, and Onn
            Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets,
            pp. 132–146, Springer Verlag, November 2010.
 Official version from publisher's
            webpage
 Details
                  
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            Download: 
            [pdf]
               (179.3kB
               )
                [ps]
               (226.4kB
               )
- Ad Hoc Autonomous Agent Teams:  Collaboration without Pre-Coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, and Jeffrey S. Rosenschein .
 In Proceedings of the Twenty-Fourth
            Conference on Artificial Intelligence, July 2010.
 AAAI
            2010
 Details
                  
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            Download: 
            [pdf]
               (119.0kB
               )
                [ps]
               (266.6kB
               )
                [slides.pdf]
               (8.1MB
               )
- To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams.
 Peter
            Stone and Sarit Kraus.
 In The Ninth International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), International Foundation for Autonomous Agents and Multiagent Systems, May 2010.
 supplemental material cited in the paper,
            including a proof and an algorithm.
 AAMAS 2010
 Details
                  
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               (180.6kB
               )
                [ps]
               (285.3kB
               )
Guggenheim
      
      
         - Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Teaching and leading an ad hoc teammate: Collaboration without pre-coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, Jeffrey S. Rosenschein, and Noa
            Agmon.
 Artificial Intelligence, 203:35–65, Elsevier, October 2013.
 Official
            version from journal website.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (499.6kB
               )
                [ps]
               (734.2kB
               )
- Leading a Best-Response Teammate in an Ad Hoc Team.
 Peter Stone,
            Gal A. Kaminka, and Jeffrey S. Rosenschein.
 In
            Esther David, Enrico Gerding, David Sarne, and Onn
            Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets,
            pp. 132–146, Springer Verlag, November 2010.
 Official version from publisher's
            webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (179.3kB
               )
                [ps]
               (226.4kB
               )
- Ad Hoc Autonomous Agent Teams:  Collaboration without Pre-Coordination.
 Peter
            Stone, Gal A. Kaminka, Sarit
            Kraus, and Jeffrey S. Rosenschein .
 In Proceedings of the Twenty-Fourth
            Conference on Artificial Intelligence, July 2010.
 AAAI
            2010
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (119.0kB
               )
                [ps]
               (266.6kB
               )
                [slides.pdf]
               (8.1MB
               )
- To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams.
 Peter
            Stone and Sarit Kraus.
 In The Ninth International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), International Foundation for Autonomous Agents and Multiagent Systems, May 2010.
 supplemental material cited in the paper,
            including a proof and an algorithm.
 AAMAS 2010
 Details
                  
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            Download: 
            [pdf]
               (180.6kB
               )
                [ps]
               (285.3kB
               )
Intel
      
      
         - Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond J. Mooney.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, February 2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Selecting Compliant Agents for Opt-in Micro-Tolling.
 Josiah Hanna,
            Guni Sharon, Stephen
            Boyles, and Peter Stone.
 In Proceedings of the 33rd AAAI Conference
            on Artificial Intelligence (AAAI), January 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
- Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems.
 Yuqian
            Jiang, Shiqi Zhang, Piyush
            Khandelwal, and Peter Stone.
 Frontiers of Information Technology
            and Electronic Engineering, 20(3):363–373, Springer, March 2019.
 Official version from Publisher's
            Webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (412.1kB
               )
- Multi-Robot Planning with Conflicts and Synergies.
 Yuqian Jiang, Harel
            Yedidsion, Shiqi Zhang, Guni
            Sharon, and Peter Stone.
 Autonomous Robots, Springer, March 2019.
 Official version from Publisher's Webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
- Open-World Reasoning for Service Robots.
 Yuqian Jiang, Nick
            Walker, Justin Hart, and Peter Stone.
 In
            Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
 Accompanying video
 Details
                  
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            Download: 
            [pdf]
               (813.5kB
               )
- Learning Curriculum Policies for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 Details
                  
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            Download: 
            [pdf]
               (953.0kB
               )
                [slides.pdf]
               (5.6MB
               )
- Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks.
 Guni
            Sharon, Stephen D. Boyles, Shani
            Alkoby, and Peter Stone.
 In Proceedings of the 18th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS-19), May 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.7MB
               )
                [slides.pptx]
               (6.5MB
               )
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
 Felipe
            Leno Da Silva, Anna Helena Reali Costa, and Peter
            Stone.
 In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
 Details
                  
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            Download: 
            [pdf]
               (1.6MB
               )
- Improving Grounded Natural Language Understanding through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond Mooney.
 In Proceedings of the International Conference on
            Robotics and Automation (ICRA 2019), May 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.1MB
               )
- Desiderata for Planning Systems in General-Purpose Service Robots.
 Nick Walker,
            Yuqian Jiang, Maya Cakmak, and
            Peter Stone.
 In Proceedings of the ICAPS Workshop on Planning and Robotics
            (PlanRob 2019), July 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (651.5kB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems.
 Stefano
            Albrecht and Peter Stone.
 Artificial Intelligence, 258:66–95,
            Elsevier, 2018.
 Available from the publisher's webpage and
            arXiv
 Details
                  
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            Download: 
            [pdf]
               (670.7kB
               )
- Multi-modal Predicate Identification using Dynamically Learned Robot Controllers.
 Saeid Amiri, Suhua Wei, Shiqi
            Zhang, Jivko Sinapov, Jesse Thomason,
            and Peter Stone.
 In Proceedings of the 27th International Joint Conference
            on Artificial Intelligence (IJCAI-18), July 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.5MB
               )
- DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
 Haipeng
            Chen, Bo An, Guni Sharon, Josiah
            P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
 In Proceedings
            of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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            Download: 
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               (2.4MB
               )
                [ps]
               (5.9MB
               )
- Passive Demonstrations of Light-Based Robot Signals for Improved Human Interpretability.
 Rolando Fernandez, Nathan
            John, Sean Kirmani, Justin Hart, Jivko
            Sinapov, and Peter Stone.
 In Proceedings of the 27th IEEE International
            Symposium on Robot and Human Interactive Communication (RO-MAN), August 2018.
 Details
                  
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            Download: 
            [pdf]
               (8.5MB
               )
                [slides.pdf]
               (983.4kB
               )
- Towards a Data Efficient Off-Policy Policy Gradient.
 Josiah Hanna
            and Peter Stone.
 In AAAI Spring Symposium on Data Efficient Reinforcement
            Learning, March 2018.
 Details
                  
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            Download: 
            [pdf]
               (345.4kB
               )
- PRISM:  Pose  Registration  for  Integrated  Semantic  Mapping.
 Justin W. Hart,
            Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter
            Stone.
 In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
            October 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.4MB
               )
- Inferring User Intention using Gaze in Vehicles.
 Yu-Sian Jiang, Garrett
            Warnell, and Peter Stone.
 In The 20th ACM International Conference
            on Multimodal Interaction (ICMI), October 2018.
 Based on an earlier version presented at the AAAI
            PAIR workshop
 Details
                  
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            [pdf]
               (2.6MB
               )
- A Study of Human-Robot Copilot Systems for En-Route Destination Changing.
 Yu-Sian Jiang, Garrett
            Warnell, Eduardo Munera, and Peter Stone.
 In Proceedings of the 27th
            IEEE International Conference on Robot and Human Interactive Communication (RO-MAN2018), August 2018.
 Available
            from RO-MAN
 Details
                  
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            Download: 
            [pdf]
               (5.8MB
               )
                [slides.pptx]
               (32.7MB
               )
- A Stitch in Time - Autonomous Model Management via Reinforcement Learning.
 Elad
            Liebman, Eric Zavesky, and Peter Stone.
 In Proceedings of the 17th
            International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.7MB
               )
- On the Impact of Music on Decision Making in Cooperative Tasks.
 Elad
            Liebman, Corey N. White, and Peter
            Stone.
 In 19th International Society for Music Information retrieval Conference (ISMIR), September 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (258.5kB
               )
- State Abstraction Synthesis for Discrete Models of Continuous Domains.
 Jacob
            Menashe and Peter Stone.
 In Data Efficient Reinforcement Learning
            Workshop at AAAI Spring Symposium, March 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (538.3kB
               )
                [ps]
               (5.3MB
               )
- Deterministic Implementations for Reproducibility in Deep Reinforcement Learning.
 Prabhat Nagarajan, Garrett
            Warnell, and Peter Stone.
 In 2nd Reproducibility in Machine Learning
            Workshop at ICML 2018, July 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.6MB
               )
- Variety Wins: Soccer-Playing Robots and Infant Walking.
 Ori Ossmy, Justine E. Hoch, Patrick
            MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph.
 Frontiers
            in Neurorobotics, 12:19, 2018.
 Available from the publisher's
            webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.9MB
               )
- Traffic Optimization For a Mixture of Self-interested and Compliant Agents.
 Guni
            Sharon, Michael Albert, Tarun
            Rambha, Stephen Boyles, and Peter
            Stone.
 In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1002.7kB
               )
                [ps]
               (5.2MB
               )
                [slides.pptx]
               (11.1MB
               )
- Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions.
 Jesse
            Thomason, Jivko Sinapov, Raymond
            J. Mooney, and Peter Stone.
 In Proceedings of the 32nd Conference
            on Artificial Intelligence (AAAI), February 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
- Deep TAMER: Interactive agent shaping in high-dimensional state spaces.
 Garrett
            Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone.
 In Proceedings
            of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2018.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
                [slides.pptx]
               (16.2MB
               )
- TD Learning with Constrained Gradients.
 Ishan Durugkar and Peter
            Stone.
 In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017, December 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (381.4kB
               )
- Iterative Human-Aware Mobile Robot Navigation.
 Shih-Yun Lo, Benito Fernandez, and Peter
            Stone.
 In Proceedings of the Human-Centered Robotics workshop of the 13th International Conference on Robotics:
            Science and System (RSS), July 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
Raytheon
      
      
         - Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond J. Mooney.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, February 2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Reducing Sampling Error in Policy Gradient Learning.
 Josiah Hanna
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 This paper contains material that was previously
            presented at the 2018 NeurIPS Deep Reinforcement Learning Workshop.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
                [slides.pdf]
               (3.1MB
               )
- Selecting Compliant Agents for Opt-in Micro-Tolling.
 Josiah Hanna,
            Guni Sharon, Stephen
            Boyles, and Peter Stone.
 In Proceedings of the 33rd AAAI Conference
            on Artificial Intelligence (AAAI), January 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
- Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems.
 Yuqian
            Jiang, Shiqi Zhang, Piyush
            Khandelwal, and Peter Stone.
 Frontiers of Information Technology
            and Electronic Engineering, 20(3):363–373, Springer, March 2019.
 Official version from Publisher's
            Webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (412.1kB
               )
- Multi-Robot Planning with Conflicts and Synergies.
 Yuqian Jiang, Harel
            Yedidsion, Shiqi Zhang, Guni
            Sharon, and Peter Stone.
 Autonomous Robots, Springer, March 2019.
 Official version from Publisher's Webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
- Open-World Reasoning for Service Robots.
 Yuqian Jiang, Nick
            Walker, Justin Hart, and Peter Stone.
 In
            Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
 Accompanying video
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- Learning Curriculum Policies for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 Details
                  
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               (953.0kB
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               (5.6MB
               )
- Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks.
 Guni
            Sharon, Stephen D. Boyles, Shani
            Alkoby, and Peter Stone.
 In Proceedings of the 18th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS-19), May 2019.
 Details
                  
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               (1.7MB
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               (6.5MB
               )
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
 Felipe
            Leno Da Silva, Anna Helena Reali Costa, and Peter
            Stone.
 In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
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               (1.6MB
               )
- Improving Grounded Natural Language Understanding through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond Mooney.
 In Proceedings of the International Conference on
            Robotics and Automation (ICRA 2019), May 2019.
 Details
                  
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               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
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               (157.4kB
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                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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               (6.1MB
               )
- Desiderata for Planning Systems in General-Purpose Service Robots.
 Nick Walker,
            Yuqian Jiang, Maya Cakmak, and
            Peter Stone.
 In Proceedings of the ICAPS Workshop on Planning and Robotics
            (PlanRob 2019), July 2019.
 Details
                  
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               (651.5kB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems.
 Stefano
            Albrecht and Peter Stone.
 Artificial Intelligence, 258:66–95,
            Elsevier, 2018.
 Available from the publisher's webpage and
            arXiv
 Details
                  
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               (670.7kB
               )
- Multi-modal Predicate Identification using Dynamically Learned Robot Controllers.
 Saeid Amiri, Suhua Wei, Shiqi
            Zhang, Jivko Sinapov, Jesse Thomason,
            and Peter Stone.
 In Proceedings of the 27th International Joint Conference
            on Artificial Intelligence (IJCAI-18), July 2018.
 Details
                  
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               (2.5MB
               )
- DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
 Haipeng
            Chen, Bo An, Guni Sharon, Josiah
            P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
 In Proceedings
            of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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               )
                [ps]
               (5.9MB
               )
- Passive Demonstrations of Light-Based Robot Signals for Improved Human Interpretability.
 Rolando Fernandez, Nathan
            John, Sean Kirmani, Justin Hart, Jivko
            Sinapov, and Peter Stone.
 In Proceedings of the 27th IEEE International
            Symposium on Robot and Human Interactive Communication (RO-MAN), August 2018.
 Details
                  
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               (8.5MB
               )
                [slides.pdf]
               (983.4kB
               )
- Towards a Data Efficient Off-Policy Policy Gradient.
 Josiah Hanna
            and Peter Stone.
 In AAAI Spring Symposium on Data Efficient Reinforcement
            Learning, March 2018.
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               (345.4kB
               )
- PRISM:  Pose  Registration  for  Integrated  Semantic  Mapping.
 Justin W. Hart,
            Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter
            Stone.
 In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
            October 2018.
 Details
                  
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               (4.4MB
               )
- Inferring User Intention using Gaze in Vehicles.
 Yu-Sian Jiang, Garrett
            Warnell, and Peter Stone.
 In The 20th ACM International Conference
            on Multimodal Interaction (ICMI), October 2018.
 Based on an earlier version presented at the AAAI
            PAIR workshop
 Details
                  
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               (2.6MB
               )
- A Study of Human-Robot Copilot Systems for En-Route Destination Changing.
 Yu-Sian Jiang, Garrett
            Warnell, Eduardo Munera, and Peter Stone.
 In Proceedings of the 27th
            IEEE International Conference on Robot and Human Interactive Communication (RO-MAN2018), August 2018.
 Available
            from RO-MAN
 Details
                  
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               (5.8MB
               )
                [slides.pptx]
               (32.7MB
               )
- A Stitch in Time - Autonomous Model Management via Reinforcement Learning.
 Elad
            Liebman, Eric Zavesky, and Peter Stone.
 In Proceedings of the 17th
            International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018.
 Details
                  
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               (1.7MB
               )
- On the Impact of Music on Decision Making in Cooperative Tasks.
 Elad
            Liebman, Corey N. White, and Peter
            Stone.
 In 19th International Society for Music Information retrieval Conference (ISMIR), September 2018.
 Details
                  
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               (258.5kB
               )
- State Abstraction Synthesis for Discrete Models of Continuous Domains.
 Jacob
            Menashe and Peter Stone.
 In Data Efficient Reinforcement Learning
            Workshop at AAAI Spring Symposium, March 2018.
 Details
                  
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               (538.3kB
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               (5.3MB
               )
- Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science.
 Decebal Constantin Mocanu, Elena
            Mocanu, Peter Stone, Phuong
            H. Nguyen, Madeleine Gibescu, and Antonio
            Liotta.
 Nature Communications, 9(2383), June 2018.
 Official version from Publisher's
            Webpage.
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               (1.5MB
               )
- Deterministic Implementations for Reproducibility in Deep Reinforcement Learning.
 Prabhat Nagarajan, Garrett
            Warnell, and Peter Stone.
 In 2nd Reproducibility in Machine Learning
            Workshop at ICML 2018, July 2018.
 Details
                  
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               (6.6MB
               )
- Variety Wins: Soccer-Playing Robots and Infant Walking.
 Ori Ossmy, Justine E. Hoch, Patrick
            MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph.
 Frontiers
            in Neurorobotics, 12:19, 2018.
 Available from the publisher's
            webpage
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               (2.9MB
               )
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
 Tarun
            Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
            and Peter Stone.
 Transportation Research Part B: Methodological,
            110:104–21, 2018.
 Official version from Publisher's
            Webpage
 Details
                  
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               (1.6MB
               )
- Traffic Optimization For a Mixture of Self-interested and Compliant Agents.
 Guni
            Sharon, Michael Albert, Tarun
            Rambha, Stephen Boyles, and Peter
            Stone.
 In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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               (1002.7kB
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                [ps]
               (5.2MB
               )
                [slides.pptx]
               (11.1MB
               )
- Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions.
 Jesse
            Thomason, Jivko Sinapov, Raymond
            J. Mooney, and Peter Stone.
 In Proceedings of the 32nd Conference
            on Artificial Intelligence (AAAI), February 2018.
 Details
                  
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               (1.4MB
               )
- Deep TAMER: Interactive agent shaping in high-dimensional state spaces.
 Garrett
            Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone.
 In Proceedings
            of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2018.
 Details
                  
