Peter Stone's Selected Publications

• Classified by Topic • Classified by Publication Type • Sorted by Date • Sorted by First Author Last Name • Classified by Funding Source •

Classified by Funding Source

• NSF • AFOSR • AFRL • ARL • FLI • ONR • IBM • DARPA • FHWA • TXDOT • Fulbright • Guggenheim • Intel • Raytheon • Lockheed Martin • Toyota • ATT • Alexander von Humboldt Foundation • Bosch • GM • Unspecified •

NSF

• Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, and Peter Stone. Scalable Multiagent Driving Policies For Reducing Traffic Congestion. In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2021.
  Details     BibTeX     Download: [pdf] (1.0MB )  [slides.pptx] (1.5MB )  

• Yunshu Du, Garrett Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew E. Taylor. Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy. Neural Computing and Applications, May 2021.
  Details     BibTeX     Download: [pdf] (2.2MB )  

• Josiah P. Hanna, Scott Niekum, and Peter Stone. Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy. Machine Learning (MLJ), 110:1267–1317, May 2021.
  Details     BibTeX     Download: [pdf] (3.7MB )  

• Justin Hart, Reuth Mirsky, Xuesu Xiao, and Peter Stone. Incorporating Gaze into Social Navigation. In Robotics: Science and Systems Workshop on Social Robot Navigation (RSS), July 2021.
  Details     BibTeX     Download: [pdf] (4.8MB )  

• Eddy Hudson, Garrett Warnell, and Peter Stone. RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning. 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 )  

• Yu-Sian Jiang, Garrett Warnell, and Peter Stone. Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), Feb 2021.
  Details     BibTeX     Download: [pdf] (911.3kB )  [poster.pdf] (1.1MB )  

• Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone. Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
  Details     BibTeX     Download: [pdf] (1.8MB )  [slides.pdf] (1.8MB )  

• W Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, and Peter Stone. Reward (Mis)design for Autonomous Driving. arXiv preprint arXiv:2104.13906, 2021.
  Paper webpage
  Details     BibTeX     Download: [pdf] (1.2MB )  

• Bo Liu, Xuesu Xiao, and Peter Stone. Team Orienteering Coverage Planning with Uncertain Reward. In International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
  Details     BibTeX     Download: [pdf] (3.9MB )  

• Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, and Animashree Anandkumar. Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition. 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 )  

• Bo Liu, Xuesu Xiao, and Peter Stone. A Lifelong Learning Approach to Mobile Robot Navigation. In IEEE International Conference on Robotics and Automation (ICRA), 2021, June 2021.
  Video presentation
  Details     BibTeX     Download: [pdf] (3.6MB )  

• William Macke, Reuth Mirsky, and Peter Stone. Expected Value of Communication for Planning in Ad Hoc Teamwork. 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 )  

• Reuth Mirsky and Peter Stone. The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care. In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), May 2021.
  Details     BibTeX     Download: [pdf] (679.2kB )  

• Guni Sharon, James Ault, Peter Stone, Varun Kompella, and Roberto Capobianco. Multiagent Epidemiologic Inference through Realtime Contact Tracing. In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2021), May 2021.
  Details     BibTeX     Download: [pdf] (1014.3kB )  

• Jennifer Suriadinata, William Macke, Reuth Mirsky, and Peter Stone. Reasoning about Human Behavior in Ad Hoc Teamwork. In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
  Video Presentation
  Details     BibTeX     Download: [pdf] (926.2kB )  

• Zizhao Wang, Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone. APPLI: Adaptive Planner Parameter Learning From Interventions. In Proceedings of the International Conference on Robotics and Automation (ICRA 2021), May 2021.
  Video presentation
  Details     BibTeX     Download: [pdf] (4.2MB )  

• Zifan Xu, Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Bo Liu, Zizhao Wang, and Peter Stone. APPLR: Adaptive Planner Parameter Learning from Reinforcement. 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 )  

• Harel Yedidsion, Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter Stone. A Scavenger Hunt for Service Robots. In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
  Video presentation
  Details     BibTeX     Download: [pdf] (1.5MB )  

• Harel Yedidsion, Shani Alkoby, and Peter Stone. Sequential Online Chore Division for Autonomous Vehicle Convoy Formation. Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
  arXiv
  Details     BibTeX     Download: [pdf] (478.9kB )  

• Siddarth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, and Peter Stone. An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch. In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020), December 2020.
  Poster
  Details     BibTeX     Download: [pdf] (1.3MB )  

• Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, and Peter Stone. Stochastic Grounded Action Transformation for Robot Learning in Simulation. In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
  11-minute video presentation.
  Details     BibTeX     Download: [pdf] (1.9MB )  

• Ishan Durugkar, Elad Liebman, and Peter Stone. Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July 2020.
  15-minute presentation
  Details     BibTeX     Download: [pdf] (3.9MB )  

• Justin Hart, Reuth Mirsky, Xuesu Xiao, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter Stone. Using Human-Inspired Signals to Disambiguate Navigational Intentions. In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
  Video presentation
  Details     BibTeX     Download: [pdf] (3.2MB )  

• Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, and Peter Stone. Reinforced Grounded Action Transformation for Sim-to-Real Transfer. In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
  14-minute video presentation.
  Details     BibTeX     Download: [pdf] (506.6kB )  

• Shih-Yun Lo, Shiqi Zhang, and Peter Stone. The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation. 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 )  

• Keting Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen. Learning and Reasoning for Robot Dialog and Navigation Tasks. 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 )  

• Reuth Mirsky, William Macke, Andy Wang, Harel Yedidsion, and Peter Stone. A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork. 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 )  

• Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, and Peter Stone. Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. Journal of Machine Learning Research, 21(181):1–50, 2020.
  Details     BibTeX     Download: [pdf] (1.4MB )  

• Sanmit Narvekar and Peter Stone. Generalizing Curricula for Reinforcement Learning. 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 )  

• Jin-Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone. Learning to Improve Multi-Robot Hallway Navigation. In Proceedings of the 4th Conference on Robot Learning (CoRL), November 2020.
  Video presentation
  Details     BibTeX     Download: [pdf] (1.3MB )  

• Brahma Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, and Peter Stone. RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration. IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS), 5:6262–69, October 2020.
  Video of the experiments; 13-minute video presentation.
  Details     BibTeX     Download: [pdf] (405.1kB )  [slides.pptx] (115.4MB )  

• Brahma Pavse, Ishan Durugkar, Josiah Hanna, and Peter Stone. Reducing Sampling Error in Batch Temporal Difference Learning. 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 )  

• Brahma S. Pavse, Josiah P. Hanna, Ishan Durugkar, and Peter Stone. On Sampling Error in Batch Action-Value Prediction Algorithms. In In the Offline Reinforcement Learning Workshop at Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
  5-mins Video Presentation
  Details     BibTeX     Download: [pdf] (327.2kB )  

• Rishi Shah, Yuqian Jiang, Justin Hart, and Peter Stone. Deep R-Learning for Continual Area Sweeping. 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 )  

• Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney. Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog. The Journal of Artificial Intelligence Research (JAIR), 67, February 2020.
  Details     BibTeX     Download: [pdf] (4.0MB )  

• Lemeng Wu, Bo Liu, Peter Stone, and Qiang Liu. Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks. In Advances in Neural Information Processing Systems 34 (2020), December 2020.
  Details     BibTeX     Download: [pdf] (8.1MB )  [slides.pdf] (744.8kB )  

• Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, and Peter Stone. APPLD: Adaptive Planner Parameter Learning from Demonstration. IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS), June 2020.
  5-minute Video presentation; 15-minute Video presentation
  Project webpage
  Details     BibTeX     Download: [pdf] (2.2MB )  [slides.pdf] (21.1MB )  

• Manish Ravula, Shani Alkobi and Peter Stone. Ad hoc Teamwork with Behavior Switching Agents. In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (350.4kB )  

• Josiah Hanna, Scott Niekum, and Peter Stone. Importance Sampling Policy Evaluation with an Estimated Behavior Policy. In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
  Details     BibTeX     Download: [pdf] (2.7MB )  [slides.pdf] (4.0MB )  

• Josiah Hanna and Peter Stone. Reducing Sampling Error in Policy Gradient Learning. 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 )  

• Josiah Hanna, Guni Sharon, Stephen Boyles, and Peter Stone. Selecting Compliant Agents for Opt-in Micro-Tolling. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), January 2019.
  Details     BibTeX     Download: [pdf] (2.2MB )  