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               (1.6MB
               )
                [slides.pptx]
               (16.2MB
               )
- Reasoning about Hypothetical Agent Behaviours and their Parameters.
 Stefano Albrecht
            and Peter Stone.
 In Proceedings of the 16th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
 Available from IFAAMAS
            and from ACM
 Details
                  
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               (608.2kB
               )
                [slides.pdf]
               (1.2MB
               )
- TD Learning with Constrained Gradients.
 Ishan Durugkar and Peter
            Stone.
 In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017, December 2017.
 Details
                  
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               (381.4kB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            Hanna, Philip Thomas, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
 Details
                  
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               (1.2MB
               )
                [slides.pdf]
               (1.1MB
               )
- Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
 Josiah
            Hanna, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2017.
 Details
                  
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               (663.8kB
               )
                [ps]
               (572.6kB
               )
                [slides.pdf]
               (1.3MB
               )
- Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests.
 Piyush
            Khandelwal and Peter Stone.
 In International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2017.
 Details
                  
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               (1.8MB
               )
- Iterative Human-Aware Mobile Robot Navigation.
 Shih-Yun Lo, Benito Fernandez, and Peter
            Stone.
 In Proceedings of the Human-Centered Robotics workshop of the 13th International Conference on Robotics:
            Science and System (RSS), July 2017.
 Details
                  
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               (2.0MB
               )
- Fast and Precise Black and White Ball Detection for RoboCup Soccer.
 Jacob
            Menashe, Josh Kelle, Katie Genter, Josiah
            Hanna, Elad Liebman, Sanmit
            Narvekar, Ruohan Zhang, and Peter
            Stone.
 In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
 Details
                  
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               (254.2kB
               )
                [ps]
               (716.1kB
               )
                [slides.pdf]
               (1.5MB
               )
- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
 Sanmit
            Narvekar, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
            2017.
 Details
                  
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               (826.2kB
               )
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               (5.8MB
               )
- Network-wide Adaptive Tolling for Connected and Automated vehicles.
 Guni
            Sharon, Michael W. Levin, Josiah
            P. Hanna, Tarun Rambha, Stephen
            D. Boyles, and Peter Stone.
 Transportation Research Part C, 84:142–157,
            September 2017.
 Transportation Research Part C.
 Audio slides.
 Contains material
            that was previously published in an AAMAS-17 paper.
 Details
                  
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               (2.8MB
               )
                [ps]
               (4.2MB
               )
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
 Guni
            Sharon and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
 Details
                  
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               (1.1MB
               )
                [ps]
               (7.1MB
               )
                [slides.pptx]
               (140.9MB
               )
- Multirobot Symbolic Planning under Temporal Uncertainty.
 Shiqi Zhang,
            Yuqian Jiang, Guni Sharon, and Peter
            Stone.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS),
            May 2017.
 Accompanying videos at https://youtu.be/ADbH3sppLHQ
 Details
                  
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               (2.3MB
               )
Lockheed Martin
      
      
         - L3M+P: Lifelong Planning with Large Language Models.
 Krish Agarwal, Yuqian Jiang,
            Jiaheng Hu, Bo Liu, and Peter
            Stone.
 In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.
 Details
                  
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               (1.2MB
               )
- Proto Successor Measure: Representing the Behavior Space of an RL Agent.
 Siddhant Agarwal, Harshit Sikchi, Peter
            Stone, and Amy Zhang.
 In International Conference on Machine Learning, June 2025.
 Details
                  
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               (911.1kB
               )
- Multi-Agent Inverse Reinforcement Learning in Real World Unstructured Pedestrian Crowds.
 Rohan
            Chandra, Haresh Karnan, Negar Mehr, Peter
            Stone, and Joydeep Biswas.
 In IEEE/RSJ International Conference on Intelligent
            Robots and Systems (IROS), October 2025.
 Details
                  
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               (695.7kB
               )
- Reinforcement Learning within the Classical Robotics Stack: A Case Study in Robot Soccer.
 Adam Labiosa, Zhihan Wang,
            Siddhant Agarwal, William Cong, Geethika Hemkumar, Abhinav Narayan Harish, Benjamin Hong, Josh Kelle, Chen Li, Yuhao Li, Zisen
            Shao, Peter Stone, and Josiah
            Hanna.
 In International Conference on Robotics and Automation (ICRA), May 2025.
 Details
                  
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               (1.1MB
               )
- Longhorn: State Space Models are Amortized Online Learners.
 Bo Liu,
            Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, and qiang liu.
 In International
            Conference on Learning Representations, April 2025.
 Details
                  
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               (877.2kB
               )
- PACER: Preference-conditioned All-terrain Costmap Generation.
 Luisa Mao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 Robotics
            and Automation Letters, 2025.
 Details
                  
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               (3.2MB
               )
                [slides.pptx]
               (28.0MB
               )
- PRESTO: Fast Motion Planning Using Diffusion Models Based on Key-Configuration Environment Representation.
 Mingyo
            Seo, Yoonyoung Cho, Yoonchang Sung, Peter
            Stone, Yuke Zhu, and Beomjoon Kim.
 In IEEE International Conference
            on Robotics and Automation (ICRA), May 2025.
 Details
                  
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               (1.4MB
               )
                [slides.pdf]
               (2.1MB
               )
                [poster.pdf]
               (1.3MB
               )
- Learning to Look: Seeking Information for Decision Making via Policy Factorization.
 Shivin Dass, Jiaheng
            Hu, Ben Abbatematteo, Peter Stone, and Roberto Martín-Martín.
 In Conference
            on Robot Learning (CoRL), November 2024.
 Details
                  
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               (6.8MB
               )
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
 Haresh,
            Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
 In
            International Conference on Robotics and Automation, May 2024.
 Details
                  
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               (4.3MB
               )
- Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning.
 Jiaheng
            Hu, Zizhao Wang, Roberto Martín-Martín, and Peter
            Stone.
 In Conference on Neural Information Parocessing Systems (NeurIPS), December 2024.
 Details
                  
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               (2.7MB
               )
- Learning Optimal Advantage from Preferences and Mistaking it for Reward.
 W. Bradley
            Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter
            Stone, and Scott Niekum.
 In The 38th Annual AAAI Conference on Artificial
            Intelligence (AAAI), February 2024.
 Details
                  
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               (3.6MB
               )
                [slides.pdf]
               (3.9MB
               )
                [poster.pdf]
               (2.9MB
               )
- Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents.
 Arrasy
            Rahman, Jiaxun Cui, and Peter Stone.
 In
            AAAI, February 2024.
 the conference presentation
 Details
                  
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               (1.3MB
               )
                [slides.ppt]
               (9.2MB
               )
                [poster.pdf]
               (956.2kB
               )
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
 Amir Hossain Raj, Zichao
            Hu, Haresh Karnan, Rohan Chandra,
            Amirreza Payandeh, Luisa Mao, Peter Stone, Joydeep
            Biswas, and and Xuesu Xiao.
 In International Conference on Robotics
            and Automation, May 2024.
 Details
                  
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               (2.0MB
               )
- Relaxed Exploration Constrained Reinforcement Learning.
 Shahaf S. Shperberg, Bo
            Liu, and Peter Stone.
 In Conference on Autonomous Agents and Multiagent
            Systems, May 2024.
 Details
                  
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               (3.4MB
               )
- Dobby: A Conversational Service Robot Driven by GPT-4.
 Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
            Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
            Hart.
 In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
 Details
                  
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               (863.8kB
               )
                [poster.pdf]
               (892.0kB
               )
- Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning.
 Yoonchang
            Sung, Rahul Shome, and Peter Stone.
 In IEEE International Conference
            on Robotics and Automation (ICRA), March 2024.
 Video
            presentation
 Details
                  
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               (482.7kB
               )
- Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes.
 Chen
            Tang, Ben Abbatematteo, Jiaheng Hu, Rohan
            Chandra, Roberto Martín-Martín, and Peter Stone.
 Annual Review
            of Control, Robotics, and Autonomous Systems (ARCRAS), 8:153–88, 2024.
 Presented in Senior member track at
            AAAI 2025
 Official
            version on publisher's website
 Details
                  
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               (4.3MB
               )
                [slides.pdf]
               (2.9MB
               )
                [poster.pdf]
               (604.3kB
               )
- N-Agent Ad Hoc Teamwork.
 Caroline Wang, Arrasy
            Rahman, Ishan Durugkar, Elad
            Liebman, and Peter Stone.
 In Conference on Neural Information Processing
            Systems (NeurIPS), December 2024.
 Details
                  
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               (1.6MB
               )
                [slides.pdf]
               (1.3MB
               )
                [poster.pdf]
               (1.7MB
               )
- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
 Zizhao
            Wang, Caroline Wang, Xuesu
            Xiao, Yuke Zhu, and Peter Stone.
 In
            AAAI Conference on Artificial Intelligence, February 2024.
 Details
                  
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               (4.5MB
               )
- LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning.
 Zifan Xu, Haozhu
            Wang, Dmitriy Bespalov, Xian Wu, Peter Stone, and Yanjun Qi.
 In Findings
            of Empirical Methods in Natural Language Processing, November 2024.
 Details
                  
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               (1.6MB
               )
- Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks.
 Ziping Xu, Zifan
            Xu, Runxuan Jiang, Peter Stone, and Ambuj
            Tewari.
 In International Conference on Learning Representations (ICLR), May 2024.
 Details
                  
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               (1.4MB
               )
- Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning.
 Zifan
            Xu, Amir Hossain Raj, Xuesu Xiao, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation, May 2024.
 Details
                  
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               (2.0MB
               )
- t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making.
 William Yue,
            Bo Liu, and Peter Stone.
 In
            Conference on Lifelong Learning Agents (CoLLAs), July 2024.
 Details
                  
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               (599.7kB
               )
                [poster.pdf]
               (709.1kB
               )
- f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences.
 Siddhant Agarwal, Ishan
            Durugkar, Peter Stone, and Amy Zhang.
 In Conference on Neural Information
            Processing Systems, December 2023.
 Details
                  
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               (3.4MB
               )
                [slides.pptx]
               (13.6MB
               )
                [poster.pdf]
               (1.8MB
               )
- "What's That Robot Doing Here?": Factors Influencing Perceptions Of Incidental Encounters With Autonomous Quadruped Robots.
 Elliott
            Hauser, Yao-Cheng Chan, Geethika Hemkumar, Daksh Dua, Parth Chonkar, Efren Mendoza Enriquez, Tiffany Kao, Shikhar Gupta, Huihai
            Wang, Justin Hart, Reuth Mirsky,
            Joydeep Biswas, Junfeng Jiao, and Peter
            Stone.
 In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23), pp.
            1–15, July 2023.
 Available online at https://dl.acm.org/doi/10.1145/3597512.3599707
 Details
                  
               BibTeX
                  
            Download: 
            
            (unavailable)
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
 Haresh
            Karnan, Elvin Yang, Daniel Farkash, Garrett
            Warnell, Joydeep Biswas, and Peter
            Stone.
 In The Conference on Robot Learning (CoRL), November 2023.
 Poster,
            Video, Project Website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (25.7MB
               )
- Models of human preference for learning reward functions.
 W. Bradley Knox,
            Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
            Stone, and Alessandro Allievi.
 Transactions on Machine Learning Research (TMLR), 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.7MB
               )
                [slides.pdf]
               (13.4MB
               )
- Reward (Mis)design for Autonomous Driving.
 W. Bradley Knox, Alessandro Allievi,
            Holger Banzhaf, Felix Schmitt, and Peter Stone.
 Artificial Intelligence,
            316:103829, 2023.
 Paper webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (696.3kB
               )
                [ps]
               (5.6MB
               )
- FAMO: Fast Adaptive Multitask Optimization.
 Bo Liu, Yihao Feng, Peter Stone, and Qiang Liu.
 In Neural Information Processing Systems Foundation,
            July 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.0MB
               )
- Exploring the Cost of Interruptions in Human-Robot Teaming.
 Swathi Mannem, William
            Macke, Peter Stone, and Reuth
            Mirsky.
 In IEEE-RAS Humanoids, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (921.5kB
               )
                [poster.pdf]
               (294.3kB
               )
- Towards a Real-Time, Low-Resource, End-to-end Object Detection Pipeline for Robot Soccer.
 Sai Kiran Narayanaswami,
            Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit
            Narvekar, and Peter Stone.
 In Amy Eguchi, Nuno Lau, Maike Paetzel-Prussman,
            and Thanapat Wanichanon, editors, RoboCup 2022: Robot World Cup XXV, pp. 62–74, Springer International Publishing,
            2023.
 The book
 Details
                  
               BibTeX
                  
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            [pdf]
               (572.2kB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
- ELDEN: Exploration via Local Dependencies.
 Zizhao Wang, Jiaheng
            Hu, Peter Stone, and Roberto Martín-Martín.
 In Conference on Neural
            Information Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.2MB
               )
                [slides.pptx]
               (22.4MB
               )
                [poster.pdf]
               (856.5kB
               )
- D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning.
 Caroline
            Wang, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
                [slides.pdf]
               (2.4MB
               )
                [poster.pdf]
               (1.4MB
               )
- Learning Real-world Autonomous Navigation by Self-Supervised Environment Synthesis.
 Zifan
            Xu, Anirudh Nair, Xuesu Xiao, and Peter
            Stone.
 In IROS Workshop on Photorealistic Image and Environment Synthesis for Robotics (PIES-Rob) , January
            2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.3MB
               )
- Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu,
            Peter Stone, and Shiqi Zhang.
 In
            International Conference on Intelligent Robots and Systems (IROS), October 2023.
 Project
            website (includes poster and 5-minute video presentation)
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
                [slides.pdf]
               (6.6MB
               )
- Learning Generalizable Manipulation Policies with Object-Centric 3D Representations.
 Yifeng
            Zhu, Zhenyu Jiang, Peter Stone, and Yuke
            Zhu.
 In Conference on Robot Learning (CoRL), November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (7.3MB
               )
                [poster.pdf]
               (5.2MB
               )
- Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles.
 Jiaxun
            Cui, Hang Qiu, Dian Chen, Peter
            Stone, and Yuke Zhu.
 In IEEE/CVF Conference on Computer Vision and
            Pattern Recognition (CVPR), June 2022.
 Project website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.5MB
               )
- Quantifying Human Rationality in Ad-hoc Teamwork.
 Yair Hanina, Reuth
            Mirsky, William Macke, and Peter
            Stone.
 In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (404.2kB
               )
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
 Eddy Hudson, Garrett
            Warnell, Faraz Torabi, and Peter
            Stone.
 In International Conference on Robotics and Automation (ICRA), May 2022.
 Presentation
            Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.5MB
               )
- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
 Haresh
            Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 In
            International Conference on Intelligent Robots and Systems, 2022, October 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.0MB
               )
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
 Haresh
            Karnan, Garrett Warnell, Xuesu
            Xiao, and Peter Stone.
 In International Conference on Robotics and
            Automation, 2022, May 2022.
 Poster,
            Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
- Adversarial Imitation Learning from Video using a State Observer.
 Haresh
            Karnan, Garrett Warnell, Faraz
            Torabi, and Peter Stone.
 In International Conference on Robotics
            and Automation, 2022, May 2022.
 Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (933.2kB
               )
- BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.
 Bo
            Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu.
 In Conference
            on Neural Information Processing Systems, 2022, December 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (1.6MB
               )
                [poster.pdf]
               (885.6kB
               )
- A Survey of Ad Hoc Teamwork Research.
 Reuth Mirsky, Ignacio
            Carlucho, Arrasy Rahman, Eliott Fosong, William
            Macke, Mohan Sridharan, Peter
            Stone, and Stefano Albrecht.
 In Baumeister, Dorothea and Rothe, Jörg, editors,
            Multi-Agent Systems, pp. 275–93, Springer International Publishing, Cham, 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (198.8kB
               )
- Task Factorization in Curriculum Learning.
 Reuth Mirsky,
            Shahaf S. Shperberg, Yulin Zhang, Zifan
            Xu, Yuqian Jiang, Jiaxun Cui, and Peter
            Stone.
 In ICML workshop on Decision Awareness in Reinforcement Learning (DARL), July 2022.
 recorded
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1011.6kB
               )
- Visually Grounded Task and Motion Planning for Mobile Manipulation.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuke Zhu, Peter
            Stone, and Shiqi Zhang.
 In International Conference on Robotics
            and Automation (ICRA), May 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
- Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation.
 Yifeng
            Zhu, Peter Stone, and Yuke
            Zhu.
 IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.3MB
               )
- VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors.
 Yifeng
            Zhu, Abhishek Joshi, Peter Stone, and Yuke
            Zhu.
 In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.4MB
               )
- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
 Michael
            Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
 Operations
            Research, March 2021.
 Details
                  
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               (692.5kB
               )
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
 Roberto Capobianco, Varun Kompella, James
            Ault, Guni Sharon, Stacy
            Jong, Spencer Fox, Lauren
            Meyers, Peter R. Wurman, and Peter
            Stone.
 The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
 Contains
            material that was previously published in an AAMAS
            2021 paper and a AAAI 2020 Fall
            Symposium paper.
 Article available from  JAIR website.
 Simulator
            source code.
 Details
                  
               BibTeX
                  
            Download: 
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               (1.6MB
               )
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
 Jiaxun
            Cui, William Macke, Harel
            Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
            Stone.
 In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2021.
 Project page, with videos
 Details
                  
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            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pptx]
               (1.5MB
               )
- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
 Yunshu Du, Garrett
            Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
            E. Taylor.
 Neural Computing and Applications, May 2021.
 Details
                  
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            Download: 
            [pdf]
               (2.2MB
               )
- Adversarial Intrinsic Motivation for Reinforcement Learning.
 Ishan Durugkar,
            Mauricio Tec, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
            December 2021.
 slides and video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.1MB
               )
- Capturing Skill State in Curriculum Learning for Human Skill Acquisition.
 Keya
            Ghonasgi, Reuth Mirsky, Sanmit
            Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D.
            Deshpande.
 In International Conference on Intelligent Robots and Systems (IROS), September 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Machine versus Human Attention in Deep Reinforcement Learning Tasks.
 Sihang Guo, Ruohan
            Zhang, Bo Liu, Yifeng Zhu,
            Mary Hayhoe, Dana Ballard, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
 Josiah
            P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
            Warnell, and Peter Stone.
 Special Issue on Reinforcement Learning
            for Real Life, Machine Learning, 2021, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.0MB
               )
- Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy.
 Josiah
            P. Hanna, Scott Niekum, and Peter
            Stone.
 Machine Learning (MLJ), 110:1267–1317, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.7MB
               )
- Incorporating Gaze into Social Navigation.
 Justin Hart, Reuth
            Mirsky, Xuesu Xiao, and Peter
            Stone.
 In RSS Workshop on Social Robot Navigation, July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
                [slides.pdf]
               (3.5MB
               )
- Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation.
 Blake Holman, Abrar
            Anwar, Akash Singh, Mauricio Tec, Justin
            Hart, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.7MB
               )
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
 Eddy Hudson, Garrett
            Warnell, and Peter Stone.
 In Autonomous Robots and Multirobot Systems
            Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (393.0kB
               )
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
 Yuqian
            Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
 In
            Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
                [slides.pdf]
               (1.8MB
               )
- A Lifelong Learning Approach to Mobile Robot Navigation.
 Bo Liu, Xuesu Xiao, and Peter Stone.
 IEEE
            Robotics and Automation Letters (RA-L), 6(2), April 2021.
 Presented at IEEE International Conference on Robotics
            and Automation (ICRA),
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.6MB
               )
- Conflict-Averse Gradient Descent for Multi-task learning.
 Bo Liu, Xingchao
            Liu, Xiaojie Jin, Peter Stone, and Qiang Liu.
 In Conference on Neural
            Information Processing Systems (NeurIPS), 2021, December 2021.
 slides
            and 9-minute presentation
 github repository
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.7MB
               )
- Team  Orienteering  Coverage  Planning  with  Uncertain  Reward.
 Bo Liu,
            Xuesu Xiao, and Peter Stone.
 In
            International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.9MB
               )
- Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition.
 Bo
            Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke
            Zhu, and Animashree Anandkumar.
 In Proceedings of the 38th International Conference on Machine Learning, PMLR 139,
            2021 (ICML), July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
                [poster.pdf]
               (1.1MB
               )
- Expected Value of Communication for Planning in Ad Hoc Teamwork.
 William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (869.9kB
               )
                [slides.pdf]
               (2.3MB
               )
                [poster.pdf]
               (1.8MB
               )
- Is the Cerebellum a Model-Based Reinforcement Learning Agent?.
 Bharath Masetty, Reuth
            Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter
            Stone.
 In Adaptive and Learning Agents Workshop at AAMAS, May 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (594.9kB
               )
                [slides.pdf]
               (1.5MB
               )
- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
 Reuth
            Mirsky and Peter Stone.
 In ICSR workshop on Adaptive Social Interaction
            and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (194.4kB
               )
- The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care.
 Reuth
            Mirsky and Peter Stone.
 In Proceedings of the 20th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (679.2kB
               )
- Reasoning about Human Behavior in Ad Hoc Teamwork.
 Jennifer Suriadinata, William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
 Video
            Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (926.2kB
               )
- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (742.7kB
               )
- APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback.
 Zizhao
            Wang, Xuesu Xiao, Bo Liu,
            Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), October 2021.
 5-minute
            Video Presentation;  15-minute Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pdf]
               (2.7MB
               )
- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
 Zizhao
            Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
            Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
 In Proceedings
            of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
 1-minute
            Video Summary;   15-minute Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.9MB
               )
                [slides.pdf]
               (2.7MB
               )
- APPLI: Adaptive Planner Parameter Learning From Interventions.
 Zizhao Wang,
            Xuesu Xiao, Bo Liu, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
- APPLR: Adaptive Planner Parameter Learning from Reinforcement.
 Zifan Xu,
            Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett
            Warnell, Bo Liu, Zizhao Wang,
            and Peter Stone.
 In Proceedings of the 2021 IEEE International Conference
            on Robotics and Automation (ICRA 2021), June 2021.
 Video
            presentation
 Project webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (27.4MB
               )
- Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning.
 Zifan
            Xu, Xuesu Xiao, Garrett
            Warnell, Anirudh Nair, and Peter Stone.
 In Proceedings of the 2021
            IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), October 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.5MB
               )
- A Scavenger Hunt for Service Robots.
 Harel Yedidsion,
            Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
            Stone.
 In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
 Harel
            Yedidsion, Shani Alkoby, and Peter
            Stone.
 Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
 arXiv
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (478.9kB
               )
- Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks.
 Ruohan
            Zhang, Faraz Torabi, Garrett
            Warnell, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems,
            35(31), June 2021.
 official online version
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.8MB
               )
- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
 Siddarth Desai, Ishan
            Durugkar, Haresh Karnan, Garrett
            Warnell, Josiah Hanna, and Peter
            Stone.
 In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
            December 2020.
 Poster
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.3MB
               )
- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
 Siddharth Desai, Haresh
            Karnan, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 11-minute video
            presentation.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.9MB
               )
- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
 Ishan
            Durugkar, Elad Liebman, and Peter
            Stone.
 In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
            2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.9MB
               )
- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
 Justin Hart,
            Reuth Mirsky, Xuesu Xiao,
            Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
            Stone.
 In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.2MB
               )
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
 Haresh
            Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 14-minute video
            presentation.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (506.6kB
               )
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
 Shih-Yun Lo, Shiqi
            Zhang, and Peter Stone.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, October 2020.
 Contains material that was previously published in an AAMAS-18
            paper (awarded the Best Robotics Paper Award at AAMAS 2018)
 Also
            available from  JAIR website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
- Learning and Reasoning for Robot Dialog and Navigation Tasks.
 Keting Lu, Shiqi
            Zhang, Peter Stone, and Xiaoping
            Chen.
 In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
            107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
 Official version from ACL
            Digital Library, including a link to the conference presentation
 Details
                  
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            Download: 
            [pdf]
               (3.6MB
               )
- A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork.
 Reuth
            Mirsky, William Macke, Andy Wang, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 29th International
            Joint Conference on Artificial Intelligence, July 2020.
 15-minute
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
                [slides.pdf]
               (1.4MB
               )
- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
 Sanmit
            Narvekar, Bei Peng, Matteo Leonetti, Jivko
            Sinapov, Matthew E. Taylor, and Peter
            Stone.
 Journal of Machine Learning Research, 21(181):1–50, 2020.
 Details
                  
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               (1.4MB
               )
- Generalizing Curricula for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In 4th Lifelong Learning Workshop at the International
            Conference on Machine Learning (ICML 2020), July 2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (330.4kB
               )
                [slides.pdf]
               (3.8MB
               )
- Learning to Improve Multi-Robot Hallway Navigation.
 Jin-Soo Park, Brian Tsang, Harel
            Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
 In Proceedings of the 4th Conference on Robot Learning (CoRL),
            November 2020.
 Video presentation
 Details
                  
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               (1.3MB
               )
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
 Brahma
            Pavse, Faraz Torabi, Josiah
            Hanna, Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
 Video
            of the experiments; 13-minute video presentation.
 Details
                  
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            Download: 
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               (405.1kB
               )
                [slides.pptx]
               (115.4MB
               )
- Reducing Sampling Error in Batch Temporal Difference Learning.
 Brahma Pavse,
            Ishan Durugkar, Josiah Hanna,
            and Peter Stone.
 In Proceedings of the 37th International Conference
            on Machine Learning (ICML), July 2020.
 The paper and talk is available from the ICML
            2020 virtual conference page.
 Details
                  
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            Download: 
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               (738.4kB
               )
                [slides.pdf]
               (5.2MB
               )
- On Sampling Error in Batch Action-Value Prediction Algorithms.
 Brahma S. Pavse,
            Josiah P. Hanna, Ishan Durugkar,
            and Peter Stone.
 In In the Offline Reinforcement Learning Workshop at
            Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
 5-minute
            Video Presentation
 Details
                  
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               (327.2kB
               )
- Deep R-Learning for Continual Area Sweeping.
 Rishi Shah, Yuqian Jiang, Justin
            Hart, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
 1-minute
            video demonstration; 13-minute Video
            presentation.
 Details
                  
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            Download: 
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               (374.2kB
               )
                [slides.pdf]
               (1.1MB
               )
- Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond J. Mooney.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, February 2020.
 Details
                  
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               (4.0MB
               )
- APPLD: Adaptive Planner Parameter Learning from Demonstration.
 Xuesu
            Xiao, Bo Liu, Garrett
            Warnell, Jonathan Fink, and Peter Stone.
 IEEE Robotics and Automation
            Letters (RA-L), June 2020.
 Presented at International Conference on Intelligent Robots and Systems ({IROS})\\  
             5-minute Video presentation; 15-minute
            Video presentation
 Project webpage
 Details
                  
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               (2.2MB
               )
                [slides.pdf]
               (21.1MB
               )
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy.
 Josiah
            Hanna, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
 Details
                  
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            Download: 
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               (2.7MB
               )
                [slides.pdf]
               (4.0MB
               )
- Reducing Sampling Error in Policy Gradient Learning.
 Josiah Hanna
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 This paper contains material that was previously
            presented at the 2018 NeurIPS Deep Reinforcement Learning Workshop.
 Details
                  
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               (1.5MB
               )
                [slides.pdf]
               (3.1MB
               )
- Selecting Compliant Agents for Opt-in Micro-Tolling.
 Josiah Hanna,
            Guni Sharon, Stephen
            Boyles, and Peter Stone.
 In Proceedings of the 33rd AAAI Conference
            on Artificial Intelligence (AAAI), January 2019.
 Details
                  
               BibTeX
                  
            Download: 
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               (2.2MB
               )
- Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems.
 Yuqian
            Jiang, Shiqi Zhang, Piyush
            Khandelwal, and Peter Stone.
 Frontiers of Information Technology
            and Electronic Engineering, 20(3):363–373, Springer, March 2019.
 Official version from Publisher's
            Webpage
 Details
                  
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            Download: 
            [pdf]
               (412.1kB
               )
- Multi-Robot Planning with Conflicts and Synergies.
 Yuqian Jiang, Harel
            Yedidsion, Shiqi Zhang, Guni
            Sharon, and Peter Stone.
 Autonomous Robots, Springer, March 2019.
 Official version from Publisher's Webpage
 Details
                  
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            Download: 
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               (2.0MB
               )
- Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots.
 Yuqian
            Jiang, Fangkai Yang, Shiqi
            Zhang, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
 Details
                  
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            Download: 
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               (925.2kB
               )
- Open-World Reasoning for Service Robots.
 Yuqian Jiang, Nick
            Walker, Justin Hart, and Peter Stone.
 In
            Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
 Accompanying video
 Details
                  
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            Download: 
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               (813.5kB
               )
- The right music at the right time: adaptive personalized playlists based on sequence modeling.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone Peter Stone.
 Management Information Systems Quarterly, 43(3):765–786, Society for Information Management
            and The Management Information Systems Research Center, 2019.
 Available from publisher's
            website.
 Details
                  
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            Download: 
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               (4.0MB
               )
- Learning Curriculum Policies for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (953.0kB
               )
                [slides.pdf]
               (5.6MB
               )
- Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report.
 Rishi Shah, Yuqian
            Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta,
            Rachel Schlossman, Marika Murphy, Justin Hart, Luis
            Sentis, and Peter Stone.
 In AAAI Fall Symposium on Artificial Intelligence
            and Human-Robot Interaction for Service Robots in Human Environments (AI-HRI 2019), November 2019.
 Details
                  
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            Download: 
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               (4.5MB
               )
- Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks.
 Guni
            Sharon, Stephen D. Boyles, Shani
            Alkoby, and Peter Stone.
 In Proceedings of the 18th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS-19), May 2019.
 Details
                  
               BibTeX
                  
            Download: 
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               (1.7MB
               )
                [slides.pptx]
               (6.5MB
               )
- Agents teaching agents: a survey on inter-agent transfer learning.
 Felipe Leno
            Da Silva, Garrett Warnell, Anna
            Helena Reali Costa, and Peter Stone.
 Autonomous Agents and Multi-Agent
            Systems, Dec 2019.
 Official version from JAAMAS
 Details
                  
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            Download: 
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               (572.4kB
               )
- Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games.
 Felipe
            Leno Da Silva, Anna Helena Reali Costa, and Peter
            Stone.
 In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
 Details
                  
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            Download: 
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               (1.6MB
               )
- Improving Grounded Natural Language Understanding through Human-Robot Dialog.
 Jesse
            Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick
            Walker, Yuqian Jiang, Harel
            Yedidsion, Justin Hart, Peter Stone,
            and Raymond Mooney.
 In Proceedings of the International Conference on
            Robotics and Automation (ICRA 2019), May 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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            Download: 
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               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
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            Download: 
            [pdf]
               (6.1MB
               )
- Desiderata for Planning Systems in General-Purpose Service Robots.
 Nick Walker,
            Yuqian Jiang, Maya Cakmak, and
            Peter Stone.
 In Proceedings of the ICAPS Workshop on Planning and Robotics
            (PlanRob 2019), July 2019.
 Details
                  
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            Download: 
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               (651.5kB
               )
- Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance.
 Harel
            Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter
            Stone, and Raymond Mooney.
 In International Conference on Social
            Robotics (ICSR), pp. 133–143, November 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (958.6kB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
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            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems.
 Stefano
            Albrecht and Peter Stone.
 Artificial Intelligence, 258:66–95,
            Elsevier, 2018.
 Available from the publisher's webpage and
            arXiv
 Details
                  
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            Download: 
            [pdf]
               (670.7kB
               )
- Multi-modal Predicate Identification using Dynamically Learned Robot Controllers.
 Saeid Amiri, Suhua Wei, Shiqi
            Zhang, Jivko Sinapov, Jesse Thomason,
            and Peter Stone.
 In Proceedings of the 27th International Joint Conference
            on Artificial Intelligence (IJCAI-18), July 2018.
 Details
                  
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            Download: 
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               (2.5MB
               )
- DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation.
 Haipeng
            Chen, Bo An, Guni Sharon, Josiah
            P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh.
 In Proceedings
            of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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               (2.4MB
               )
                [ps]
               (5.9MB
               )
- Passive Demonstrations of Light-Based Robot Signals for Improved Human Interpretability.
 Rolando Fernandez, Nathan
            John, Sean Kirmani, Justin Hart, Jivko
            Sinapov, and Peter Stone.
 In Proceedings of the 27th IEEE International
            Symposium on Robot and Human Interactive Communication (RO-MAN), August 2018.
 Details
                  
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            Download: 
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               (8.5MB
               )
                [slides.pdf]
               (983.4kB
               )
- Towards a Data Efficient Off-Policy Policy Gradient.
 Josiah Hanna
            and Peter Stone.
 In AAAI Spring Symposium on Data Efficient Reinforcement
            Learning, March 2018.
 Details
                  
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               (345.4kB
               )
- PRISM:  Pose  Registration  for  Integrated  Semantic  Mapping.
 Justin W. Hart,
            Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter
            Stone.
 In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
            October 2018.
 Details
                  
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            Download: 
            [pdf]
               (4.4MB
               )
- Inferring User Intention using Gaze in Vehicles.
 Yu-Sian Jiang, Garrett
            Warnell, and Peter Stone.
 In The 20th ACM International Conference
            on Multimodal Interaction (ICMI), October 2018.
 Based on an earlier version presented at the AAAI
            PAIR workshop
 Details
                  
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               (2.6MB
               )
- A Study of Human-Robot Copilot Systems for En-Route Destination Changing.
 Yu-Sian Jiang, Garrett
            Warnell, Eduardo Munera, and Peter Stone.
 In Proceedings of the 27th
            IEEE International Conference on Robot and Human Interactive Communication (RO-MAN2018), August 2018.
 Available
            from RO-MAN
 Details
                  
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            Download: 
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               (5.8MB
               )
                [slides.pptx]
               (32.7MB
               )
- A Stitch in Time - Autonomous Model Management via Reinforcement Learning.
 Elad
            Liebman, Eric Zavesky, and Peter Stone.
 In Proceedings of the 17th
            International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018.
 Details
                  
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               (1.7MB
               )
- On the Impact of Music on Decision Making in Cooperative Tasks.
 Elad
            Liebman, Corey N. White, and Peter
            Stone.
 In 19th International Society for Music Information retrieval Conference (ISMIR), September 2018.
 Details
                  