• Yuqian Jiang, Shiqi Zhang, Piyush Khandelwal, and Peter Stone. Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems. 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 )  

• Yuqian Jiang, Harel Yedidsion, Shiqi Zhang, Guni Sharon, and Peter Stone. Multi-Robot Planning with Conflicts and Synergies. Autonomous Robots, Springer, March 2019.
  Official version from Publisher's Webpage
  Details     BibTeX     Download: [pdf] (2.0MB )  

• Yuqian Jiang, Fangkai Yang, Shiqi Zhang, and Peter Stone. Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
  Details     BibTeX     Download: [pdf] (925.2kB )  

• Yuqian Jiang, Nick Walker, Justin Hart, and Peter Stone. Open-World Reasoning for Service Robots. In Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
  Accompanying video
  Details     BibTeX     Download: [pdf] (813.5kB )  

• Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone Peter Stone. The right music at the right time: adaptive personalized playlists based on sequence modeling. 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 )  

• Patrick MacAlpine, Faraz Torabi, Brahma Pavse, and Peter Stone. UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions. 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     BibTeX     Download: [pdf] (233.2kB )  [ps] (3.8MB )  

• Patrick MacAlpine, Faraz Torabi, Brahma Pavse, John Sigmon, and Peter Stone. UT Austin Villa: RoboCup 2018 3D Simulation League Champions. 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     BibTeX     Download: [pdf] (486.2kB )  [ps] (6.0MB )  

• Sanmit Narvekar and Peter Stone. Learning Curriculum Policies for Reinforcement Learning. 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 )  

• Rishi Shah, Yuqian Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta, Rachel Schlossman, Marika Murphy, Justin Hart, Luis Sentis, and Peter Stone. Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report. 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: [pdf] (4.5MB )  

• Guni Sharon, Stephen D. Boyles, Shani Alkoby, and Peter Stone. Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks. 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 )  

• Felipe Leno Da Silva, Garrett Warnell, Anna Helena Reali Costa, and Peter Stone. Agents teaching agents: a survey on inter-agent transfer learning. Autonomous Agents and Multi-Agent Systems, Dec 2019.
  Official version from JAAMAS
  Details     BibTeX     Download: [pdf] (572.4kB )  

• Felipe Leno Da Silva, Anna Helena Reali Costa, and Peter Stone. Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games. In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
  Details     BibTeX     Download: [pdf] (1.6MB )  

• Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond Mooney. Improving Grounded Natural Language Understanding through Human-Robot Dialog. In Proceedings of the International Conference on Robotics and Automation (ICRA 2019), May 2019.
  Details     BibTeX     Download: [pdf] (1.6MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Imitation Learning from Video by Leveraging Proprioception. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (1.1MB )  [slides.pptx] (20.3MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Recent Advances in Imitation Learning from Observation. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (157.4kB )  [slides.pptx] (45.5MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Generative Adversarial Imitation from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (1.0MB )  

• Faraz Torabi, Sean Geiger, Garrett Warnell, and Peter Stone. Sample-efficient Adversarial Imitation Learning from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (6.1MB )  

• Nick Walker, Yuqian Jiang, Maya Cakmak, and Peter Stone. Desiderata for Planning Systems in General-Purpose Service Robots. In Proceedings of the ICAPS Workshop on Planning and Robotics (PlanRob 2019), July 2019.
  Details     BibTeX     Download: [pdf] (651.5kB )  

• Harel Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter Stone, and Raymond Mooney. Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance. In International Conference on Social Robotics (ICSR), pp. 133–143, November 2019.
  Details     BibTeX     Download: [pdf] (958.6kB )  

• Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, and Peter Stone. Leveraging Human Guidance for Deep Reinforcement Learning Tasks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (471.1kB )  [slides.pdf] (1.2MB )  

• Stefano Albrecht and Peter Stone. Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems. Artificial Intelligence, 258:66–95, Elsevier, 2018.
  Available from the publisher's webpage and arXiv
  Details     BibTeX     Download: [pdf] (670.7kB )  

• Saeid Amiri, Suhua Wei, Shiqi Zhang, Jivko Sinapov, Jesse Thomason, and Peter Stone. Multi-modal Predicate Identification using Dynamically Learned Robot Controllers. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), July 2018.
  Details     BibTeX     Download: [pdf] (2.5MB )  

• Haipeng Chen, Bo An, Guni Sharon, Josiah P. Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh. DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), February 2018.
  Details     BibTeX     Download: [pdf] (2.4MB )  [ps] (5.9MB )  

• Rolando Fernandez, Nathan John, Sean Kirmani, Justin Hart, Jivko Sinapov, and Peter Stone. Passive Demonstrations of Light-Based Robot Signals for Improved Human Interpretability. In Proceedings of the 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), August 2018.
  Details     BibTeX     Download: [pdf] (8.5MB )  [slides.pdf] (983.4kB )  

• Josiah Hanna and Peter Stone. Towards a Data Efficient Off-Policy Policy Gradient. In AAAI Spring Symposium on Data Efficient Reinforcement Learning, March 2018.
  Details     BibTeX     Download: [pdf] (345.4kB )  

• Justin W. Hart, Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter Stone. PRISM: Pose Registration for Integrated Semantic Mapping. In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2018.
  Details     BibTeX     Download: [pdf] (4.4MB )  

• Yu-Sian Jiang, Garrett Warnell, and Peter Stone. Inferring User Intention using Gaze in Vehicles. In The 20th ACM International Conference on Multimodal Interaction (ICMI), October 2018.
  Available from AAAI/PAIR and to appear at ICMI
  Details     BibTeX     Download: [pdf] (2.6MB )  

• Yu-Sian Jiang, Garrett Warnell, Eduardo Munera, and Peter Stone. A Study of Human-Robot Copilot Systems for En-Route Destination Changing. In Proceedings of the 27th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN2018), August 2018.
  Available from RO-MAN
  Details     BibTeX     Download: [pdf] (5.8MB )  [slides.pptx] (32.7MB )  

• 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. Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas --- Final Report. Technical Report 0-6838-3, The University of Texas at Austin Center for Transportation Research, 2018.
  Available online
  Details     BibTeX     Download: (unavailable)

• Elad Liebman, Eric Zavesky, and Peter Stone. A Stitch in Time - Autonomous Model Management via Reinforcement Learning. In Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018.
  Details     BibTeX     Download: [pdf] (1.7MB )  

• Elad Liebman, Corey N. White, and Peter Stone. On the Impact of Music on Decision Making in Cooperative Tasks. In 19th International Society for Music Information retrieval Conference (ISMIR), September 2018.
  Details     BibTeX     Download: [pdf] (258.5kB )  

• Patrick MacAlpine and Peter Stone. Overlapping Layered Learning. 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     BibTeX     Download: [pdf] (1.2MB )  [ps] (3.8MB )  

• Patrick MacAlpine and Peter Stone. UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions. 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     BibTeX     Download: [pdf] (973.5kB )  [ps] (19.4MB )  

• Jacob Menashe and Peter Stone. State Abstraction Synthesis for Discrete Models of Continuous Domains. In Data Efficient Reinforcement Learning Workshop at AAAI Spring Symposium, March 2018.
  Details     BibTeX     Download: [pdf] (538.3kB )  [ps] (5.3MB )  

• Decebal Constantin Mocanu, Elena Mocanu, Peter Stone, Phuong H. Nguyen, Madeleine Gibescu, and Antonio Liotta. Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science. Nature Communications, 9(2383), June 2018.
  Official version from Publisher's Webpage.
  Details     BibTeX     Download: [pdf] (1.5MB )  

• Prabhat Nagarajan, Garrett Warnell, and Peter Stone. Deterministic Implementations for Reproducibility in Deep Reinforcement Learning. In 2nd Reproducibility in Machine Learning Workshop at ICML 2018, July 2018.
  Details     BibTeX     Download: [pdf] (6.6MB )  

• Ori Ossmy, Justine E. Hoch, Patrick MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph. Variety Wins: Soccer-Playing Robots and Infant Walking. Frontiers in Neurorobotics, 12:19, 2018.
  Available from the publisher's webpage
  Details     BibTeX     Download: [pdf] (2.9MB )  

• Aishwarya Padmakumar, Peter Stone, and Raymond J. Mooney. Learning a Policy for Opportunistic Active Learning. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-18), Brussels, Belgium, November 2018.
  Details     BibTeX     Download: [pdf] (394.3kB )  

• Tarun Rambha, Stephen D. Boyles, Avinash Unnikrishnan, and Peter Stone. Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty. Transportation Research Part B: Methodological, 110:104–21, 2018.
  Official version from Publisher's Webpage
  Details     BibTeX     Download: [pdf] (1.6MB )  

• Guni Sharon, Michael Albert, Tarun Rambha, Stephen Boyles, and Peter Stone. Traffic Optimization For a Mixture of Self-interested and Compliant Agents. 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 )  

• Jesse Thomason, Jivko Sinapov, Raymond J. Mooney, and Peter Stone. Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions. In Proceedings of the 32nd Conference on Artificial Intelligence (AAAI), February 2018.
  Details     BibTeX     Download: [pdf] (1.4MB )  

• Garrett Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone. Deep TAMER: Interactive agent shaping in high-dimensional state spaces. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, February 2018.
  Details     BibTeX     Download: [pdf] (1.6MB )  [slides.pptx] (16.2MB )  

• Michael Albert, Vincent Conitzer, and Peter Stone. Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), May 2017.
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• Michael Albert, Vincent Conitzer, and Peter Stone. Automated Design of Robust Mechanisms. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), Feb 2017.
  Details     BibTeX     Download: [pdf] (366.4kB )  [slides.pdf] (2.7MB )  

• Stefano Albrecht, Somchaya Liemhetcharat, and Peter Stone. Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial. Autonomous Agents and Multi-Agent Systems, 31(4):765–66, July 2017.
  Official version from Publisher's Webpage
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• Stefano Albrecht and Peter Stone. Reasoning about Hypothetical Agent Behaviours and their Parameters. 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 )  

• Ishan Durugkar and Peter Stone. TD Learning with Constrained Gradients. In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017, December 2017.
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• Katie Genter, Tim Laue, and Peter Stone. Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale Ad Hoc Teamwork Robotics Competition. Autonomous Agents and Multi-Agent Systems (JAAMAS), 31(4):790–820, Springer, July 2017.
  Official version from Publisher's Webpage
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• Santiago Gonzalez, Vijay Chidambaram, Jivko Sinapov, and Peter Stone. CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression. In Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '17), July 2017.
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• Josiah Hanna, Philip Thomas, Peter Stone, and Scott Niekum. Data-Efficient Policy Evaluation Through Behavior Policy Search. In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
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• Josiah Hanna, Peter Stone, and Scott Niekum. Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. 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 )  

• Josiah Hanna and Peter Stone. Grounded Action Transformation for Robot Learning in Simulation. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
  Details     BibTeX     Download: [pdf] (1.3MB )  [slides.pdf] (1.3MB )  

• Matthew Hausknecht, Wen-Ke Li, Michael Mauk, and Peter Stone. Machine Learning Capabilities of a Simulated Cerebellum. "IEEE Transactions on Neural Networks and Learning Systems", 28(3):510–22, March 2017.
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• Todd Hester and Peter Stone. Intrinsically motivated model learning for developing curious robots. Artificial Intelligence, 247:170–86, June 2017.
  from journal website.
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• 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. BWIBots: A platform for bridging the gap between AI and human--robot interaction research. The International Journal of Robotics Research, 36(5--7):635–59, 2017.
  Accompanying videos at https://youtu.be/2UJG4-ejVww
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• Piyush Khandelwal and Peter Stone. Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.
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• 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. An Assessment of Autonomous Vehicles: Traffic Impacts and Infrastructure Needs --- Final Report. Technical Report 0-6847-1, The University of Texas at Austin Center for Transportation Research, 2017.
  Available online
  Details     BibTeX     Download: (unavailable)

• Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, and Peter Stone. Designing Better Playlists with Monte Carlo Tree Search. In Proceedings of the Twenty-Ninth Conference On Innovative Applications Of Artificial Intelligence (IAAI-17), February 2017.
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• Shih-Yun Lo, Benito Fernandez, and Peter Stone. Iterative Human-Aware Mobile Robot Navigation. In Proceedings of the Human-Centered Robotics workshop of the 13th International Conference on Robotics: Science and System (RSS), July 2017.
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• Dongcai Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen. Leveraging Commonsense Reasoning and Multimodal Perception for Robot Spoken Dialog Systems. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2017.
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• Patrick MacAlpine and Peter Stone. Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges. 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.
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• Patrick MacAlpine and Peter Stone. UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions. 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
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• Patrick MacAlpine and Peter Stone. Prioritized Role Assignment for Marking. 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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• Patrick MacAlpine and Peter Stone. UT Austin Villa RoboCup 3D Simulation Base Code Release. 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
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• Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, and Peter Stone. Fast and Precise Black and White Ball Detection for RoboCup Soccer. In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
  Details     BibTeX     Download: [pdf] (254.2kB )  [ps] (716.1kB )  [slides.pdf] (1.5MB )  

• Sanmit Narvekar, Jivko Sinapov, and Peter Stone. Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August 2017.
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• Guni Sharon, Michael W. Levin, Josiah P. Hanna, Tarun Rambha, Stephen D. Boyles, and Peter Stone. Network-wide Adaptive Tolling for Connected and Automated vehicles. 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: [pdf] (2.8MB )  [ps] (4.2MB )  

• Guni Sharon and Peter Stone. A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections. 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.
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• Maxwell Svetlik, Matteo Leonetti, Jivko Sinapov, Rishi Shah, Nick Walker, and Peter Stone. Automatic Curriculum Graph Generation for Reinforcement Learning Agents. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
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• Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Justin Hart, Peter Stone, and Raymond J. Mooney. Opportunistic Active Learning for Grounding Natural Language Descriptions. In Proceedings of the 1st Annual Conference on Robot Learning (CoRL-17), pp. 67–76, PMLR, Mountain View, California, November 2017.
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• Shiqi Zhang, Yuqian Jiang, Guni Sharon, and Peter Stone. Multirobot Symbolic Planning under Temporal Uncertainty. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS), May 2017.
  Accompanying videos at https://youtu.be/ADbH3sppLHQ
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• Shiqi Zhang, Piyush Khandelwal, and Peter Stone. Dynamically Constructed (PO)MDPs for Adaptive Robot Planning. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
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• Shiqi Zhang and Peter Stone. Integrated Commonsense Reasoning and Probabilistic Planning. In Proceedings of 2017 ICAPS Workshop on Planning and Robotics, June 2017.
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• Tsz-Chiu Au, Shun Zhang, and Peter Stone. Autonomous Intersection Management for Semi-Autonomous Vehicles. In Dusan Teodorovi'c, editors, Handbook of Transportation, pp. 88–104, Routledge, 2016.
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• Samuel Barrett, Avi Rosenfeld, Sarit Kraus, and Peter Stone. Making Friends on the Fly: Cooperating with New Teammates. Artificial Intelligence, October 2016.
  Official version from journal website.
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• Ginevra Gaudioso, Matteo Leonetti, and Peter Stone. State Aggregation through Reasoning in Answer Set Programming. In Proceedings of the IJCAI Workshop on Autonomous Mobile Service Robots (WSR 16), July 2016.
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• Katie Genter and Peter Stone. Ad Hoc Teamwork Behaviors for Influencing a Flock. Acta Polytechnica, 56(1), 2016.
  Details     BibTeX     Download: [pdf] (421.5kB )  [ps] (1.6MB )  

• Katie Genter and Peter Stone. Adding Influencing Agents to a Flock. 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 )  

• Jonathan Grizou, Samuel Barrett, Manuel Lopes, and Peter Stone. Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (339.0kB )  

• Josiah P. Hanna, Michael Albert, Donna Chen, and Peter Stone. Minimum Cost Matching for Autonomous Carsharing. 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 )  