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            Download: 
            [pdf]
               (258.5kB
               )
- State Abstraction Synthesis for Discrete Models of Continuous Domains.
 Jacob
            Menashe and Peter Stone.
 In Data Efficient Reinforcement Learning
            Workshop at AAAI Spring Symposium, March 2018.
 Details
                  
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            Download: 
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               (538.3kB
               )
                [ps]
               (5.3MB
               )
- Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science.
 Decebal Constantin Mocanu, Elena
            Mocanu, Peter Stone, Phuong
            H. Nguyen, Madeleine Gibescu, and Antonio
            Liotta.
 Nature Communications, 9(2383), June 2018.
 Official version from Publisher's
            Webpage.
 Details
                  
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               (1.5MB
               )
- Deterministic Implementations for Reproducibility in Deep Reinforcement Learning.
 Prabhat Nagarajan, Garrett
            Warnell, and Peter Stone.
 In 2nd Reproducibility in Machine Learning
            Workshop at ICML 2018, July 2018.
 Details
                  
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               (6.6MB
               )
- Variety Wins: Soccer-Playing Robots and Infant Walking.
 Ori Ossmy, Justine E. Hoch, Patrick
            MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph.
 Frontiers
            in Neurorobotics, 12:19, 2018.
 Available from the publisher's
            webpage
 Details
                  
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               (2.9MB
               )
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
 Tarun
            Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
            and Peter Stone.
 Transportation Research Part B: Methodological,
            110:104–21, 2018.
 Official version from Publisher's
            Webpage
 Details
                  
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               (1.6MB
               )
- Traffic Optimization For a Mixture of Self-interested and Compliant Agents.
 Guni
            Sharon, Michael Albert, Tarun
            Rambha, Stephen Boyles, and Peter
            Stone.
 In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
 Details
                  
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            Download: 
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               (1002.7kB
               )
                [ps]
               (5.2MB
               )
                [slides.pptx]
               (11.1MB
               )
- Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions.
 Jesse
            Thomason, Jivko Sinapov, Raymond
            J. Mooney, and Peter Stone.
 In Proceedings of the 32nd Conference
            on Artificial Intelligence (AAAI), February 2018.
 Details
                  
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            Download: 
            [pdf]
               (1.4MB
               )
- Deep TAMER: Interactive agent shaping in high-dimensional state spaces.
 Garrett
            Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone.
 In Proceedings
            of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2018.
 Details
                  
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            Download: 
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               (1.6MB
               )
                [slides.pptx]
               (16.2MB
               )
- Reasoning about Hypothetical Agent Behaviours and their Parameters.
 Stefano Albrecht
            and Peter Stone.
 In Proceedings of the 16th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
 Available from IFAAMAS
            and from ACM
 Details
                  
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            Download: 
            [pdf]
               (608.2kB
               )
                [slides.pdf]
               (1.2MB
               )
- TD Learning with Constrained Gradients.
 Ishan Durugkar and Peter
            Stone.
 In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017, December 2017.
 Details
                  
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            Download: 
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               (381.4kB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            Hanna, Philip Thomas, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
 Details
                  
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            Download: 
            [pdf]
               (1.2MB
               )
                [slides.pdf]
               (1.1MB
               )
- Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
 Josiah
            Hanna, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2017.
 Details
                  
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            Download: 
            [pdf]
               (663.8kB
               )
                [ps]
               (572.6kB
               )
                [slides.pdf]
               (1.3MB
               )
- Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests.
 Piyush
            Khandelwal and Peter Stone.
 In International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2017.
 Details
                  
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            Download: 
            [pdf]
               (1.8MB
               )
- Iterative Human-Aware Mobile Robot Navigation.
 Shih-Yun Lo, Benito Fernandez, and Peter
            Stone.
 In Proceedings of the Human-Centered Robotics workshop of the 13th International Conference on Robotics:
            Science and System (RSS), July 2017.
 Details
                  
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            Download: 
            [pdf]
               (2.0MB
               )
- Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges.
 Patrick
            MacAlpine and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 168–86, Springer International Publishing, 2017.
 Details
                  
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            Download: 
            [pdf]
               (518.7kB
               )
                [ps]
               (2.6MB
               )
                [slides.pdf]
               (45.5MB
               )
- Fast and Precise Black and White Ball Detection for RoboCup Soccer.
 Jacob
            Menashe, Josh Kelle, Katie Genter, Josiah
            Hanna, Elad Liebman, Sanmit
            Narvekar, Ruohan Zhang, and Peter
            Stone.
 In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
 Details
                  
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            Download: 
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               (254.2kB
               )
                [ps]
               (716.1kB
               )
                [slides.pdf]
               (1.5MB
               )
- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
 Sanmit
            Narvekar, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
            2017.
 Details
                  
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            Download: 
            [pdf]
               (826.2kB
               )
                [slides.pdf]
               (5.8MB
               )
- Network-wide Adaptive Tolling for Connected and Automated vehicles.
 Guni
            Sharon, Michael W. Levin, Josiah
            P. Hanna, Tarun Rambha, Stephen
            D. Boyles, and Peter Stone.
 Transportation Research Part C, 84:142–157,
            September 2017.
 Transportation Research Part C.
 Audio slides.
 Contains material
            that was previously published in an AAMAS-17 paper.
 Details
                  
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            Download: 
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               (2.8MB
               )
                [ps]
               (4.2MB
               )
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
 Guni
            Sharon and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
 Details
                  
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            Download: 
            [pdf]
               (1.1MB
               )
                [ps]
               (7.1MB
               )
                [slides.pptx]
               (140.9MB
               )
- Multirobot Symbolic Planning under Temporal Uncertainty.
 Shiqi Zhang,
            Yuqian Jiang, Guni Sharon, and Peter
            Stone.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS),
            May 2017.
 Accompanying videos at https://youtu.be/ADbH3sppLHQ
 Details
                  
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            Download: 
            [pdf]
               (2.3MB
               )
Toyota
      
      
         - Reducing Sampling Error in Policy Gradient Learning.
 Josiah Hanna
            and Peter Stone.
 In Proceedings of the 18th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS), May 2019.
 This paper contains material that was previously
            presented at the 2018 NeurIPS Deep Reinforcement Learning Workshop.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
                [slides.pdf]
               (3.1MB
               )
- Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science.
 Decebal Constantin Mocanu, Elena
            Mocanu, Peter Stone, Phuong
            H. Nguyen, Madeleine Gibescu, and Antonio
            Liotta.
 Nature Communications, 9(2383), June 2018.
 Official version from Publisher's
            Webpage.
 Details
                  
               BibTeX
                  
            Download: 
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               (1.5MB
               )
- Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty.
 Tarun
            Rambha, Stephen D. Boyles, Avinash Unnikrishnan,
            and Peter Stone.
 Transportation Research Part B: Methodological,
            110:104–21, 2018.
 Official version from Publisher's
            Webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Reasoning about Hypothetical Agent Behaviours and their Parameters.
 Stefano Albrecht
            and Peter Stone.
 In Proceedings of the 16th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
 Available from IFAAMAS
            and from ACM
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (608.2kB
               )
                [slides.pdf]
               (1.2MB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            Hanna, Philip Thomas, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
                [slides.pdf]
               (1.1MB
               )
- Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
 Josiah
            Hanna, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (663.8kB
               )
                [ps]
               (572.6kB
               )
                [slides.pdf]
               (1.3MB
               )
- Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests.
 Piyush
            Khandelwal and Peter Stone.
 In International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
 Sanmit
            Narvekar, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
            2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (826.2kB
               )
                [slides.pdf]
               (5.8MB
               )
- Network-wide Adaptive Tolling for Connected and Automated vehicles.
 Guni
            Sharon, Michael W. Levin, Josiah
            P. Hanna, Tarun Rambha, Stephen
            D. Boyles, and Peter Stone.
 Transportation Research Part C, 84:142–157,
            September 2017.
 Transportation Research Part C.
 Audio slides.
 Contains material
            that was previously published in an AAMAS-17 paper.
 Details
                  
               BibTeX
                  
            Download: 
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               (2.8MB
               )
                [ps]
               (4.2MB
               )
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
 Guni
            Sharon and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [ps]
               (7.1MB
               )
                [slides.pptx]
               (140.9MB
               )
- Multirobot Symbolic Planning under Temporal Uncertainty.
 Shiqi Zhang,
            Yuqian Jiang, Guni Sharon, and Peter
            Stone.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS),
            May 2017.
 Accompanying videos at https://youtu.be/ADbH3sppLHQ
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.3MB
               )
ATT
      
      
         - Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Reasoning about Hypothetical Agent Behaviours and their Parameters.
 Stefano Albrecht
            and Peter Stone.
 In Proceedings of the 16th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
 Available from IFAAMAS
            and from ACM
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (608.2kB
               )
                [slides.pdf]
               (1.2MB
               )
- Data-Efficient Policy Evaluation Through Behavior Policy Search.
 Josiah
            Hanna, Philip Thomas, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
                [slides.pdf]
               (1.1MB
               )
- Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
 Josiah
            Hanna, Peter Stone, and Scott
            Niekum.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (663.8kB
               )
                [ps]
               (572.6kB
               )
                [slides.pdf]
               (1.3MB
               )
- Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests.
 Piyush
            Khandelwal and Peter Stone.
 In International Conference on Autonomous
            Agents and Multiagent Systems (AAMAS), May 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
- Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
 Sanmit
            Narvekar, Jivko Sinapov, and Peter
            Stone.
 In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August
            2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (826.2kB
               )
                [slides.pdf]
               (5.8MB
               )
- A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections.
 Guni
            Sharon and Peter Stone.
 In Gita Sukthankar and Juan
            A. Rodriguez-Aguilar, editors, Autonomous Agents and Multiagent Systems - AAMAS 2017 Workshops, Best Papers, Lecture
            Notes in Artificial Intelligence, pp. 151–67, Springer International Publishing, 2017.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [ps]
               (7.1MB
               )
                [slides.pptx]
               (140.9MB
               )
- Multirobot Symbolic Planning under Temporal Uncertainty.
 Shiqi Zhang,
            Yuqian Jiang, Guni Sharon, and Peter
            Stone.
 In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS),
            May 2017.
 Accompanying videos at https://youtu.be/ADbH3sppLHQ
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.3MB
               )
Alexander von Humboldt Foundation
      
      
         - Imitation Learning from Video by Leveraging Proprioception.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pptx]
               (20.3MB
               )
- Recent Advances in Imitation Learning from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August
            2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (157.4kB
               )
                [slides.pptx]
               (45.5MB
               )
- Generative Adversarial Imitation from Observation.
 Faraz Torabi,
            Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.0MB
               )
- Sample-efficient Adversarial Imitation Learning from Observation.
 Faraz
            Torabi, Sean Geiger, Garrett Warnell, and Peter
            Stone.
 In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.1MB
               )
- Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
 Ruohan
            Zhang, Faraz Torabi, Lin Guan, Dana
            H. Ballard, and Peter Stone.
 In Proceedings of the 28th International
            Joint Conference on Artificial Intelligence (IJCAI), August 2019.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (471.1kB
               )
                [slides.pdf]
               (1.2MB
               )
- Reasoning about Hypothetical Agent Behaviours and their Parameters.
 Stefano Albrecht
            and Peter Stone.
 In Proceedings of the 16th International Conference
            on Autonomous Agents and Multiagent Systems (AAMAS-17), May 2017.
 Available from IFAAMAS
            and from ACM
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (608.2kB
               )
                [slides.pdf]
               (1.2MB
               )
Bosch
      
      
         - Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks.
 Viraj Joshi, Zifan
            Xu, Bo Liu, Peter Stone, and
            Amy Zhang.
 In Reinforcement Learning Conference (RLC), August 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.5MB
               )
- Learning to Look: Seeking Information for Decision Making via Policy Factorization.
 Shivin Dass, Jiaheng
            Hu, Ben Abbatematteo, Peter Stone, and Roberto Martín-Martín.
 In Conference
            on Robot Learning (CoRL), November 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.8MB
               )
- Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning.
 Haresh,
            Karnan; Elvin, Yang; Garrett, Warnell; Joydeep, Biswas; Peter, and Stone.
 In
            International Conference on Robotics and Automation, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.3MB
               )
- Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning.
 Jiaheng
            Hu, Zizhao Wang, Roberto Martín-Martín, and Peter
            Stone.
 In Conference on Neural Information Parocessing Systems (NeurIPS), December 2024.
 Details
                  
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            Download: 
            [pdf]
               (2.7MB
               )
- Learning Optimal Advantage from Preferences and Mistaking it for Reward.
 W. Bradley
            Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson, Serena Booth, Anca Dragan, Peter
            Stone, and Scott Niekum.
 In The 38th Annual AAAI Conference on Artificial
            Intelligence (AAAI), February 2024.
 Details
                  
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            Download: 
            [pdf]
               (3.6MB
               )
                [slides.pdf]
               (3.9MB
               )
                [poster.pdf]
               (2.9MB
               )
- Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds.
 Amir Hossain Raj, Zichao
            Hu, Haresh Karnan, Rohan Chandra,
            Amirreza Payandeh, Luisa Mao, Peter Stone, Joydeep
            Biswas, and and Xuesu Xiao.
 In International Conference on Robotics
            and Automation, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
- The Human in the Loop: Perspectives and Challenges for RoboCup 2050.
 Alessandra Rossi, Maike Paetzel-Prüsmann,
            Merel Keijsers, Michael Anderson, Susan Leigh Anderson, Daniel Barry, Jan Gutsche, Justin
            Hart, Luca Iocchi, Ainse Kokkelmans, Wouter Kuijpers, Yun Liu, Daniel
            Polani, Caleb Roscon, Marcus Scheunemann, Peter Stone, Florian Vahl, René
            van de Molengraft, and Oskar von Stryk.
 Autonomous
            Robots, May 2024.
 Official version on publisher's website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- Relaxed Exploration Constrained Reinforcement Learning.
 Shahaf S. Shperberg, Bo
            Liu, and Peter Stone.
 In Conference on Autonomous Agents and Multiagent
            Systems, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
- Dobby: A Conversational Service Robot Driven by GPT-4.
 Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi,
            Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, and Justin
            Hart.
 In International Symposium on Robot and Human Interactive Communication (RO-MAN), January 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (863.8kB
               )
                [poster.pdf]
               (892.0kB
               )
- Asynchronous Task Plan Refinement for Multi-Robot Task and Motion Planning.
 Yoonchang
            Sung, Rahul Shome, and Peter Stone.
 In IEEE International Conference
            on Robotics and Automation (ICRA), March 2024.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (482.7kB
               )
- Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes.
 Chen
            Tang, Ben Abbatematteo, Jiaheng Hu, Rohan
            Chandra, Roberto Martín-Martín, and Peter Stone.
 Annual Review
            of Control, Robotics, and Autonomous Systems (ARCRAS), 8:153–88, 2024.
 Presented in Senior member track at
            AAAI 2025
 Official
            version on publisher's website
 Details
                  
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            Download: 
            [pdf]
               (4.3MB
               )
                [slides.pdf]
               (2.9MB
               )
                [poster.pdf]
               (604.3kB
               )
- Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning.
 Zizhao
            Wang, Caroline Wang, Xuesu
            Xiao, Yuke Zhu, and Peter Stone.
 In
            AAAI Conference on Artificial Intelligence, February 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.5MB
               )
- Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks.
 Ziping Xu, Zifan
            Xu, Runxuan Jiang, Peter Stone, and Ambuj
            Tewari.
 In International Conference on Learning Representations (ICLR), May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
- Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning.
 Zifan
            Xu, Amir Hossain Raj, Xuesu Xiao, and Peter
            Stone.
 In IEEE International Conference on Robotics and Automation, May 2024.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.0MB
               )
- t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making.
 William Yue,
            Bo Liu, and Peter Stone.
 In
            Conference on Lifelong Learning Agents (CoLLAs), July 2024.
 Details
                  
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            Download: 
            [pdf]
               (599.7kB
               )
                [poster.pdf]
               (709.1kB
               )
- f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences.
 Siddhant Agarwal, Ishan
            Durugkar, Peter Stone, and Amy Zhang.
 In Conference on Neural Information
            Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (13.6MB
               )
                [poster.pdf]
               (1.8MB
               )
- The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications.
 Serena
            Booth, W Bradley Knox, Julie Shah, Scott
            Niekum, Peter Stone, and Alessandro Allievi.
 In Proceedings of the
            37th AAAI Conference on Artificial Intelligence (AAAI), Feb 2023.
 Project
            page with slides and video.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
- "What's That Robot Doing Here?": Factors Influencing Perceptions Of Incidental Encounters With Autonomous Quadruped Robots.
 Elliott
            Hauser, Yao-Cheng Chan, Geethika Hemkumar, Daksh Dua, Parth Chonkar, Efren Mendoza Enriquez, Tiffany Kao, Shikhar Gupta, Huihai
            Wang, Justin Hart, Reuth Mirsky,
            Joydeep Biswas, Junfeng Jiao, and Peter
            Stone.
 In Proceedings of the First International Symposium on Trustworthy Autonomous Systems (TAS '23), pp.
            1–15, July 2023.
 Available online at https://dl.acm.org/doi/10.1145/3597512.3599707
 Details
                  