• Matthew Hausknecht and Peter Stone. Deep Reinforcement Learning in Parameterized Action Space. In Proceedings of the International Conference on Learning Representations (ICLR), May 2016.
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• Matthew Hausknecht and Peter Stone. Grounded Semantic Networks for Learning Shared Communication Protocols. In Deep Reinforcement Learning, NIPS Workshop, December 2016.
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• Matthew Hausknecht and Peter Stone. On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning. In Deep Reinforcement Learning: Frontiers and Challenges, IJCAI Workshop, July 2016.
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• Matthew Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan, and Peter Stone. Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
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• Matthew Hausknecht, Yilun Chen, and Peter Stone. Deep Imitation Learning for Parameterized Action Spaces. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
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• Kazunori Iwata, Elad Liebman, Peter Stone, Toyoshiro Nakashima, Yoshiyuki Anan, and Naohiro Ishii. Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines. In Roger Lee, editors, Computer and Information Science 2015, Studies in Computational Intelligence, Springer Verlag, Berlin, 2016.
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• Piyush Khandelwal, Elad Liebman, Scott Niekum, and Peter Stone. On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search. In Proceedings of The 33rd International Conference on Machine Learning, pp. 1319–1328, June 2016.
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• 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. Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas --- Final Report. Technical Report 0-6838-2, The University of Texas at Austin Center for Transportation Research, 2016.
  Available online
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• Matteo Leonetti, Luca Iocchi, and Peter Stone. A synthesis of automated planning and reinforcement learning for efficient, robust decision-making. Artificial Intelligence, 241:103 – 130, September 2016.
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• David L. Leottau, Javier Ruiz-del-Solar, Patrick MacAlpine, and Peter Stone. A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer. 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.
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• Elad Liebman, Peter Stone, and Corey N. White. Impact of Music on Decision Making in Quantitative Tasks. In 17th International Society for Music Information retrieval Conference (ISMIR), August 2016.
  Details     BibTeX     Download: [pdf] (591.1kB )  [slides.pdf] (678.6kB )  

• Patrick MacAlpine, Josiah Hanna, Jason Liang, and Peter Stone. UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions. 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     BibTeX     Download: [pdf] (790.2kB )  [ps] (7.2MB )  

• Patrick MacAlpine, Elad Liebman, and Peter Stone. Adaptation of Surrogate Tasks for Bipedal Walk Optimization. In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.
  Details     BibTeX     Download: [pdf] (172.1kB )  [ps] (739.5kB )  [slides.pdf] (165.0MB )  

• Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, and Peter Stone. Source Task Creation for Curriculum Learning. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
  Details     BibTeX     Download: [pdf] (630.0kB )  [slides.pdf] (10.2MB )  

• Jivko Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone. Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
  Details     BibTeX     Download: [pdf] (6.6MB )  [slides.pdf] (5.2MB )  

• Jesse Thomason, Jivko Sinapov, Maxwell Svetlik, Peter Stone, and Raymond Mooney. Learning Multi-Modal Grounded Linguistic Semantics by Playing I Spy. In Proceedings of the 25th international joint conference on Artificial Intelligence (IJCAI), July 2016.
  Demo Video
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• Daniel Urieli and Peter Stone. An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
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• Daniel Urieli and Peter Stone. Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market. In Proceedings of the 30th Conference on Artificial Intelligence (AAAI 2016), February 2016.
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• Shiqi Zhang, Dongcai Lu, Xiaoping Chen, and Peter Stone. Robot Scavenger Hunt: A Standardized Framework for Evaluating Intelligent Mobile Robots. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
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• Samuel Barrett and Peter Stone. Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 2015.
  Details     BibTeX     Download: [pdf] (993.2kB )  [ps] (2.8MB )  

• Mike Depinet, Patrick MacAlpine, and Peter Stone. Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League. 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
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• Fei Fang, Peter Stone, and Milind Tambe. When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing. 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     BibTeX     Download: [pdf] (456.7kB )  [ps] (983.9kB )  [slides.pptx] (6.2MB )  

• Katie Genter, Shun Zhang, and Peter Stone. Determining Placements of Influencing Agents in a Flock. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
  Details     BibTeX     Download: [pdf] (426.7kB )  [ps] (1.4MB )  [slides.pdf] (1.6MB )  

• Ilaria Gori, Jivko Sinapov, Priyanka Khante, Peter Stone, and J.K. Aggarwal. Robot-centric Activity Recognition 'in the Wild'. In Proceedings of the International Conference on Social Robotics (ICSR), October 2015.
  Details     BibTeX     Download: [pdf] (361.3kB )  

• Matthew Hausknecht and Peter Stone. The Impact of Determinism on Learning Atari 2600 Games. In AAAI Workshop on Learning for General Competency in Video Games, January 2015.
  Details     BibTeX     Download: [pdf] (65.1kB )  

• Matthew Hausknecht and Peter Stone. Deep Recurrent Q-Learning for Partially Observable MDPs. In AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents (AAAI-SDMIA15), November 2015.
  Details     BibTeX     Download: [pdf] (1.5MB )  [slides.pdf] (3.8MB )  

• Piyush Khandelwal, Samuel Barrett, and Peter Stone. Leading the Way: An Efficient Multi-robot Guidance System. 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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• W. Bradley Knox and Peter Stone. Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance. 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     BibTeX     Download: [pdf] (3.9MB )  

• Elad Liebman, Benny Chor, and Peter Stone. Representative Selection in Nonmetric Datasets. "Applied Artificial Intelligence", 29:807–838, 2015.
  Details     BibTeX     Download: [pdf] (846.3kB )  

• Elad Liebman, Peter Stone, and Corey N. White. How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification. In 16th International Society for Music Information retrieval Conference (ISMIR), October 2015.
  Details     BibTeX     Download: [pdf] (832.6kB )  [ps] (6.3MB )  [slides.pdf] (2.0MB )  

• Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone. DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
  Details     BibTeX     Download: [pdf] (1.5MB )  [ps] (38.4MB )  [slides.pdf] (2.6MB )  

• Patrick MacAlpine, Mike Depinet, Jason Liang, and Peter Stone. UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions. 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     BibTeX     Download: [pdf] (235.7kB )  [ps] (1.9MB )  

• Patrick MacAlpine, Mike Depinet, and Peter Stone. UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning. 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     BibTeX     Download: [pdf] (714.7kB )  [ps] (2.5MB )  [slides.pdf] (105.3MB )  

• Patrick MacAlpine, Eric Price, and Peter Stone. SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning. 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     BibTeX     Download: [pdf] (260.3kB )  [ps] (676.5kB )  [slides.pdf] (40.3MB )  

• Jacob Menashe and Peter Stone. Monte Carlo Hierarchical Model Learning. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
  Details     BibTeX     Download: [pdf] (693.2kB )  [ps] (18.4MB )  

• Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, and Peter Stone. Learning Inter-Task Transferability in the Absence of Target Task Samples. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2015.
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• Jesse Thomason, Shiqi Zhang, Raymond Mooney, and Peter Stone. Learning to Interpret Natural Language Commands through Human-Robot Dialog. In Proceedings of the 2015 International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
  Demo
  Details     BibTeX     Download: [pdf] (1.4MB )  [slides.pdf] (1.1MB )  

• Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone. Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy. In Proceedings of the 13th International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR), September 2015.
  Demo Video
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• Shiqi Zhang and Peter Stone. CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot. In Proceedings of the 29th Conference on Artificial Intelligence (AAAI), January 2015.
  Details     BibTeX     Download: [pdf] (306.0kB )  [ps] (1.5MB )  

• Noa Agmon, Samuel Barrett, and Peter Stone. Modeling Uncertainty in Leading Ad Hoc Teams. In Proc. of 13th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2014.
  Details     BibTeX     Download: [pdf] (255.6kB )  [ps] (1.7MB )  

• Samuel Barrett, Noa Agmon, Noam Hazon, Sarit Kraus, and Peter Stone. Communicating with Unknown Teammates. In Proceedings of the Twenty-First European Conference on Artificial Intelligence, August 2014.
  Details     BibTeX     Download: [pdf] (215.9kB )  [ps] (2.6MB )  [slides.pdf] (1.4MB )  

• Katie Genter and Peter Stone. Influencing a Flock via Ad Hoc Teamwork. In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
  Details     BibTeX     Download: [pdf] (358.4kB )  [ps] (1.4MB )  [slides.pdf] (15.3MB )  

• Matthew Hausknecht, Joel Lehman, Risto Miikkulainen, and Peter Stone. A Neuroevolution Approach to General Atari Game Playing. IEEE Transactions on Computational Intelligence and AI in Games, 2014.
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• Piyush Khandelwal, Fangkai Yang, Matteo Leonetti, Vladimir Lifschitz, and Peter Stone. Planning in Action Language $\cal BC$ while Learning Action Costs for Mobile Robots. In International Conference on Automated Planning and Scheduling (ICAPS), June 2014.
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• Piyush Khandelwal and Peter Stone. Multi-robot Human Guidance using Topological Graphs. In AAAI Spring 2014 Symposium on Qualitative Representations for Robots (AAAI-SSS), March 2014.
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• Patrick MacAlpine, Katie Genter, Samuel Barrett, and Peter Stone. The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork. 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
  Details     BibTeX     Download: [pdf] (491.0kB )  [ps] (4.0MB )  [slides.pdf] (30.4MB )  

• Daniel Urieli and Peter Stone. TacTex'13: A Champion Adaptive Power Trading Agent. In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI 2014), July 2014.
  Details     BibTeX     Download: [pdf] (257.8kB )  [ps] (7.3MB )  [slides.pdf] (3.8MB )  

• Fangkai Yang, Piyush Khandelwal, Matteo Leonetti, and Peter Stone. Planning in Answer Set Programming while Learning Action Costs for Mobile Robots. In AAAI Spring 2014 Symposium on Knowledge Representation and Reasoning in Robotics (AAAI-SSS), March 2014.
  Details     BibTeX     Download: [pdf] (643.4kB )  [ps] (5.3MB )  

• Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone. The 2012 UT Austin Villa Code Release. In RoboCup-2013: Robot Soccer World Cup XVII, Springer Verlag, 2013.
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• Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone. UT Austin Villa 2012: Standard Platform League World Champions. 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.
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• Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld. Teamwork with Limited Knowledge of Teammates. In Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, July 2013.
  Details     BibTeX     Download: [pdf] (190.1kB )  [ps] (2.0MB )  

• Dustin Carlino, Stephen D. Boyles, and Peter Stone. Auction-based autonomous intersection management. In Proceedings of the 16th IEEE Intelligent Transportation Systems Conference (ITSC), October 2013.
  Details     BibTeX     Download: [pdf] (318.1kB )  [ps] (1.4MB )  

• Doran Chakraborty and Peter Stone. Multiagent Learning in the Presence of Memory-Bounded Agents. Autonomous Agents and Multiagent Systems (JAAMAS), Springer, 2013.
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• Doran Chakraborty and Peter Stone. Cooperating with a Markovian Ad Hoc Teammate. In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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• Doran Chakraborty, Noa Agmon, and Peter Stone. Targeted Opponent Modeling of Memory-Bounded Agents. In Proceedings of the Adaptive Learning Agents Workshop (ALA), May 2013.
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• Alon Farchy, Samuel Barrett, Patrick MacAlpine, and Peter Stone. Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back. 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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• Katie Genter, Noa Agmon, and Peter Stone. Role-Based Ad Hoc Teamwork. 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.
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• Katie Genter, Noa Agmon, and Peter Stone. Ad Hoc Teamwork for Leading a Flock. In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), May 2013.
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• Katie Genter, Noa Agmon, and Peter Stone. Improving Efficiency of Leading a Flock in Ad Hoc Teamwork Settings. In AAMAS Autonomous Robots and Multirobot Systems (ARMS) Workshop, May 2013.
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• Todd Hester and Peter Stone. TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots. Machine Learning, 90(3):385–429, 2013.
  Official version from journal website.
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• Todd Hester and Peter Stone. The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots. 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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• Todd Hester, Manuel Lopes, and Peter Stone. Learning Exploration Strategies in Model-Based Reinforcement Learning. In The Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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• W. Bradley Knox, Peter Stone, and Cynthia Breazeal. Training a Robot via Human Feedback: A Case Study. In International Conference on Social Robotics, October 2013.
  BEST PAPER AWARD WINNER at ICSR 2013
  An associated video summarizing the paper (direct link).
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• Patrick MacAlpine, Nick Collins, Adrian Lopez-Mobilia, and Peter Stone. UT Austin Villa: RoboCup 2012 3D Simulation League Champion. 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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• Patrick MacAlpine, Francisco Barrera, and Peter Stone. Positioning to Win: A Dynamic Role Assignment and FormationPositioning System. 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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• Patrick MacAlpine, Elad Liebman, and Peter Stone. Simultaneous Learning and Reshaping of an Approximated Optimization Task. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
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• Jacob Menashe, Katie Genter, Samuel Barrett, and Peter Stone. UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy. In The Eighth Workshop on Humanoid Soccer Robots at Humanoids 2013, October 2013.
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• Peter Stone, Gal A. Kaminka, Sarit Kraus, Jeffrey S. Rosenschein, and Noa Agmon. Teaching and leading an ad hoc teammate: Collaboration without pre-coordination. Artificial Intelligence, 203:35–65, Elsevier, October 2013.
  Official version from journal website.
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• Daniel Urieli and Peter Stone. Model-Selection for Non-Parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System. 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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• Daniel Urieli and Peter Stone. A Learning Agent for Heat-Pump Thermostat Control. In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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• Noa Agmon and Peter Stone. Leading Ad Hoc Agents in Joint Action Settings with Multiple Teammates. In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
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• Noa Agmon, Chien-Liang Fok, Yehuda Emaliah, Peter Stone, Christine Julien, and Sriram Vishwanath. On Coordination in Practical Multi-Robot Patrol. In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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• Tsz-Chiu Au, Michael Quinlan, and Peter Stone. Setpoint Scheduling for Autonomous Vehicle Controllers. In Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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• Aijun Bai, Xiaoping Chen, Patrick MacAlpine, Daniel Urieli, Samuel Barrett, and Peter Stone. Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions. 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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• Samuel Barrett and Peter Stone. An Analysis Framework for Ad Hoc Teamwork Tasks. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
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• Samuel Barrett, Katie Genter, Todd Hester, Piyush Khandelwal, Michael Quinlan, Peter Stone, and Mohan Sridharan. Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing. Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2012.
  Details     BibTeX     Download: [pdf] (1.1MB )  [ps] (32.8MB )  

• Dustin Carlino, Mike Depinet, Piyush Khandelwal, and Peter Stone. Approximately Orchestrated Routing and Transportation Analyzer: Large-scale Traffic Simulation for Autonomous Vehicles. In Proceedings of the 15th IEEE Intelligent Transportation Systems Conference (ITSC), September 2012.
  Details     BibTeX     Download: [pdf] (727.1kB )  [ps] (14.3MB )  

• David Fajardo, Tsz-Chiu Au, Travis Waller, Peter Stone, and David Yang. Automated Intersection Control: Performance of a Future Innovation Versus Current Traffic Signal Control. Transportation Research Record (TRR), 2259:223–32, 2012.
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• Matthew Hausknecht, Piyush Khandelwal, Risto Miikkulainen, and Peter Stone. HyperNEAT-GGP: A HyperNEAT-based Atari General Game Player. In Genetic and Evolutionary Computation Conference (GECCO), July 2012.
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• Todd Hester, Michael Quinlan, and Peter Stone. RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control. In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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• Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, and Peter Stone. PAC Subset Selection in Stochastic Multi-armed Bandits. 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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• Piyush Khandelwal and Peter Stone. A Low Cost Ground Truth Detection System Using the Kinect. 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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• W. Bradley Knox, Brian D. Glass, Bradley C. Love, W. Todd Maddox, and Peter Stone. How Humans Teach Agents: A New Experimental Perspective. 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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• W. Bradley Knox, A. Ross Otto, Peter Stone, and Bradley Love. The Nature of Belief-Directed Exploratory Choice in Human Decision-Making. Frontiers in Psychology, 2(398), January 2012.
  Frontiers in Psychology
  Download article from publisher (free)
  A follow-up commentary by Erica Yu.
  Details     BibTeX     Download: (unavailable)

• W. Bradley Knox and Peter Stone. Reinforcement Learning from Simultaneous Human and MDP Reward. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
  AAMAS 2012
  Details     BibTeX     Download: [pdf] (929.6kB )  [ps] (4.9MB )  

• W. Bradley Knox, Cynthia Breazeal, and Peter Stone. Learning from feedback on actions past and intended. In Proceedings of 7th ACM/IEEE International Conference on Human-Robot Interaction, Late-Breaking Reports Session (HRI), March 2012.
  HRI 2012
  Details     BibTeX     Download: [pdf] (447.6kB )  [ps] (3.9MB )  

• Wen-Ke Li, Matthew J. Hausknecht, Peter Stone, and Michael D. Mauk. Using a million cell simulation of the cerebellum: Network scaling and task generality. Neural Networks, November 2012.
  Details     BibTeX     Download: [pdf] (765.8kB )  [ps] (2.5MB )  