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            Download: 
            
            (unavailable)
- Causal Policy Gradient for Whole-Body Mobile Manipulation.
 Jiaheng Hu,
            Peter Stone, and Roberto Martin-Martin.
 In Robotics: Science and Systems
            (RSS), July 2023.
 Details
                  
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            Download: 
            [pdf]
               (4.0MB
               )
- VaryNote: A Method to Automatically Vary the Number of Notes in           Symbolic Music.
 Juan M. Huerta, Bo
            Liu, and Peter Stone.
 In The 16th International Symposium on Computer
            Music Multidisciplinary Research, (CMMR), Springer, November 2023.
 the
            conference presentation
 Details
                  
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            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pdf]
               (2.3MB
               )
- STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experience.
 Haresh
            Karnan, Elvin Yang, Daniel Farkash, Garrett
            Warnell, Joydeep Biswas, and Peter
            Stone.
 In The Conference on Robot Learning (CoRL), November 2023.
 Poster,
            Video, Project Website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (25.7MB
               )
- Models of human preference for learning reward functions.
 W. Bradley Knox,
            Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter
            Stone, and Alessandro Allievi.
 Transactions on Machine Learning Research (TMLR), 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.7MB
               )
                [slides.pdf]
               (13.4MB
               )
- Reward (Mis)design for Autonomous Driving.
 W. Bradley Knox, Alessandro Allievi,
            Holger Banzhaf, Felix Schmitt, and Peter Stone.
 Artificial Intelligence,
            316:103829, 2023.
 Paper webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (696.3kB
               )
                [ps]
               (5.6MB
               )
- FAMO: Fast Adaptive Multitask Optimization.
 Bo Liu, Yihao Feng, Peter Stone, and Qiang Liu.
 In Neural Information Processing Systems Foundation,
            July 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.0MB
               )
- LIBERO: Benchmarking Knowledge Transfer in Lifelong Robot Learning.
 Bo
            Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke
            Zhu, and Peter Stone.
 In 37th Conference on Neural Information Processing
            Systems (NeurIPS 2023) Track on Datasets and Benchmarks, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (37.6MB
               )
                [poster.pdf]
               (2.6MB
               )
- Exploring the Cost of Interruptions in Human-Robot Teaming.
 Swathi Mannem, William
            Macke, Peter Stone, and Reuth
            Mirsky.
 In IEEE-RAS Humanoids, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (921.5kB
               )
                [poster.pdf]
               (294.3kB
               )
- Towards a Real-Time, Low-Resource, End-to-end Object Detection Pipeline for Robot Soccer.
 Sai Kiran Narayanaswami,
            Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit
            Narvekar, and Peter Stone.
 In Amy Eguchi, Nuno Lau, Maike Paetzel-Prussman,
            and Thanapat Wanichanon, editors, RoboCup 2022: Robot World Cup XXV, pp. 62–74, Springer International Publishing,
            2023.
 The book
 Details
                  
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            Download: 
            [pdf]
               (572.2kB
               )
- Program Embeddings for Rapid Mechanism Evaluation.
 Sai Kiran Narayanaswami, David Fridovich-Keil, Swarat Chaudhuri,
            and Peter Stone.
 In ICRA Workshop on Multi-Robot Learning, May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.3MB
               )
                [poster.pdf]
               (916.2kB
               )
- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
 Jinsoo Park, Xuesu
            Xiao, Garrett Warnell, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 6-minute video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.6MB
               )
                [slides.pptx]
               (21.3MB
               )
                [poster.pdf]
               (1.1MB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
- Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search.
 Yoonchang
            Sung and Peter Stone.
 In Robotics: Science and Systems (RSS2023),
            July 2023.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.9MB
               )
                [slides.pdf]
               (8.1MB
               )
                [poster.pdf]
               (6.9MB
               )
- ELDEN: Exploration via Local Dependencies.
 Zizhao Wang, Jiaheng
            Hu, Peter Stone, and Roberto Martín-Martín.
 In Conference on Neural
            Information Processing Systems, December 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.2MB
               )
                [slides.pptx]
               (22.4MB
               )
                [poster.pdf]
               (856.5kB
               )
- D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning.
 Caroline
            Wang, Garrett Warnell, and Peter
            Stone.
 In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
                [slides.pdf]
               (2.4MB
               )
                [poster.pdf]
               (1.4MB
               )
- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
 Caroline
            Wang, Ishan Durugkar, Elad Liebman,
            and Peter Stone.
 In Proceedings of the 37th AAAI Conference on Artificial
            Intelligence (AAAI-23), February 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (801.2kB
               )
                [slides.pdf]
               (3.7MB
               )
                [poster.pdf]
               (1.4MB
               )
- Learning Real-world Autonomous Navigation by Self-Supervised Environment Synthesis.
 Zifan
            Xu, Anirudh Nair, Xuesu Xiao, and Peter
            Stone.
 In IROS Workshop on Photorealistic Image and Environment Synthesis for Robotics (PIES-Rob) , January
            2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.3MB
               )
- Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.
 Xiaohan Zhang, Saeid Amiri,
            Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
 Autonomous
            Robots, March 2023.
 Official version
            on publisher's website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.6MB
               )
- Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu,
            Peter Stone, and Shiqi Zhang.
 In
            International Conference on Intelligent Robots and Systems (IROS), October 2023.
 Project
            website (includes poster and 5-minute video presentation)
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
                [slides.pdf]
               (6.6MB
               )
- Learning Generalizable Manipulation Policies with Object-Centric 3D Representations.
 Yifeng
            Zhu, Zhenyu Jiang, Peter Stone, and Yuke
            Zhu.
 In Conference on Robot Learning (CoRL), November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (7.3MB
               )
                [poster.pdf]
               (5.2MB
               )
- Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles.
 Jiaxun
            Cui, Hang Qiu, Dian Chen, Peter
            Stone, and Yuke Zhu.
 In IEEE/CVF Conference on Computer Vision and
            Pattern Recognition (CVPR), June 2022.
 Project website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.5MB
               )
- Quantifying Human Rationality in Ad-hoc Teamwork.
 Yair Hanina, Reuth
            Mirsky, William Macke, and Peter
            Stone.
 In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (404.2kB
               )
- Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch.
 Eddy Hudson, Garrett
            Warnell, Faraz Torabi, and Peter
            Stone.
 In International Conference on Robotics and Automation (ICRA), May 2022.
 Presentation
            Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.5MB
               )
- Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation.
 Haresh Karnan, Anirudh Nair, Xuesu Xiao,
            Garrett Warnell, Soren Pirk, Alexander Toshev, Justin
            Hart, Joydeep Biswas, and Peter Stone.
 Robotics
            and Automation Letters (RA-L), 2022, 7:11807–14, October 2022.
 Dataset;
            Poster; Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
- VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics.
 Haresh
            Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett
            Warnell, Peter Stone, and Joydeep Biswas.
 In
            International Conference on Intelligent Robots and Systems, 2022, October 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.0MB
               )
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation.
 Haresh
            Karnan, Garrett Warnell, Xuesu
            Xiao, and Peter Stone.
 In International Conference on Robotics and
            Automation, 2022, May 2022.
 Poster,
            Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
- Adversarial Imitation Learning from Video using a State Observer.
 Haresh
            Karnan, Garrett Warnell, Faraz
            Torabi, and Peter Stone.
 In International Conference on Robotics
            and Automation, 2022, May 2022.
 Video
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (933.2kB
               )
- BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.
 Bo
            Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu.
 In Conference
            on Neural Information Processing Systems, 2022, December 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (1.6MB
               )
                [poster.pdf]
               (885.6kB
               )
- Value Function Decomposition for Iterative Design of Reinforcement Learning Agents.
 James MacGlashan, Evan Archer,
            Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2022.
 5-minute
            Video Presentation; the
            slides
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (11.6MB
               )
- A Survey of Ad Hoc Teamwork Research.
 Reuth Mirsky, Ignacio
            Carlucho, Arrasy Rahman, Eliott Fosong, William
            Macke, Mohan Sridharan, Peter
            Stone, and Stefano Albrecht.
 In Baumeister, Dorothea and Rothe, Jörg, editors,
            Multi-Agent Systems, pp. 275–93, Springer International Publishing, Cham, 2022.
 Details
                  
               BibTeX
                  
            Download: 
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               (198.8kB
               )
- Task Factorization in Curriculum Learning.
 Reuth Mirsky,
            Shahaf S. Shperberg, Yulin Zhang, Zifan
            Xu, Yuqian Jiang, Jiaxun Cui, and Peter
            Stone.
 In ICML workshop on Decision Awareness in Reinforcement Learning (DARL), July 2022.
 recorded
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1011.6kB
               )
- Dynamic Sparse Training for Deep Reinforcement Learning.
 Ghada Sokar, Elena
            Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy,
            and Peter Stone.
 In Proceedings of the 31st International Joint Conference
            on Artificial Intelligence, July 2022.
 arXiv version with the appendix
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.7MB
               )
                [slides.pptx]
               (16.7MB
               )
- Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning.
 Yoonchang
            Sung, Zizhao Wang, and Peter Stone.
 In
            Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (742.0kB
               )
                [poster.pdf]
               (5.7MB
               )
- Causal Dynamics Learning for Task-Independent State Abstraction.
 Zizhao
            Wang, Xuesu Xiao, Zifan Xu, Yuke
            Zhu, and Peter Stone.
 In Proceedings of the 39th International Conference
            on Machine Learning (ICML2022), July 2022.
 recorded presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (4.0MB
               )
                [poster.pdf]
               (1.6MB
               )
- Visually Grounded Task and Motion Planning for Mobile Manipulation.
 Xiaohan Zhang, Yifeng
            Zhu, Yan Ding, Yuke Zhu, Peter
            Stone, and Shiqi Zhang.
 In International Conference on Robotics
            and Automation (ICRA), May 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
- Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation.
 Yifeng
            Zhu, Peter Stone, and Yuke
            Zhu.
 IEEE Robotics and Automation Letters (RA-L), 7:4126–33, April 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.3MB
               )
- VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors.
 Yifeng
            Zhu, Abhishek Joshi, Peter Stone, and Yuke
            Zhu.
 In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), December 2022.
 Project page
 Code
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.4MB
               )
- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
 Michael
            Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
 Operations
            Research, March 2021.
 Details
                  
               BibTeX
                  
            Download: 
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               (692.5kB
               )
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
 Roberto Capobianco, Varun Kompella, James
            Ault, Guni Sharon, Stacy
            Jong, Spencer Fox, Lauren
            Meyers, Peter R. Wurman, and Peter
            Stone.
 The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
 Contains
            material that was previously published in an AAMAS
            2021 paper and a AAAI 2020 Fall
            Symposium paper.
 Article available from  JAIR website.
 Simulator
            source code.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
 Jiaxun
            Cui, William Macke, Harel
            Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
            Stone.
 In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2021.
 Project page, with videos
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pptx]
               (1.5MB
               )
- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
 Yunshu Du, Garrett
            Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
            E. Taylor.
 Neural Computing and Applications, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
- Adversarial Intrinsic Motivation for Reinforcement Learning.
 Ishan Durugkar,
            Mauricio Tec, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
            December 2021.
 slides and video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.1MB
               )
- Capturing Skill State in Curriculum Learning for Human Skill Acquisition.
 Keya
            Ghonasgi, Reuth Mirsky, Sanmit
            Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D.
            Deshpande.
 In International Conference on Intelligent Robots and Systems (IROS), September 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Machine versus Human Attention in Deep Reinforcement Learning Tasks.
 Sihang Guo, Ruohan
            Zhang, Bo Liu, Yifeng Zhu,
            Mary Hayhoe, Dana Ballard, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Grounded Action Transformation for Sim-to-Real Reinforcement Learning.
 Josiah
            P. Hanna, Siddharth Desai, Haresh Karnan, Garrett
            Warnell, and Peter Stone.
 Special Issue on Reinforcement Learning
            for Real Life, Machine Learning, 2021, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.0MB
               )
- Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy.
 Josiah
            P. Hanna, Scott Niekum, and Peter
            Stone.
 Machine Learning (MLJ), 110:1267–1317, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.7MB
               )
- Incorporating Gaze into Social Navigation.
 Justin Hart, Reuth
            Mirsky, Xuesu Xiao, and Peter
            Stone.
 In RSS Workshop on Social Robot Navigation, July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
                [slides.pdf]
               (3.5MB
               )
- Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation.
 Blake Holman, Abrar
            Anwar, Akash Singh, Mauricio Tec, Justin
            Hart, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.7MB
               )
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
 Eddy Hudson, Garrett
            Warnell, and Peter Stone.
 In Autonomous Robots and Multirobot Systems
            Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (393.0kB
               )
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
 Yuqian
            Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
 In
            Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
                [slides.pdf]
               (1.8MB
               )
- A Lifelong Learning Approach to Mobile Robot Navigation.
 Bo Liu, Xuesu Xiao, and Peter Stone.
 IEEE
            Robotics and Automation Letters (RA-L), 6(2), April 2021.
 Presented at IEEE International Conference on Robotics
            and Automation (ICRA),
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.6MB
               )
- Conflict-Averse Gradient Descent for Multi-task learning.
 Bo Liu, Xingchao
            Liu, Xiaojie Jin, Peter Stone, and Qiang Liu.
 In Conference on Neural
            Information Processing Systems (NeurIPS), 2021, December 2021.
 slides
            and 9-minute presentation
 github repository
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.7MB
               )
- Team  Orienteering  Coverage  Planning  with  Uncertain  Reward.
 Bo Liu,
            Xuesu Xiao, and Peter Stone.
 In
            International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.9MB
               )
- Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition.
 Bo
            Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke
            Zhu, and Animashree Anandkumar.
 In Proceedings of the 38th International Conference on Machine Learning, PMLR 139,
            2021 (ICML), July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
                [poster.pdf]
               (1.1MB
               )
- Expected Value of Communication for Planning in Ad Hoc Teamwork.
 William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (869.9kB
               )
                [slides.pdf]
               (2.3MB
               )
                [poster.pdf]
               (1.8MB
               )
- Is the Cerebellum a Model-Based Reinforcement Learning Agent?.
 Bharath Masetty, Reuth
            Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter
            Stone.
 In Adaptive and Learning Agents Workshop at AAMAS, May 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (594.9kB
               )
                [slides.pdf]
               (1.5MB
               )
- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
 Reuth
            Mirsky and Peter Stone.
 In ICSR workshop on Adaptive Social Interaction
            and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (194.4kB
               )
- The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care.
 Reuth
            Mirsky and Peter Stone.
 In Proceedings of the 20th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (679.2kB
               )
- Reasoning about Human Behavior in Ad Hoc Teamwork.
 Jennifer Suriadinata, William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
 Video
            Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (926.2kB
               )
- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (742.7kB
               )
- APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback.
 Zizhao
            Wang, Xuesu Xiao, Bo Liu,
            Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), October 2021.
 5-minute
            Video Presentation;  15-minute Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.1MB
               )
                [slides.pdf]
               (2.7MB
               )
- From Agile Ground to Aerial Navigation: Learning from Learned Hallucination.
 Zizhao
            Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika
            Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone.
 In Proceedings
            of the International Conference on Intelligent Robots and Systems (IROS 2021), October 2021.
 1-minute
            Video Summary;   15-minute Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.9MB
               )
                [slides.pdf]
               (2.7MB
               )
- APPLI: Adaptive Planner Parameter Learning From Interventions.
 Zizhao Wang,
            Xuesu Xiao, Bo Liu, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the International Conference
            on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
- APPLR: Adaptive Planner Parameter Learning from Reinforcement.
 Zifan Xu,
            Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett
            Warnell, Bo Liu, Zizhao Wang,
            and Peter Stone.
 In Proceedings of the 2021 IEEE International Conference
            on Robotics and Automation (ICRA 2021), June 2021.
 Video
            presentation
 Project webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (27.4MB
               )
- Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning.
 Zifan
            Xu, Xuesu Xiao, Garrett
            Warnell, Anirudh Nair, and Peter Stone.
 In Proceedings of the 2021
            IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), October 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.5MB
               )
- A Scavenger Hunt for Service Robots.
 Harel Yedidsion,
            Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
            Stone.
 In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
 Harel
            Yedidsion, Shani Alkoby, and Peter
            Stone.
 Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
 arXiv
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (478.9kB
               )
- Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks.
 Ruohan
            Zhang, Faraz Torabi, Garrett
            Warnell, and Peter Stone.
 Autonomous Agents and Multi-Agent Systems,
            35(31), June 2021.
 official online version
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.8MB
               )
- The EMPATHIC Framework for Task Learning from Implicit Human Feedback.
 Yuchen
            Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott
            Niekum, and W. Bradley Knox.
 In Proceedings of the 4th Conference on Robot
            Learning (CoRL 2020), November 2020.
 5-minute video presentation;
                       47-minute in-depth talk.
 Project website.
 Raw
            data from experiments.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (6.4MB
               )
                [slides.pptx]
               (59.4MB
               )
- An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch.
 Siddarth Desai, Ishan
            Durugkar, Haresh Karnan, Garrett
            Warnell, Josiah Hanna, and Peter
            Stone.
 In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020),
            December 2020.
 Poster
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.3MB
               )
- Stochastic Grounded Action Transformation for Robot Learning in Simulation.
 Siddharth Desai, Haresh
            Karnan, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 11-minute video
            presentation.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.9MB
               )
- Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
 Ishan
            Durugkar, Elad Liebman, and Peter
            Stone.
 In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July
            2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.9MB
               )
- Using Human-Inspired Signals to Disambiguate Navigational Intentions.
 Justin Hart,
            Reuth Mirsky, Xuesu Xiao,
            Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter
            Stone.
 In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.2MB
               )
- Reinforced Grounded Action Transformation for Sim-to-Real Transfer.
 Haresh
            Karnan, Siddharth Desai, Josiah P. Hanna, Garrett
            Warnell, and Peter Stone.
 In IEEE/RSJ International Conference on
            Intelligent Robots and Systems(IROS 2020), October 2020.
 14-minute video
            presentation.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (506.6kB
               )
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
 Shih-Yun Lo, Shiqi
            Zhang, and Peter Stone.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, October 2020.
 Contains material that was previously published in an AAMAS-18
            paper (awarded the Best Robotics Paper Award at AAMAS 2018)
 Also
            available from  JAIR website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
- Learning and Reasoning for Robot Dialog and Navigation Tasks.
 Keting Lu, Shiqi
            Zhang, Peter Stone, and Xiaoping
            Chen.
 In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp.
            107–117, Association for Computational Linguistics, 1st virtual meeting, July 2020.
 Official version from ACL
            Digital Library, including a link to the conference presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.6MB
               )
- A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork.
 Reuth
            Mirsky, William Macke, Andy Wang, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 29th International
            Joint Conference on Artificial Intelligence, July 2020.
 15-minute
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
                [slides.pdf]
               (1.4MB
               )
- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
 Sanmit
            Narvekar, Bei Peng, Matteo Leonetti, Jivko
            Sinapov, Matthew E. Taylor, and Peter
            Stone.
 Journal of Machine Learning Research, 21(181):1–50, 2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
- Generalizing Curricula for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In 4th Lifelong Learning Workshop at the International
            Conference on Machine Learning (ICML 2020), July 2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (330.4kB
               )
                [slides.pdf]
               (3.8MB
               )
- Learning to Improve Multi-Robot Hallway Navigation.
 Jin-Soo Park, Brian Tsang, Harel
            Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
 In Proceedings of the 4th Conference on Robot Learning (CoRL),
            November 2020.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.3MB
               )
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
 Brahma
            Pavse, Faraz Torabi, Josiah
            Hanna, Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
 Video
            of the experiments; 13-minute video presentation.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (405.1kB
               )
                [slides.pptx]
               (115.4MB
               )
- Reducing Sampling Error in Batch Temporal Difference Learning.
 Brahma Pavse,
            Ishan Durugkar, Josiah Hanna,
            and Peter Stone.
 In Proceedings of the 37th International Conference
            on Machine Learning (ICML), July 2020.
 The paper and talk is available from the ICML
            2020 virtual conference page.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (738.4kB
               )
                [slides.pdf]
               (5.2MB
               )
- On Sampling Error in Batch Action-Value Prediction Algorithms.
 Brahma S. Pavse,
            Josiah P. Hanna, Ishan Durugkar,
            and Peter Stone.
 In In the Offline Reinforcement Learning Workshop at
            Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
 5-minute
            Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (327.2kB
               )
- Deep R-Learning for Continual Area Sweeping.
 Rishi Shah, Yuqian Jiang, Justin
            Hart, and Peter Stone.
 In Proceedings of the IEEE/RSJ International
            Conference on Intelligent Robots and Systems (IROS 2020), October 2020.
 1-minute
            video demonstration; 13-minute Video
            presentation.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (374.2kB
               )
                [slides.pdf]
               (1.1MB
               )
- The right music at the right time: adaptive personalized playlists based on sequence modeling.
 Elad
            Liebman, Maytal Saar-Tsechansky, and Peter
            Stone Peter Stone.
 Management Information Systems Quarterly, 43(3):765–786, Society for Information Management
            and The Management Information Systems Research Center, 2019.
 Available from publisher's
            website.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
GM
      
      
         - Causal Policy Gradient for Whole-Body Mobile Manipulation.
 Jiaheng Hu,
            Peter Stone, and Roberto Martin-Martin.
 In Robotics: Science and Systems
            (RSS), July 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
- VaryNote: A Method to Automatically Vary the Number of Notes in           Symbolic Music.
 Juan M. Huerta, Bo
            Liu, and Peter Stone.
 In The 16th International Symposium on Computer
            Music Multidisciplinary Research, (CMMR), Springer, November 2023.
 the
            conference presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pdf]
               (2.3MB
               )
- Reward (Mis)design for Autonomous Driving.
 W. Bradley Knox, Alessandro Allievi,
            Holger Banzhaf, Felix Schmitt, and Peter Stone.
 Artificial Intelligence,
            316:103829, 2023.
 Paper webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (696.3kB
               )
                [ps]
               (5.6MB
               )
- Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways.
 Jinsoo Park, Xuesu
            Xiao, Garrett Warnell, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 2023 IEEE International
            Conference on Robotics and Automation (ICRA 2023), May 2023.
 6-minute video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.6MB
               )
                [slides.pptx]
               (21.3MB
               )
                [poster.pdf]
               (1.1MB
               )
- Visually Adaptive Geometric Navigation.
 Shravan Ravi, Gary Wang, Shreyas Satewar, Xuesu
            Xiao, Garrett Warnell, Joydeep
            Biswas, and Peter Stone.
 In IEEE International Symposium on Safety,Security,and
            Rescue Robotics, November 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
- DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching.
 Caroline
            Wang, Ishan Durugkar, Elad Liebman,
            and Peter Stone.
 In Proceedings of the 37th AAAI Conference on Artificial
            Intelligence (AAAI-23), February 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (801.2kB
               )
                [slides.pdf]
               (3.7MB
               )
                [poster.pdf]
               (1.4MB
               )
- Learning a robust multiagent driving policy for traffic congestion reduction.
 Yulin
            Zhang, William Macke, Jiaxun Cui,
            Sharon Hornstein, Daniel Urieli, and Peter
            Stone.
 Neural Computing and Applications, 2023.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
- Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.
 Xiaohan Zhang, Saeid Amiri,
            Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang.
 Autonomous
            Robots, March 2023.
 Official version
            on publisher's website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.6MB
               )
- Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles.
 Jiaxun
            Cui, Hang Qiu, Dian Chen, Peter
            Stone, and Yuke Zhu.
 In IEEE/CVF Conference on Computer Vision and
            Pattern Recognition (CVPR), June 2022.
 Project website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.5MB
               )
- Quantifying Human Rationality in Ad-hoc Teamwork.
 Yair Hanina, Reuth
            Mirsky, William Macke, and Peter
            Stone.
 In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), May 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (404.2kB
               )
- BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach.
 Bo
            Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu.
 In Conference
            on Neural Information Processing Systems, 2022, December 2022.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (1.6MB
               )
                [poster.pdf]
               (885.6kB
               )
- Value Function Decomposition for Iterative Design of Reinforcement Learning Agents.
 James MacGlashan, Evan Archer,
            Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2022.
 5-minute
            Video Presentation; the
            slides
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (11.6MB
               )
- A Survey of Ad Hoc Teamwork Research.
 Reuth Mirsky, Ignacio
            Carlucho, Arrasy Rahman, Eliott Fosong, William
            Macke, Mohan Sridharan, Peter
            Stone, and Stefano Albrecht.
 In Baumeister, Dorothea and Rothe, Jörg, editors,
            Multi-Agent Systems, pp. 275–93, Springer International Publishing, Cham, 2022.
 Details
                  
               BibTeX
                  
            Download: 
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               (198.8kB
               )
- Task Factorization in Curriculum Learning.
 Reuth Mirsky,
            Shahaf S. Shperberg, Yulin Zhang, Zifan
            Xu, Yuqian Jiang, Jiaxun Cui, and Peter
            Stone.
 In ICML workshop on Decision Awareness in Reinforcement Learning (DARL), July 2022.
 recorded
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1011.6kB
               )
- Dynamic Sparse Training for Deep Reinforcement Learning.
 Ghada Sokar, Elena
            Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy,
            and Peter Stone.
 In Proceedings of the 31st International Joint Conference
            on Artificial Intelligence, July 2022.
 arXiv version with the appendix
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.7MB
               )
                [slides.pptx]
               (16.7MB
               )
- Causal Dynamics Learning for Task-Independent State Abstraction.
 Zizhao
            Wang, Xuesu Xiao, Zifan Xu, Yuke
            Zhu, and Peter Stone.
 In Proceedings of the 39th International Conference
            on Machine Learning (ICML2022), July 2022.
 recorded presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.2MB
               )
                [slides.pdf]
               (4.0MB
               )
                [poster.pdf]
               (1.6MB
               )
- Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization.
 Michael
            Albert, Vincent Conitzer, Giuseppe Lopomo, and Peter Stone.
 Operations
            Research, March 2021.
 Details
                  
               BibTeX
                  
            Download: 
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               (692.5kB
               )
- Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies.
 Roberto Capobianco, Varun Kompella, James
            Ault, Guni Sharon, Stacy
            Jong, Spencer Fox, Lauren
            Meyers, Peter R. Wurman, and Peter
            Stone.
 The Journal of Artificial Intelligence Research (JAIR), 71:953–92, August 2021.
 Contains
            material that was previously published in an AAMAS
            2021 paper and a AAAI 2020 Fall
            Symposium paper.
 Article available from  JAIR website.
 Simulator
            source code.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
 Jiaxun
            Cui, William Macke, Harel
            Yedidsion, Aastha Goyal, Daniel Urieli, and Peter
            Stone.
 In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS),
            May 2021.
 Project page, with videos
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
                [slides.pptx]
               (1.5MB
               )
- Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy.
 Yunshu Du, Garrett
            Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew
            E. Taylor.
 Neural Computing and Applications, May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
- Adversarial Intrinsic Motivation for Reinforcement Learning.
 Ishan Durugkar,
            Mauricio Tec, Scott Niekum, and Peter
            Stone.
 In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021),
            December 2021.
 slides and video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.1MB
               )
- Capturing Skill State in Curriculum Learning for Human Skill Acquisition.
 Keya
            Ghonasgi, Reuth Mirsky, Sanmit
            Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D.
            Deshpande.
 In International Conference on Intelligent Robots and Systems (IROS), September 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Machine versus Human Attention in Deep Reinforcement Learning Tasks.
 Sihang Guo, Ruohan
            Zhang, Bo Liu, Yifeng Zhu,
            Mary Hayhoe, Dana Ballard, and Peter
            Stone.
 In Conference on Neural Information Processing Systems (NeurIPS), December 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.6MB
               )
- Incorporating Gaze into Social Navigation.
 Justin Hart, Reuth
            Mirsky, Xuesu Xiao, and Peter
            Stone.
 In RSS Workshop on Social Robot Navigation, July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.8MB
               )
                [slides.pdf]
               (3.5MB
               )
- RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning.
 Eddy Hudson, Garrett
            Warnell, and Peter Stone.
 In Autonomous Robots and Multirobot Systems
            Workshop at the 20th International Conference onAutonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (393.0kB
               )
- Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
 Yuqian
            Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone.
 In
            Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.8MB
               )
                [slides.pdf]
               (1.8MB
               )
- A Lifelong Learning Approach to Mobile Robot Navigation.
 Bo Liu, Xuesu Xiao, and Peter Stone.
 IEEE
            Robotics and Automation Letters (RA-L), 6(2), April 2021.
 Presented at IEEE International Conference on Robotics
            and Automation (ICRA),
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.6MB
               )
- Conflict-Averse Gradient Descent for Multi-task learning.
 Bo Liu, Xingchao
            Liu, Xiaojie Jin, Peter Stone, and Qiang Liu.
 In Conference on Neural
            Information Processing Systems (NeurIPS), 2021, December 2021.
 slides
            and 9-minute presentation
 github repository
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (9.7MB
               )
- Team  Orienteering  Coverage  Planning  with  Uncertain  Reward.
 Bo Liu,
            Xuesu Xiao, and Peter Stone.
 In
            International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.9MB
               )
- Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition.
 Bo
            Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke
            Zhu, and Animashree Anandkumar.
 In Proceedings of the 38th International Conference on Machine Learning, PMLR 139,
            2021 (ICML), July 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.2MB
               )
                [poster.pdf]
               (1.1MB
               )
- Expected Value of Communication for Planning in Ad Hoc Teamwork.
 William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (869.9kB
               )
                [slides.pdf]
               (2.3MB
               )
                [poster.pdf]
               (1.8MB
               )
- Is the Cerebellum a Model-Based Reinforcement Learning Agent?.
 Bharath Masetty, Reuth
            Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter
            Stone.
 In Adaptive and Learning Agents Workshop at AAMAS, May 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (594.9kB
               )
                [slides.pdf]
               (1.5MB
               )
- Intelligent Disobedience and AI Rebel Agents in Assistive Robotics.
 Reuth
            Mirsky and Peter Stone.
 In ICSR workshop on Adaptive Social Interaction
            and MOVement for assistive and rehabilitation robotics (ASIMOV), November 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (194.4kB
               )
- The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care.
 Reuth
            Mirsky and Peter Stone.
 In Proceedings of the 20th International
            Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (679.2kB
               )
- Reasoning about Human Behavior in Ad Hoc Teamwork.
 Jennifer Suriadinata, William
            Macke, Reuth Mirsky, and Peter
            Stone.
 In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
 Video
            Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (926.2kB
               )
- DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation.
 Faraz
            Torabi, Garrett Warnell, and Peter
            Stone.
 In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September
            2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (742.7kB
               )
- APPLR: Adaptive Planner Parameter Learning from Reinforcement.
 Zifan Xu,
            Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett
            Warnell, Bo Liu, Zizhao Wang,
            and Peter Stone.
 In Proceedings of the 2021 IEEE International Conference
            on Robotics and Automation (ICRA 2021), June 2021.
 Video
            presentation
 Project webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (3.4MB
               )
                [slides.pptx]
               (27.4MB
               )
- Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning.
 Zifan
            Xu, Xuesu Xiao, Garrett
            Warnell, Anirudh Nair, and Peter Stone.
 In Proceedings of the 2021
            IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), October 2021.
 Video
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.5MB
               )
- A Scavenger Hunt for Service Robots.
 Harel Yedidsion,
            Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter
            Stone.
 In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.5MB
               )
- Sequential Online Chore Division for Autonomous Vehicle Convoy Formation.
 Harel
            Yedidsion, Shani Alkoby, and Peter
            Stone.
 Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
 arXiv
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (478.9kB
               )
- The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation.
 Shih-Yun Lo, Shiqi
            Zhang, and Peter Stone.
 The Journal of Artificial Intelligence Research
            (JAIR), 67, October 2020.
 Contains material that was previously published in an AAMAS-18
            paper (awarded the Best Robotics Paper Award at AAMAS 2018)
 Also
            available from  JAIR website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (4.0MB
               )
- A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork.
 Reuth
            Mirsky, William Macke, Andy Wang, Harel
            Yedidsion, and Peter Stone.
 In Proceedings of the 29th International
            Joint Conference on Artificial Intelligence, July 2020.
 15-minute
            presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.2MB
               )
                [slides.pdf]
               (1.4MB
               )
- Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey.
 Sanmit
            Narvekar, Bei Peng, Matteo Leonetti, Jivko
            Sinapov, Matthew E. Taylor, and Peter
            Stone.
 Journal of Machine Learning Research, 21(181):1–50, 2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.4MB
               )
- Generalizing Curricula for Reinforcement Learning.
 Sanmit Narvekar
            and Peter Stone.
 In 4th Lifelong Learning Workshop at the International
            Conference on Machine Learning (ICML 2020), July 2020.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (330.4kB
               )
                [slides.pdf]
               (3.8MB
               )
- Learning to Improve Multi-Robot Hallway Navigation.
 Jin-Soo Park, Brian Tsang, Harel
            Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone.
 In Proceedings of the 4th Conference on Robot Learning (CoRL),
            November 2020.
 Video presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (1.3MB
               )
- RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration.
 Brahma
            Pavse, Faraz Torabi, Josiah
            Hanna, Garrett Warnell, and Peter
            Stone.
 IEEE Robotics and Automation Letters (RA-L), 5:6262–69, October 2020.
 Video
            of the experiments; 13-minute video presentation.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (405.1kB
               )
                [slides.pptx]
               (115.4MB
               )
- Reducing Sampling Error in Batch Temporal Difference Learning.
 Brahma Pavse,
            Ishan Durugkar, Josiah Hanna,
            and Peter Stone.
 In Proceedings of the 37th International Conference
            on Machine Learning (ICML), July 2020.
 The paper and talk is available from the ICML
            2020 virtual conference page.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (738.4kB
               )
                [slides.pdf]
               (5.2MB
               )
- On Sampling Error in Batch Action-Value Prediction Algorithms.
 Brahma S. Pavse,
            Josiah P. Hanna, Ishan Durugkar,
            and Peter Stone.
 In In the Offline Reinforcement Learning Workshop at
            Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
 5-minute
            Video Presentation
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (327.2kB
               )
Good Systems
      