• Patrick MacAlpine, Samuel Barrett, Daniel Urieli, Victor Vu, and Peter Stone. Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition. 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     BibTeX     Download: [pdf] (461.2kB )  [ps] (2.0MB )  [slides.pdf] (204.2MB )  

• Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae \cStiurc\ua, Victor Vu, and Peter Stone. UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition. 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     BibTeX     Download: [pdf] (646.3kB )  [ps] (2.7MB )  [slides.pdf] (135.4MB )  

• Patrick MacAlpine and Peter Stone. Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk. 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
  Ukrainian translation by Domri team
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• Noa Agmon, Daniel Urieli, and Peter Stone. Multiagent Patrol Generalized to Complex Environmental Conditions. In Proceedings of the Twenty-Fifth Conference on ArtificialIntelligence (AAAI), August 2011.
  Extended version, book chapter
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• Tsz-Chiu Au, Neda Shahidi, and Peter Stone. Enforcing Liveness in Autonomous Traffic Management. In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
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• Samuel Barrett, Peter Stone, and Sarit Kraus. Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain. In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
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• Samuel Barrett and Peter Stone. Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards. In Tenth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
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• Samuel Barrett, Katie Genter, Matthew Hausknecht, Todd Hester, Piyush Khandelwal, Juhyun Lee, Michael Quinlan, Aibo Tian, Peter Stone, and Mohan Sridharan. Austin Villa 2010 Standard Platform Team Report. Technical Report UT-AI-TR-11-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2011.
  Details     BibTeX     Download: [pdf] (1.3MB )  [ps] (38.0MB )  

• Doran Chakraborty and Peter Stone. Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree. In Proceedings of the Twenty Eighth International Conference on Machine Learning (ICML), 2011.
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• Matthew Hausknecht, Tsz-Chiu Au, Peter Stone, David Fajardo, and Travis Waller. Dynamic Lane Reversal in Traffic Management. In Proceedings of IEEE Intelligent Transportation Systems Conference (ITSC), 2011.
  Details     BibTeX     Download: [pdf] (127.0kB )  [ps] (4.3MB )  

• Matthew Hausknecht, Tsz-Chiu Au, and Peter Stone. Autonomous Intersection Management: Multi-Intersection Optimization. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2011.
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• Todd Hester and Peter Stone. Learning and Using Models. In Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Springer Verlag, Berlin, Germany, 2011.
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• Shivaram Kalyanakrishnan and Peter Stone. Characterizing Reinforcement Learning Methods through Parameterized Learning Problems. Machine Learning (MLJ), 84(1--2):205–247, July 2011.
  Publisher's on-line version
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• Shivaram Kalyanakrishnan and Peter Stone. On Learning with Imperfect Representations. In Proceedings of the 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, pp. 17–24, IEEE, April 2011.
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• W. Bradley Knox and Peter Stone. Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report. 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)
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• Raz Lin, Sarit Kraus, Noa Agmon, Samuel Barrett, and Peter Stone. Comparing Agents: Success against People in Security Domains. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, August 2011.
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• Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae\cStiurc\ua, Victor Vu, and Peter Stone. UT Austin Villa 2011 3D Simulation Team Report. Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory, 2011.
  Details     BibTeX     Download: [pdf] (1.2MB )  [ps] (5.3MB )  

• David Pardoe and Peter Stone. Designing Adaptive Trading Agents. ACM SIGecom Exchanges, 10(2):37–9, June 2011.
  SIGecom Exchanges
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• David Pardoe and Peter Stone. A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
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• Matthew E. Taylor and Peter Stone. An Introduction to Inter-task Transfer for Reinforcement Learning. AI Magazine, 32(1):15–34, 2011.
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• Daniel Urieli, Patrick MacAlpine, Shivaram Kalyanakrishnan, Yinon Bentor, and Peter Stone. On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer. 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     BibTeX     Download: [pdf] (530.9kB )  [ps] (1.6MB )  [slides.pptx] (3.8MB )  

• Shimon Whiteson, Brian Tanner, Matthew E. Taylor, and Peter Stone. Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning. In IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), April 2011.
  2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL)
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• Tsz-Chiu Au and Peter Stone. Motion Planning Algorithms for Autonomous Intersection Management. In AAAI 2010 Workshop on Bridging The Gap Between Task And Motion Planning (BTAMP), 2010.
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• Samuel Barrett, Katie Genter, Todd Hester, Michael Quinlan, and Peter Stone. Controlled Kicking under Uncertainty. In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
  Details     BibTeX     Download: [pdf] (357.3kB )  [ps] (17.7MB )  

• Samuel Barrett, Matt E. Taylor, and Peter Stone. Transfer Learning for Reinforcement Learning on a Physical Robot. 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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• Doran Chakraborty and Peter Stone. Convergence, Targeted Optimality and Safety in Multiagent Learning. In Proceedings of the Twenty-seventh International Conference on Machine Learning (ICML), June 2010.
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• Todd Hester and Peter Stone. Real Time Targeted Exploration in Large Domains. In The Ninth International Conference on Development and Learning (ICDL), August 2010.
  ICDL 2010
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• Todd Hester, Michael Quinlan, and Peter Stone. Generalized Model Learning for Reinforcement Learning on a Humanoid Robot. In IEEE International Conference on Robotics and Automation (ICRA), May 2010.
  Video available at http://www.cs.utexas.edu/~AustinVilla/?p=research/rl_kick
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• Tobias Jung and Peter Stone. Gaussian processes for sample efficient reinforcement learning with RMAX-like exploration. In The European Conference on Machine Learning (ECML), September 2010.
  Details     BibTeX     Download: [pdf] (417.0kB )  [ps] (6.5MB )  [slides.pdf] (505.6kB )  

• Shivaram Kalyanakrishnan and Peter Stone. Efficient Selection of Multiple Bandit Arms: Theory and Practice. In Proceedings of the Twenty-seventh International Conference on Machine Learning (ICML), 2010.
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• Piyush Khandelwal, Matthew Hausknecht, Juhyun Lee, Aibo Tian, and Peter Stone. Vision Calibration and Processing on a Humanoid Soccer Robot. In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
  Details     BibTeX     Download: [pdf] (402.6kB )  [ps] (14.8MB )  

• W. Bradley Knox and Peter Stone. Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning. 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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• Itsuki Noda, Peter Stone, Tomohisa Yamashita, and Koichi Kurumatani. Multi-Agent Social Simulation. 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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• David Pardoe, Peter Stone, Maytal Saar-Tsechansky, Tayfun Keskin, and Kerem Tomak. Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge. Informs Journal on Computing, 22(3):353–370, 2010.
  Details     BibTeX     Download: [pdf] (530.9kB )  [ps] (9.2MB )  

• David Pardoe and Peter Stone. The 2007 TAC SCM Prediction Challenge. 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     BibTeX     Download: [pdf] (1.0MB )  [ps] (2.0MB )  

• David Pardoe and Peter Stone. Boosting for Regression Transfer. In Proceedings of the 27th International Conference on Machine Learning (ICML), June 2010.
  Some of the data used in the experiments.
  Details     BibTeX     Download: [pdf] (600.5kB )  [ps] (1.7MB )  

• David Pardoe, Doran Chakraborty, and Peter Stone. TacTex09: A Champion Bidding Agent for Ad Auctions. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), May 2010.
  Details     BibTeX     Download: [pdf] (564.3kB )  [ps] (1.0MB )  

• Michael Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter Stone. Bringing Simulation to Life: A Mixed Reality Autonomous Intersection. 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     BibTeX     Download: [pdf] (1.3MB )  [ps] (10.6MB )  

• Adam Setapen, Michael Quinlan, and Peter Stone. MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training. 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     BibTeX     Download: [pdf] (533.2kB )  [ps] (9.7MB )  

• Peter Stone, Michael Quinlan, and Todd Hester. The Essence of Soccer, Can Robots Play Too?. 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     BibTeX     Download: [pdf] (121.3kB )  [ps] (514.1kB )  

• Peter Stone, Gal A. Kaminka, Sarit Kraus, and Jeffrey S. Rosenschein . Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination. 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 )  

• Peter Stone and Sarit Kraus. To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams. 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     BibTeX     Download: [pdf] (180.6kB )  [ps] (285.3kB )  

• Shimon Whiteson, Matthew E. Taylor, and Peter Stone. Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning. Journal of Autonomous Agents and Multi-Agent Systems, 21(1):1–27, 2010.
  Details     BibTeX     Download: [pdf] (760.6kB )  [ps] (1.9MB )  

• Jonathan Wildstrom, Peter Stone, and Emmett Witchel. Autonomous Return on Investment Analysis of Additional Processing Resources. International Journal on Autonomic Computing, 1(3):280–296, Inderscience Publishers, Inderscience Publishers, Geneva, SWITZERLAND, 2010.
  IJAC
  Details     BibTeX     Download: (unavailable)

• Peter Djeu, Michael Quinlan, and Peter Stone. Improving Particle Filter Performance Using SSE Instructions. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2009.
  Details     BibTeX     Download: [pdf] (176.8kB )  [ps] (2.7MB )  

• Ian Fasel, Michael Quinlan, and Peter Stone. A Task Specification Language for Bootstrap Learning. 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     BibTeX     Download: [pdf] (407.2kB )  [ps] (1.9MB )  

• Todd Hester and Peter Stone. Generalized Model Learning for Reinforcement Learning in Factored Domains. In The Eighth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2009.
  AAMAS 2009
  Details     BibTeX     Download: [pdf] (181.5kB )  [ps] (425.5kB )  

• Todd Hester and Peter Stone. An Empirical Comparison of Abstraction in Models of Markov Decision Processes. In Proceedings of the ICML/UAI/COLT Workshop on Abstraction in Reinforcement Learning, June 2009.
  ICML ARL 2009
  Details     BibTeX     Download: [pdf] (127.0kB )  [ps] (363.0kB )  

• Todd Hester, Michael Quinlan, Peter Stone, and Mohan Sridharan. TT-UT Austin Villa 2009: Naos across Texas. Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory, 2009.
  Details     BibTeX     Download: [pdf] (787.9kB )  [ps] (7.0MB )  

• Nicholas K. Jong and Peter Stone. Compositional Models for Reinforcement Learning. In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 2009.
  Details     BibTeX     Download: [pdf] (173.0kB )  [ps] (431.7kB )  

• Tobias Jung and Peter Stone. Feature Selection for Value Function Approximation Using Bayesian Model Selection. In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 2009.
  Details     BibTeX     Download: [pdf] (746.9kB )  [ps] (2.3MB )  [slides.pdf] (957.5kB )  

• Tobias Jung, Mazda Ahmadi, and Peter Stone. Connectivity-based Localization in Robot Networks. In International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09), June 2009.
  Details     BibTeX     Download: [pdf] (176.8kB )  [ps] (514.7kB )  

• Shivaram Kalyanakrishnan and Peter Stone. An Empirical Analysis of Value Function-Based and Policy Search Reinforcement Learning. 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     BibTeX     Download: [pdf] (366.4kB )  [ps] (1.7MB )  

• Shivaram Kalyanakrishnan, Yinon Bentor, and Peter Stone. The UT Austin Villa 3D Simulation Soccer Team 2008. Technical Report AI09-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2009.
  Details     BibTeX     Download: [pdf] (292.6kB )  [ps] (983.9kB )  

• W. Bradley Knox and Peter Stone. Interactively Shaping Agents via Human Reinforcement: The TAMER Framework. In The Fifth International Conference on Knowledge Capture, September 2009.
  The TAMER project page with videos of TAMER in action.
  K-CAP 2009
  Details     BibTeX     Download: [pdf] (540.2kB )  [ps] (3.7MB )  

• W. Bradley Knox, Ian Fasel, and Peter Stone. Design Principles for Creating Human-Shapable Agents. 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     BibTeX     Download: [pdf] (400.8kB )  [ps] (2.1MB )  

• David Pardoe and Peter Stone. An Autonomous Agent for Supply Chain Management. In Gedas Adomavicius and Alok Gupta, editors, Handbooks in Information Systems Series: Business Computing, pp. 141–72, Emerald Group, 2009.
  Details     BibTeX     Download: [pdf] (392.2kB )  [ps] (736.6kB )  

• David Pardoe and Peter Stone. Adapting Price Predictions in TAC SCM. 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
  Details     BibTeX     Download: [pdf] (328.7kB )  [ps] (524.0kB )  

• Mohan Sridharan and Peter Stone. Color Learning and Illumination Invariance on Mobile Robots: A Survey. Robotics and Autonomous Systems (RAS) Journal, 57(60-7):629–44, June 2009.
  Details     BibTeX     Download: [pdf] (1.3MB )  [ps] (6.0MB )  

• Matthew E. Taylor and Peter Stone. Transfer Learning for Reinforcement Learning Domains: A Survey. Journal of Machine Learning Research, 10(1):1633–1685, 2009.
  Official version from journal website.
  Details     BibTeX     Download: [pdf] (399.8kB )  [ps] (579.4kB )  

• Mazda Ahmadi and Peter Stone. Instance-Based Action Models for Fast Action Planning. 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     BibTeX     Download: [pdf] (466.3kB )  [ps] (3.0MB )  

• Patrick Beeson, Jack O'Quin, Bartley Gillan, Tarun Nimmagadda, Mickey Ristroph, David Li, and Peter Stone. Multiagent Interactions in Urban Driving. Journal of Physical Agents, 2(1):15–30, March 2008. Special issue on Multi-Robot Systems
  JoPhA
  Details     BibTeX     Download: [pdf] (2.1MB )  [ps] (6.6MB )  

• Doran Chakraborty and Peter Stone. Online Multiagent Learning against Memory Bounded Adversaries. In Machine Learning and Knowledge Discovery in Databases, pp. 211–26, September 2008.
  Official version from Publisher's Webpage© Springer-Verlag
  Details     BibTeX     Download: [pdf] (232.4kB )  [ps] (669.2kB )  

• Kurt Dresner and Peter Stone. A Multiagent Approach to Autonomous Intersection Management. 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     BibTeX     Download: [pdf] (1.3MB )  [ps] (2.2MB )  

• Kurt Dresner and Peter Stone. Mitigating Catastrophic Failure at Intersections of Autonomous Vehicles. In AAMAS Workshop on Agents in Traffic and Transportation, pp. 78–85, Estoril, Portugal, May 2008.
  Details     BibTeX     Download: [pdf] (836.3kB )  [ps] (1.3MB )  

• Uli Grasemann, Daniel Stronger, and Peter Stone. A Neural Network-Based Approach to Robot Motion Control. 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     BibTeX     Download: [pdf] (280.9kB )  [ps] (1.6MB )  

• Todd Hester and Peter Stone. Negative Information and Line Observations for Monte Carlo Localization. In IEEE International Conference on Robotics and Automation, May 2008.
  ICRA 2008
  Details     BibTeX     Download: [pdf] (128.7kB )  [ps] (501.7kB )  

• Todd Hester, Michael Quinlan, and Peter Stone. UT Austin Villa 2008: Standing on Two Legs. Technical Report UT-AI-TR-08-8, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2008.
  Details     BibTeX     Download: [pdf] (705.9kB )  [ps] (6.2MB )  

• Nicholas K. Jong and Peter Stone. Hierarchical Model-Based Reinforcement Learning: Rmax + MAXQ. In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
  ICML 2008
  Details     BibTeX     Download: [pdf] (157.5kB )  [ps] (370.2kB )  

• Nicholas K. Jong, Todd Hester, and Peter Stone. The Utility of Temporal Abstraction in Reinforcement Learning. In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
  AAMAS-2008
  Details     BibTeX     Download: [pdf] (136.4kB )  [ps] (325.7kB )  

• Shivaram Kalyanakrishnan, Peter Stone, and Yaxin Liu. Model-based Reinforcement Learning in a Complex Domain. 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     BibTeX     Download: [pdf] (200.9kB )  [ps] (515.0kB )  

• W. Bradley Knox and Peter Stone. TAMER: Training an Agent Manually via Evaluative Reinforcement. 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     BibTeX     Download: [pdf] (1.1MB )  [ps] (12.8MB )  

• Juhyun Lee, W. Bradley Knox, and Peter Stone. Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting. 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     BibTeX     Download: [pdf] (2.4MB )  [ps] (3.4MB )  