      
         - Offline Action-Free Learning of Ex-BMDPs by Comparing Diverse Datasets.
 Alexander Levine, Peter
            Stone, and and Amy Zhang.
 In Reinforcement Learning Conference, August 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (770.2kB
               )
- ProtoCRL: Prototype-based Network for Continual Reinforcement Learning.
 Michela Proietti, Peter
            R. Wurman, Peter Stone, and Roberto Capobianco.
 In Reinforcement
            Learning Conference, August 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- LLM-GROP: Visually grounded robot task and motion planning with large language models.
 Xiaohan Zhang, Yan Ding,
            Yohei Hayamizu, Zainab Altaweel, Yifeng Zhu, Yuke
            Zhu, Peter Stone, Chris Paxton, and Shiqi
            Zhang.
 The International Journal of Robotics Research, 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.5MB
               )
Unspecified
      
      
         - Principles and Guidelines for Evaluating Social Robot Navigation Algorithms.
 Anthony Francis, Claudia Perez-D'Arpino,
            Chengshu Li, Fei Xia, Alexandre Alahi, Rachid Alami1, Aniket Bera, Abhijat Biswas,
            Joydeep Biswas, Rohan Chandra, Hao-Tien
            Lewis Chiang, Michael Everett, Sehoon Ha, Justin Hart, Jonathan P. How, Haresh
            Karnan, Tsang-Wei Edward Lee, Luis J. Manso, Reuth Mirksy,
            Soren Pirk, Phani Teja Singamaneni, Peter Stone, Ada
            V. Taylor, Peter Trautman, Nathan Tsoi, Marynel Vazquez, Xuesu Xiao, Peng
            Xu, Naoki Yokoyama, Alexander Toshev, and and Roberto Martin-Martin.
 ACM Transactions on Human-Robot Interaction (THRI),
            14(2), February 2025.
 Official version on publisher's website
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (8.8MB
               )
- A Champion-Level Vision-Based Reinforcement Learning Agent for Competitive Racing in Gran Turismo 7.
 Hojoon
            Lee, Takuma Seno, Jun Jet Tai, Kaushik Subramanian, Kenta Kawamoto, Peter Stone,
            and Peter R. Wurman.
 IEEE Robotics and Automation Letters, 10(6):5545–52,
            June 2025.
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (2.1MB
               )
- SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning.
 Hojoon
            Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter
            R. Wurman, Jaegul Choo, Peter Stone, and Takuma Seno.
 In International
            Conference on Learning Representations, April 2025.
 Code and videos are on the
            paper's webpage
 Details
                  
               BibTeX
                  
            Download: 
            [pdf]
               (5.7MB
               )
- Argus: A Compact and Versatile Foundation Model for Vision.
 Weiming Zhuang, Chen
            Chen, Zhizhong Li, Sina Sajadmanesh, Jingtao Li, Jiabo Huang, Vikash Sehwag, Vivek Sharma, Hirotaka Shinozaki, Felan Carlo
            Garcia, Yihao Zhan, Naohiro Adachi, Ryoji Eki, Michael Spranger, Peter Stone,
            and Lingjuan Lyu.
 In Conference on Computer Vision and Pattern Recognition, June 2025.
 Details
                  
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               (3.1MB
               )
- Now, Later, and Lasting: 10 Priorities for AI Research, Policy, and Practice.
 Eric Horvitz, Vincent Conitzer, Sheila
            McIlraith, and Peter Stone.
 Communications of the ACM, 67(6):39–40,
            May 2024.
 Official
            online version
 arXiv version
 Details
                  
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               (151.4kB
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- Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration.
 Borja G. Leon,
            Francesco Riccio, Kaushik Subramanian, and Peter R. Wurman an Peter Stone.
 In
            Conference on Neural Information Processing Systems (NeurIPS), December 2024.
 Project
            website (with videos)
 Details
                  
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            [pdf]
               (1.5MB
               )
                [slides.pdf]
               (1.4MB
               )
                [poster.pdf]
               (1.5MB
               )
- A collective AI via lifelong learning and sharing at the edge.
 Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir
            Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan
            How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven
            Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash,
            Vishwa Parekh, Kaushik Roy, Shahaf Shperberg, Hava T. Siegelmann, Peter Stone,
            Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, and Soheil Kolouri.
 nature
            machine intelligence, 2024.
 Details
                  
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               (2.8MB
               )
- A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo.
 Miguel Vasco, Takuma
            Seno, Kenta Kawamoto, Kaushik Subramanian, Peter R. Wurman, and Peter
            Stone.
 In Reinforcement Learning Conference (RLC), August 2024.
 arXiv
            version
 Details
                  
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               (15.4MB
               )
- Real-time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing.
 Catherine Weaver, Roberto
            Capobianco, Peter Wurman, Peter Stone,
            and Masayoshi Tomizuka.
 In American Control Conference (ACC), July 2024.
 Project
            page with video.
 Details
                  
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               (1.5MB
               )
- Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Third BARN Challenge at ICRA 2024 [Competitions].
 Xuesu Xiao, Zifan Xu, Aniket Datar, Garrett Warnell, Peter
            Stone, Joshua Julian Damanik, Jaewon Jung, Chala Adane Deresa, Than
            Duc Huy, Chen Jinyu, Chen Yichen, Joshua Adrian Cahyono, Jingda Wu, Longfei Mo, Mingyang Lv, Bowen Lan, Qingyang Meng, Weizhi
            Tao, and Li Cheng.
 IEEE Robotics \& Automation Magazine, 2024.
 Details
                  
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               (1.7MB
               )
- Event Tables for Efficient Experience Replay.
 Varun Kompella, Thomas Walsh, Samuel
            Barrett, Peter Wurman, and Peter Stone.
 Transactions
            on Machine Learning Research (TMLR), 2023.
 Details
                  
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               (6.8MB
               )
- Composing Efficient, Robust Tests for Policy Selection.
 Dustin Morrill, Thomas J. Walsh, Daniel Hernandez,
            Peter R. Wurman, and Peter Stone.
 In
            The 39th Conference on Uncertainty in Artificial Intelligence (UAI), August 2023.
 short
            video presentation, poster
 Details
                  
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               (5.5MB
               )
- Walking and falling: Using robot simulations to model the role of errors in infant walking.
 Ossmy, Ori, Han, Danyang,
            MacAlpine, Patrick, Hoch, Justine, Stone, Peter, and Adolph, Karen E..
 Developmental Science, 27:e13449, September
            2023.
 Available from the publisher's webpage
 Details
                  
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            (unavailable)
- Will Robots Triumph over World Cup Winners by 2050?.
 Peter Stone.
 IEEE
            Spectrum, 60(7):40–9, July 2023.
 Official online
            version
 Details
                  
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            (unavailable)
- Improving Artificial Intelligence with Games.
 Peter R. Wurman, Peter
            Stone, and Michael Spranger.
 Science, 381:147–8, July 2023.
 Available from Science
            website.
 Details
                  
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            Download: 
            
            (unavailable)
- Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning.
 Peter
            R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik
            Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Varun
            Kompella, Piyush Khandelwal, HaoChih
            Lin, Patrick MacAlpine, Declan Oller, Craig Sherstan, Takuma Seno, Michael
            D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead,
            Peter Duerr, Peter Stone, Michael Spranger, and and
            Hiroaki Kitano.
 Nature, 62:223–28, Feb. 2022.
 Available from Nature
            website.
 project webpage
 Details
                  
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               (2.7MB
               )
- Challenges and Opportunities of Applying Reinforcement Learning to Autonomous Racing.
 Peter
            R. Wurman, Peter Stone, and Michael Sprannger.
 IEEE Intelligent
            Systems, 37(3):20–3, May-June 2022.
 Official
            online version
 Details
                  
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            (unavailable)
- Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The BARN Challenge at ICRA 2022.
 Xuesu Xiao, Zifan Xu, Zizhao
            Wang, Yunlong Song, Garrett Warnell, Peter
            Stone, Tingnan Zhang, Shravan Ravi, Gary Wang, Haresh Karnan, Joydeep
            Biswas, Nicholas Mohammad, Lauren Bramblett, Rahul Peddi, Nicola Bezzo, Zhanteng Xie, and Philip Dames.
 IEEE Robotics
            \& Automation Magazine, 29(4):148–56, Dec. 2022.
 Official
            online version.
 Details
                  
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            (unavailable)
- Efficient Real-Time Inference in Temporal Convolution Networks.
 Piyush
            Khandelwal, James MacGlashan, Peter Wurman, and Peter
            Stone.
 In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
 Details
                  
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               (346.4kB
               )
- RoboCup 2021 Worldwide: A Successful Robotics Competition During a Pandemic.
 Peter
            Stone, Luca Iocchi, Flavio Tonidandel, and Changjiu Zhou.
 IEEE Robotics \& Automation Magazine, 28(4):114–19,
            December 2021.
 Official online version
 Details
                  
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- A Broader, More Inclusive Definition of AI.
 Peter Stone.
 Journal
            of Artificial General Intelligence, 11(2):63–65, 2020.
 Details
                  
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               (50.6kB
               )
- A Century Long Commitment to Assessing Artificial Intelligence and Its Impact on Society.
 Barbara
            J. Grosz and Peter Stone.
 Communications of the ACM, 61(12),
            December 2018.
 Official
            online version
 Details
                  
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               (84.2kB
               )
- Behavioral Cloning from Observation.
 Faraz Torabi, Garrett
            Warnell, and Peter Stone.
 In Proceedings of the 27th International
            Joint Conference on Artificial Intelligence (IJCAI), July 2018.
 Also available from arXiv
 Details
                  
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               (2.3MB
               )
                [slides.pptx]
               (26.0MB
               )
- Multiagent Learning Paradigms.
 Karl Tuyls and Peter Stone.
 In
            Francesco Belardinelli and Estefania Argente, editors, Multi-Agent Systems and Agreement Technologies, Lecture Notes
            in Artificial Intelligence, pp. 3–21, Springer, 2018.
 Details
                  
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               (509.0kB
               )
- Decision mechanisms underlying mood-congruent emotional classification.
 Corey
            N. White, Elad Liebman, and Peter
            Stone.
 Cognition and Emotion, 32(2):249–58, Taylor \& Francis, 2017.
 Available from publisher's
            website.
 Details
                  
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               (1.2MB
               )
- UT Austin Villa: Project-Driven Research in AI and Robotics.
 Genter, Katie, MacAlpine, Patrick, Menashe, Jacob,
            Hannah, Josiah, Liebman, Elad, Narvekar, Sanmit, Zhang,Ruohan, and Stone, Peter.
 IEEE Intelligent Systems , 31(02):94–101,
            IEEE Computer Society, Los Alamitos, CA, USA, March 2016.
 Available from publisher's
            webpage
 Details
                  
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- Dynamic Behaviors on the NAO Robot With Closed-Loop Whole Body Operational Space Control.
 Donghyun Kim, Steven Jens
            Jorgensen, Peter Stone, and Luis
            Sentis.
 In IEEE-RAS International Conference on Humanoid Robots, 2016.
 Details
                  
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               (4.0MB
               )
- What's Hot at RoboCup (Extended Abstract).
 Peter Stone.
 In Proceedings
            of the Thirtieth AAAI Conference on Artificial Intelligence, February 2016.
 Details
                  
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               (64.9kB
               )
- Artificial Intelligence and Life in 2030.
 Peter Stone, Rodney Brooks,
            Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram
            Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David Parkes,
            William Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, and Astro
            Teller.
 One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University,
            Stanford, CA, 2016.
 Available online
 Details
                  
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- Who Speaks for AI.
 Eric Eaton, Tom Dietterich, Maria Gini, Barbara J. Grosz, Charles
            L. Isbell, Subbarao Kambhamp, Michael Littman, Francesca Rossi, Stuart
            Russell, Peter Stone, Toby Walsh, and Michael Wooldridge.
 AI Matters,
            2(2), December 2015.
 Details
                  
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- RoboCup Soccer Leagues.
 Daniele Nardi, Itsuki
            Noda, Fernando Ribeiro, Peter Stone, Oskar
            von Stryk, and Manuela Veloso.
 AI Magazine, 35(3):77–85, 2014.
 Details
                  
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- RoboCup-2012: Robot Soccer World Cup XVI,
 Xiaoping
            Chen, Peter Stone, Luis Enrique
            Sucar, and Tijn van der Zant, editors.
 Lecture Notes in Artificial Intelligence,
            Springer Verlag, Berlin, 2013.
 A book based on  RoboCup-2012
 Available from the publisher's webpage
 ISBN: 978-3-642-39249-8
 Details
                  
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- Video: RoboCup Robot Soccer History 1997 -- 2011.
 Manuela Veloso and Peter Stone.
 October 2012. Available from https://www.youtube.com/watch?v=WLOv2AFAZhc
 Details
                  
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               )
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               (43.8kB
               )
- Empowerment for continuous agent-environment systems.
 Tobias Jung,
            Daniel Polani, and Peter Stone.
 Adaptive
            Behavior, 19(1):16–39, 2011.
 Available from Adaptive
            Behavior page.
 Details
                  
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               (1.8MB
               )
                [ps]
               (1.8MB
               )
- Flood Disaster Mitigation: A Real-world Challenge Problem forMulti-Agent Unmanned Surface Vehicles.
 Paul
            Scerri, Balajee Kannan, Pras Velagapudi, Kate Macarthur, Peter Stone, Matthew E. Taylor, John Dolan, Alessandro Farinelli, Archie Chapman, Bernadine
            Dias, and George Kantor.
 In Proceedings of the Autonomous Robots and MultirobotSystems workshop (at AAMAS-11),
            May 2011.
 ARMS-11
 Details
                  
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               (765.1kB
               )
- Proceedings of the Tenth International Conference on Autonomous Agents and Multiagent Systems,
 Kagan
            Tumer, Pinar Yolum, Liz
            Sonenberg, and Peter Stone, editors.
 International Foundation for Autonomous
            Agents and Multiagent Systems (IFAAMAS), May 2011.
 A book based on AAMAS 2011
 ISBN-10: 0-9826571-5-3  ISBN-13 978-0-9826571-5-7
 on-line
            version from IFAAMAS.
 Details
                  
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- Cobot in LambdaMOO:  An Adaptive Social Statistics Agent.
 Charles
            Lee Isbell, Jr., Michael
            Kearns, Satinder Singh, Christian
            Shelton, Peter Stone, and Dave
            Kormann.
 Autonomous Agents and Multiagent Systems, 13(3), November 2006.
 JAAMAS
 Official
            version from publisher's website.
 Contains material
            that was previously published in an Agents-2001 paper
            that won the BEST PAPER AWARD.
 Details
                  
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- Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems,
 Peter
            Stone and Gerhard Weiss, editors.
 Association for Computing Machinery
            (ACM), May 2006.
 A book based on AAMAS 2006
 ISBN: 1-59593-303-4
 on-line
            version from ACM.
 Details
                  
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            (unavailable)
- A Polynomial-time Nash Equilibrium Algorithm for Repeated Games.
 Michael
            L. Littman and Peter Stone.
 Decision Support Systems, 39:55–66
            , 2005.
 An earlier version appeared in the proceedings of the
            fourth annual ACM Conference on Electronic Commerce
 Official version from Decision
            Support Systems
 Details
                  
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               (244.7kB
               )
                [ps]
               (272.4kB
               )
- Reinforcement Learning for RoboCup-Soccer Keepaway.
 Peter Stone,
            Richard S. Sutton, and Gregory
            Kuhlmann.
 Adaptive Behavior, 13(3):165–188, 2005.
 Contains material that was previously published
            in an ICML-2001 paper  and a 
            RoboCup 2003 Symposium paper.
 Some simulations
            of keepaway referenced in the paper and keepaway software.
 Details
                  
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               )
                [ps]
               (2.0MB
               )
- The First International Trading Agent Competition: Autonomous Bidding Agents.
 Peter
            Stone and Amy Greenwald.
 Electronic Commerce Research,
            5(2):229–65, April 2005.
 Official version from publisher's
            website © Springer-Verlag
 Details
                  
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               (398.7kB
               )
                [ps]
               (679.1kB
               )
- Towards Employing PSRs in a Continuous Domain.
 Nicholas
            K. Jong and Peter Stone.
 Technical Report UT-AI-TR-04-309, The
            University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2004.
 UTAustin
            AI Lab technical reports
 Details
                  
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- RoboCup as an Introduction to CS Research.
 Peter Stone.
 In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors,
            RoboCup-2003: Robot Soccer World Cup VII, Lecture Notes in Artificial Intelligence, pp. 284–95, Springer Verlag,
            Berlin, 2004.
 Details
                  
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               (150.1kB
               )
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               (1.2MB
               )
- Guest Editors' Introduction: Agents and Markets.
 Amy Greenwald,
            Nicholas R. Jennings, and Peter
            Stone.
 IEEE Intelligent Systems, 18(6):12–14, November/December 2003.
 IEEEIntelligent
            Systems special issue on agents and markets.
 Details
                  
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               (545.6kB
               )
- The RoboCup Soccer Server and CMUnited Clients: Implemented Infrastructure for MAS Research.
 Itsuki
            Noda and Peter Stone.
 Autonomous Agents and Multi-Agent Systems,
            7(1--2):101–120, July--September 2003.
 Details
                  
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               (271.2kB
               )
                [ps]
               (459.0kB
               )
- Learning Predictive State Representations.
 Satinder Singh, Michael
            L. Littman, Nicholas K. Jong, David
            Pardoe, and Peter Stone.
 In Proceedings of the Twentieth International
            Conference on Machine Learning, August 2003.
 ICML-2003
 Details
                  
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               (316.3kB
               )
                [ps]
               (319.2kB
               )
- Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions.
 Peter
            Stone, Robert E. Schapire, Michael
            L. Littman, János A. Csirik, and David
            McAllester.
 Journal of Artificial Intelligence Research, 19:209–242, 2003.
 Available from journal's
            web page.
 Details
                  
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- Multiagent Competitions and Research: Lessons from RoboCup and TAC.
 Peter
            Stone.
 In Gal A. Kaminka, Pedro U. Lima, and Raul Rojas, editors,
            RoboCup-2002: Robot Soccer World Cup VI, Lecture Notes in Artificial Intelligence, pp. 224–237, Springer Verlag,
            Berlin, 2003.
 Details
                  
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               (216.7kB
               )
                [ps]
               (168.6kB
               )
- The 2001 Trading Agent Competition.
 Michael P. Wellman, Amy Greenwald, Peter Stone,
            and Peter R. Wurman.
 Electronic Markets, 13(1):4–12, May 2003.
 Available from the publisher's
            webpage
 An earlier version appeared in the Fourteenth Conference on Innovative Applications of Artificial Intelligence,
            pages 935-941, Edmonton, July 2002.
 Details
                  
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               (165.3kB
               )
                [ps]
               (855.0kB
               )
- Concurrent Layered Learning.
 Shimon Whiteson and Peter Stone.
 In Second International Joint Conference on Autonomous Agents
            and Multiagent Systems, pp. 193–200, ACM Press, New York, NY, July 2003.
 AAMAS-2003
 Details
                  
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               (159.1kB
               )
                [ps]
               (372.6kB
               )
- Performance Analysis of a Counter-intuitive Automated Stock-Trading Strategy.
 Ronggang Yu and Peter
            Stone.
 In Proceedings of the Fifth International Conference on Electronic Commerce, Pittsburgh, PA, October
            2003.
 ICEC-2003
 Details
                  
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               (382.5kB
               )
                [ps]
               (1.2MB
               )
- Self-enforcing Strategic Demand Reduction.
 Paul S. A. Reitsma,
            Peter Stone, János A. Csirik, and
            Michael L. Littman.
 In Agent Mediated Electronic Commerce IV: Designing
            Mechanisms and Systems, Lecture Notes in Artificial Intelligence, pp. 289–306, Springer Verlag, 2002.
 Details
                  
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               (141.7kB
               )
                [ps]
               (125.4kB
               )
- Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation.
 Robert
            E. Schapire, Peter Stone, David
            McAllester, Michael L. Littman, and János
            A. Csirik.
 In Proceedings of the Nineteenth International Conference on Machine Learning, 2002.
 ICML-2002
 Details
                  
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               (159.5kB
               )
                [ps]
               (137.2kB
               )
- ATTUnited-2001: Using Heterogeneous Players.
 Peter Stone.
 In Andreas
            Birk, Silvia Coradeschi, and Satoshi Tadokoro, editors, RoboCup-2001: Robot Soccer
            World Cup V, Lecture Notes in Artificial Intelligence, pp. 495–98, Springer Verlag, Berlin, 2002.
 Details
                  
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               (112.8kB
               )
                [ps]
               (79.3kB
               )
- RoboCup-2001:  The Fifth Robotic Soccer World Championships.
 Manuela Veloso,
            Tucker Balch, Peter Stone,
            Hiroaki Kitano, Fuminori Yamasaki, Ken Endo, Minoru
            Asada, M. Jamzad, B. S. Sadjad, V. S. Mirrokni, M. Kazemi, H. Chitsaz, A. Heydarnoori,
            M. T. Hajiaghai, and E. Chiniforooshan.
 AI Magazine, 23(1):55–68, 2002.
 Details
                  
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- FAucS: An FCC Spectrum Auction Simulator for Autonomous Bidding Agents.
 János
            A. Csirik, Michael L. Littman, Satinder
            Singh, and Peter Stone.
 In Electronic Commerce:  Proceedings of the
            Second International Workshop, pp. 139–151, Springer Verlag, Heidelberg, Germany, 2001.
 WELCOM-01
 Details
                  
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               (202.3kB
               )
                [ps]
               (170.8kB
               )
- Autonomous Bidding Agents in the Trading Agent Competition.
 Amy
            Greenwald and Peter Stone.
 IEEE Internet Computing, 5(2):52–60,
            March/April 2001.
 Magazine's website
 Details
                  
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               (817.8kB
               )
                [ps]
               (1.4MB
               )
- Implicit Negotiation in Repeated Games.
 Michael L. Littman and Peter
            Stone.
 In Proceedings of The Eighth International Workshop on Agent Theories, Architectures, and Languages (ATAL-2001),
            pp. 393–404, August 2001.
 ATAL-2001
 Details
                  
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               (181.2kB
               )
                [ps]
               (149.4kB
               )
- Keeping the Ball from CMUnited-99.
 David McAllester and Peter Stone.
 In Peter Stone,
            Tucker Balch, and Gerhard
            Kraetzschmar, editors, RoboCup-2000: Robot Soccer World Cup IV, Lecture Notes in Artificial Intelligence, pp. 333–338,
            Springer Verlag, Berlin, 2001.
 Details
                  
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               (107.1kB
               )
                [ps]
               (66.1kB
               )
- Layered Disclosure: Revealing Agents' Internals.
 Patrick Riley, Peter
            Stone, and Manuela Veloso.
 In C. Castelfranchi and Y. Lespérance,
            editors, Intelligent Agents VII. Agent Theories, Architectures, and Languages --- 7th. International Workshop, ATAL-2000,
            Boston, MA, USA, July 7--9, 2000, Proceedings, Lecture Notes in Artificial Intelligence, Springer-Verlag, Berlin, Berlin,
            2001.
 Publisher's Webpage© Springer-Verlag
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               (96.6kB
               )
                [ps]
               (881.8kB
               )
- ATT-CMUnited-2000: Third Place Finisher in the RoboCup-2000 Simulator League.
 Patrick
            Riley, Peter Stone, David
            McAllester, and Manuela Veloso.
 In P.
            Stone, T. Balch, and G.
            Kraetzschmar, editors, RoboCup-2000: Robot Soccer World Cup IV, Lecture Notes in Artificial Intelligence, Springer
            Verlag, Berlin, 2001.
 Details
                  
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               (114.6kB
               )
                [ps]
               (82.2kB
               )
- RoboCup-2000: Robot Soccer World Cup IV,
 Peter Stone, Tucker
            Balch, and Gerhard Kraetzschmar, editors.
 Lecture Notes
            in Artificial Intelligence, Springer Verlag, Berlin, 2001.
 A book based on 
            RoboCup-2000
 Available from the publisher's
            webpage
 ISBN: 3540421858
 Details
                  
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            Download: 
            
            (unavailable)
- ATTac-2000: An Adaptive Autonomous Bidding Agent.
 Peter Stone, Michael L. Littman, Satinder Singh,
            and Michael Kearns.
 Journal of Artificial Intelligence Research,
            15:189–206, June 2001.
 Available from journal's web page.
 Details
                  
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               (326.9kB
               )
                [ps]
               (305.2kB
               )
- RoboCup-2000:  The Fourth Robotic Soccer World Championships.
 Peter Stone,
            (ed.), Minoru Asada, Tucker
            Balch, Raffaelo D'Andrea, Masahiro Fujita, Bernhard Hengst, Gerhard
            Kraetzschmar, Pedro Lima, Nuno Lau, Henrik Lund, Daniel Polani, Paul Scerri, Satoshi Tadokoro, Thilo Weigel, and Gordon Wyeth.
 AI Magazine,
            22(1), 2001.
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- An Architecture for Action Selection in Robotic Soccer.
 Peter Stone
            and David McAllester.
 In Proceedings of the Fifth International
            Conference on     Autonomous Agents, pp. 316–323, ACM Press, New York, NY, 2001.
 Agents-2001
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- Overview of RoboCup-99.
 Silvia Coradeschi, Lars
            Karlsson, Peter Stone, Tucker
            Balch, Gerhard Kraetzschmar, and Minoru
            Asada.
 AI Magazine, 21(3), 2000.
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- Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer,
 Peter
            Stone.
 MIT Press, 2000.
 A book based on my Ph.D.
            thesis
 Contents, availability, and on-line appendices
 ISBN: 0262194384
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- Multiagent Systems: A survey from a machine learning perspective.
 Peter
            Stone and Manuela Veloso.
 Autonomous Robots, 8(3):345–383, July
            2000.
 Formerly citable as Carnegie Mellon University CS               technical report number CMU-CS-97-193. December,
            1997.
 Details
                  
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- Layered Learning.
 Peter Stone and Manuela
            Veloso.
 In Ramon López de Mántaras and Enric Plaza, editors, Machine Learning: ECML 2000 (Proceedings
            of the Eleventh European Conference on Machine Learning), pp. 369–381, Springer Verlag, Barcelona,Catalonia,Spain,
            May/June 2000.
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- Defining and Using Ideal Teammate and Opponent Models.
 Peter Stone,
            Patrick Riley, and Manuela Veloso.
 In
            Proceedings of the Twelfth Annual Conference on Innovative Applications of Artificial Intelligence, 2000.
 AAAI Homepage
 Details
                  
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- TPOT-RL Applied to Network Routing.
 Peter Stone.
 In Proceedings
            of the Seventeenth International Conference on Machine Learning, pp. 935–942, 2000.
 ICML-2000
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- The CMUnited-99 Champion Simulator Team.
 Peter Stone, Patrick
            Riley, and Manuela Veloso.
 In M. Veloso,
            E. Pagello, and H. Kitano, editors, RoboCup-99: Robot
            Soccer World Cup III, Lecture Notes in Artificial Intelligence, pp. 35–48, Springer Verlag, Berlin, 2000.
 Extended version (unofficial, but with
            some more details)  (pdf version)
 Details
                  
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- The CMUnited-97 Robotic Soccer Team:  Perception and Multi-agent Control.
 Manuela
            Veloso, Peter Stone, and Kwun Han.
 Robotics and Autonomous Systems,
            29(2-3):133–143, November 2000.
 Details
                  
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- Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork.
 Peter Stone and Manuela Veloso.
 Artificial
            Intelligence, 110(2):241–273, June 1999.
 HTML
            version.
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- Team-Partitioned, Opaque-Transition Reinforcement Learning.
 Peter Stone
            and Manuela Veloso.
 In Minoru
            Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer
            World Cup II, Lecture Notes in Artificial Intelligence, pp. 261–72, Springer Verlag, Berlin, 1999. Also in Proceedings
            of the Third International Conference on                  Autonomous Agents, 1999
 Details
                  
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- The CMUnited-98 Champion Simulator Team.
 Peter Stone, Manuela
            Veloso, and Patrick Riley.
 In M. Asada
            and H. Kitano, editors, RoboCup-98: Robot Soccer World
            Cup II, Lecture Notes in Artificial Intelligence, pp. 61–76, Springer Verlag, 1999.
 (extended version linked
            here)
 HTML version.
 Details
                  
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               (195.1kB
               )
                [ps]
               (174.7kB
               )
- Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer.
 Manuela
            Veloso, Peter Stone, and Michael
            Bowling.
 In Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems II, pp. 134–143,
            SPIE, Bellingham, WA, September 1999.
 Details
                  
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               (108.2kB
               )
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               (1.8MB
               )
- The CMUnited-98 Champion Small Robot Team.
 Manuela Veloso, Michael
            Bowling, Sorin Achim, Kwun Han, and Peter Stone.
 In Minoru
            Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer
            World Cup II, Lecture Notes in Artificial Intelligence, pp. 77–92, Springer Verlag, Berlin, 1999.
 Details
                  
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               (211.2kB
               )
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               (1.2MB
               )
- The RoboCup Physical Agent Challenge:  Phase-I.
 Minoru
            Asada, Yasuo Kuniyoshi, Alexis Drogoul,
            Hajime Asama, Maja
            Mataric, Dominique Duhaut, Peter Stone, and Hiroaki
            Kitano.
 Applied Artificial Intelligence, 12:251–263, 1998.
 HTML
            version.
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               (131.6kB
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- A Layered Approach to Learning Client Behaviors in the RoboCup Soccer Server.
 Peter
            Stone and Manuela Veloso.
 Applied Artificial Intelligence, 12:165–188,
            1998.
 HTML version.
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               (189.1kB
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- Towards Collaborative and Adversarial Learning:  A Case Study in Robotic Soccer.
 Peter
            Stone and Manuela Veloso.
 International Journal of Human-Computer     
              Studies, 48(1):83–104, January 1998.
 HTML
            version.
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               (137.7kB
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- Using Decision Tree Confidence Factors for Multiagent Control.
 Peter
            Stone and Manuela Veloso.
 In Hiroaki
            Kitano, editors, RoboCup-97: Robot Soccer World Cup I, Lecture Notes in Artificial Intelligence, pp. 99–111,
            Springer Verlag, Berlin, 1998.
 HTML
            version.
 Official version from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (157.2kB
               )
                [ps]
               (128.0kB
               )
- The CMUnited-97 Simulator Team.
 Peter Stone and Manuela
            Veloso.
 In Hiroaki Kitano, editors, RoboCup-97: Robot
            Soccer World Cup I, Lecture Notes in Artificial Intelligence, pp. 387–397, Springer Verlag, Berlin, 1998.
 HTML version.
 Official version
            from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (128.3kB
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               (107.2kB
               )
- The CMUnited-97 Small-Robot Team.
 Manuela Veloso, Peter
            Stone, Kwun Han, and Sorin Achim.
 In Hiroaki Kitano, editors,
            RoboCup-97: Robot Soccer World Cup I, Lecture Notes in Artificial Intelligence, pp. 242–256, Springer Verlag,
            Berlin, 1998.
 HTML version.
 Official
            version from Publisher's Webpage© Springer-Verlag
 Details
                  
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               (191.8kB
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- The RoboCup Synthetic Agent Challenge 97.
 Hiroaki Kitano,
            Milind Tambe, Peter Stone, Manuela Veloso, Silvia Coradeschi, Eiichi Osawa,
            Hitoshi Matsubara, Itsuki Noda, and Minoru
            Asada.
 In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, pp. 24–29,
            Morgan Kaufmann, San Francisco, CA, 1997.
 IJCAI-97
 HTML
            version.
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- Interactive, Repair-Based Planning and Scheduling for Shuttle Payload Operations.
 Gregg Rabideau, Steve
            Chien, Peter Stone, Jason Willis, Curt Eggemeyer, and Tobias Mann.
 In
            Proceedings of the 1997 IEEE Aerospace Conference, pp. 325–341, Aspen, CO, February 1997.
 Part
            1   (pdf version) Part
            2   (pdf version) Part
            3   (pdf version) Part
            4   (pdf version)
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- Building a Dedicated Robotic Soccer System.
 Sorin Achim, Peter Stone,
            and Manuela Veloso.
 In Proceedings of the IROS-96 Workshop on RoboCup,
            pp. 41–48, Osaka, Japan, November 1996.
 HTML
            version.
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               )
- Predictive Memory for an Inaccessible Environment.
 Mike Bowling,
            Peter Stone, and Manuela Veloso.
 In
            Proceedings of the IROS-96 Workshop on RoboCup, pp. 28–34, Osaka, Japan, November 1996.
 HTML
            version.
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               (135.0kB
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               )
- User-guided Interleaving of Planning and Execution.
 Peter Stone and
            Manuela Veloso.
 In M. Ghallab and A. Milani, editors, New Directions
            in AI Planning, pp. 103–112, IOS Press, 1996.
 Details
                  
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- Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function.
 Peter
            Stone and Manuela Veloso.
 In Advances in Neural Information Processing
            Systems 8, pp. 896–902, MIT Press, Cambridge, MA, 1996.
 NIPS-95
 HTML version.
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               )
- Using Testing to Iteratively Improve Training.
 Peter Stone and Manuela Veloso.
 In Working Notes of the AAAI 1995 Fall Symposium on        Active
            Learning, pp. 110–111, Boston, MA, November 1995.
 Details
                  
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- FLECS: Planning with a Flexible Commitment Strategy.
 Manuela Veloso and
            Peter Stone.
 Journal of Artificial Intelligence Research, 3:25–52,
            June 1995.
 Available from journal's web page.
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- The need for different domain-independent heuristics.
 Peter Stone,
            Manuela Veloso, and Jim Blythe.
 In Proceedings
            of the Second International Conference on AI Planning Systems, pp. 164–169, June 1994.
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- Learning to Solve Complex Planning Problems: Finding Useful Auxiliary Problems.
 Peter
            Stone and Manuela Veloso.
 In Technical Report of the AAAI 1994 Fall Symposium
            on        Planning and Learning: On to Real Applications, pp. 137–141, New Orleans, LA, November 1994.
 Details
                  
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