• Joseph Reisinger, Peter Stone, and Risto Miikkulainen. Online Kernel Selection for Bayesian Reinforcement Learning. In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
  ICML 2008
  Details     BibTeX     Download: [pdf] (434.0kB )  [ps] (1.7MB )  

• Daniel Stronger and Peter Stone. Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents. International Journal on Artificial Intelligence Tools, 17(1):159–174, February 2008.
  official published version
  Details     BibTeX     Download: [pdf] (236.4kB )  [ps] (1.0MB )  

• Daniel Stronger and Peter Stone. Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot. In IEEE International Conference on Robotics and Automation, May 2008.
  ICRA 2008
  Details     BibTeX     Download: [pdf] (182.1kB )  [ps] (902.7kB )  

• Matthew E. Taylor, Nicholas K. Jong, and Peter Stone. Transferring Instances for Model-Based Reinforcement Learning. In Machine Learning and Knowledge Discovery in Databases, pp. 488–505, September 2008.
  Official version from Publisher's Webpage© Springer-Verlag
  Details     BibTeX     Download: [pdf] (304.9kB )  [ps] (860.1kB )  

• Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone. Autonomous Transfer for Reinforcement Learning. In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
  AAMAS-2008
  Details     BibTeX     Download: [pdf] (233.3kB )  [ps] (391.7kB )  

• Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone. Transfer Learning and Intelligence: an Argument and Approach. In Proceedings of the First Conference on Artificial General Intelligence, March 2008.
  AGI-2008
  Google video version of the conference presentation.
  Details     BibTeX     Download: [pdf] (149.0kB )  [ps] (202.5kB )  

• Mark VanMiddlesworth, Kurt Dresner, and Peter Stone. Replacing the Stop Sign: Unmanaged Intersection Control for Autonomous Vehicles. In AAMAS Workshop on Agents in Traffic and Transportation, pp. 94–101, Estoril, Portugal, May 2008.
  Details     BibTeX     Download: [pdf] (161.4kB )  [ps] (305.1kB )  

• Mazda Ahmadi, Matthew E. Taylor, and Peter Stone. IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks. In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
  BEST PAPER AWARD NOMINEE.
  AAMAS-2007
  Details     BibTeX     Download: [pdf] (261.6kB )  [ps] (1.0MB )  

• Bikramjit Banerjee and Peter Stone. General Game Learning using Knowledge Transfer. In The 20th International Joint Conference on Artificial Intelligence, pp. 672–677, January 2007.
  IJCAI-07
  Details     BibTeX     Download: [pdf] (118.1kB )  [ps] (198.5kB )  

• Kurt Dresner and Peter Stone. Sharing the Road: Autonomous Vehicles meet Human Drivers. In The 20th International Joint Conference on Artificial Intelligence, pp. 1263–68, January 2007.
  IJCAI-07
  Details     BibTeX     Download: [pdf] (189.9kB )  [ps] (287.7kB )  

• Kurt Dresner and Peter Stone. Learning Policy Selection for Autonomous Intersection Management. In AAMAS 2007 Workshop on Adaptive and Learning Agents, pp. 34–39, Honolulu, Hawaii, USA, May 2007.
  Details     BibTeX     Download: [pdf] (79.9kB )  [ps] (197.6kB )  

• Peggy Fidelman and Peter Stone. The Chin Pinch: A Case Study in Skill Learning on a Legged Robot. 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     BibTeX     Download: [pdf] (186.9kB )  [ps] (1.6MB )  

• Nicholas K. Jong and Peter Stone. Model-Based Function Approximation for Reinforcement Learning. In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
  Details     BibTeX     Download: [pdf] (321.1kB )  [ps] (1.0MB )  

• Nicholas K. Jong and Peter Stone. Model-Based Exploration in Continuous State Spaces. In The Seventh Symposium on Abstraction, Reformulation, and Approximation, July 2007.
  Details     BibTeX     Download: [pdf] (324.3kB )  [ps] (1.1MB )  

• Shivaram Kalyanakrishnan, Yaxin Liu, and Peter Stone. Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study. 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     BibTeX     Download: [pdf] (992.2kB )  [ps] (1.6MB )  

• Shivaram Kalyanakrishnan and Peter Stone. Batch Reinforcement Learning in a Complex Domain. 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     BibTeX     Download: [pdf] (186.4kB )  [ps] (384.8kB )  

• Shivaram Kalyanakrishnan and Peter Stone. The UT Austin Villa 3D Simulation Soccer Team 2007. 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     BibTeX     Download: [pdf] (273.4kB )  [ps] (5.7MB )  

• Gregory Kuhlmann and Peter Stone. Graph-Based Domain Mapping for Transfer Learning in General Games. In Proceedings of The Eighteenth European Conference on Machine Learning, September 2007.
  Details     BibTeX     Download: [pdf] (377.0kB )  [ps] (601.6kB )  

• Manish Saggar, Thomas D'Silva, Nate Kohl, and Peter Stone. Autonomous Learning of Stable Quadruped Locomotion. 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     BibTeX     Download: [pdf] (1.1MB )  [ps] (26.8MB )  

• Mohan Sridharan and Peter Stone. Structure Based Color Learning on a Mobile Robot under Changing Illumination. Autonomous Robots, 23(3):161–182, 2007.
  Official versionfrom the Autonomous Robots publisher's webpage.
  Details     BibTeX     Download: [pdf] (2.0MB )  [ps] (8.6MB )  

• Mohan Sridharan and Peter Stone. Planning Actions to Enable Color Learning on a Mobile Robot. International Journal of Information and Systems Sciences, 3(3):510–25, 2007.
  official published version
  Details     BibTeX     Download: (unavailable)

• Mohan Sridharan and Peter Stone. Action Selection for Illumination Invariant Color Learning. In The IEEE International Conference on Intelligent Robots and Systems (IROS), 2007.
  Details     BibTeX     Download: [pdf] (176.5kB )  [ps] (490.5kB )  

• Mohan Sridharan and Peter Stone. Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination. In The 20th International Joint Conference on Artificial Intelligence, pp. 2212–2217, January 2007.
  IJCAI-07
  Details     BibTeX     Download: [pdf] (129.5kB )  [ps] (184.9kB )  

• Peter Stone. Intelligent Autonomous Robotics: A Robot Soccer Case Study, Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan \& Claypool Publishers, 2007.
  Available from Synthesis page.
  ISBN: 9781598291262
  Details     BibTeX     Download: (unavailable)

• Peter Stone. Multiagent learning is not the answer. It is the question. 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.
  Details     BibTeX     Download: [pdf] (117.9kB )  [ps] (91.0kB )  

• Peter Stone. Learning and Multiagent Reasoning for Autonomous Agents. In The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
  IJCAI-07
  Details     BibTeX     Download: [pdf] (308.5kB )  [ps] (379.3kB )  

• Peter Stone, Patrick Beeson, Tekin Mericli, and Ryan Madigan. DARPA Urban Challenge Technical Report: Austin Robot Technology. June 2007. Available from http://www.darpa.mil/grandchallenge/rules.asp
  Details     BibTeX     Download: [pdf] (2.7MB )  

• Daniel Stronger and Peter Stone. Selective Visual Attention for Object Detection on a Legged Robot. 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     BibTeX     Download: [pdf] (159.7kB )  [ps] (342.4kB )  

• Daniel Stronger and Peter Stone. A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot. In IEEE International Conference on Robotics and Automation, pp. 3915–3920, April 2007.
  Details     BibTeX     Download: [pdf] (271.4kB )  [ps] (2.2MB )  

• Matthew E. Taylor, Peter Stone, and Yaxin Liu. Transfer Learning via Inter-Task Mappings for Temporal Difference Learning. Journal of Machine Learning Research, 8(1):2125–2167, 2007.
  Available from journal's web page.
  Details     BibTeX     Download: [pdf] (499.9kB )  [ps] (831.3kB )  

• Matthew E. Taylor, Shimon Whiteson, and Peter Stone. Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison. In Proceedings of the Twenty-Second Conference on Artificial Intelligence, pp. 1675–1678, July 2007. Nectar Track
  AAAI 2007
  Details     BibTeX     Download: [pdf] (99.7kB )  [ps] (190.4kB )  

• Matthew E. Taylor and Peter Stone. Cross-Domain Transfer for Reinforcement Learning. In Proceedings of the Twenty-Fourth International Conference on Machine Learning, June 2007.
  ICML 2007
  Details     BibTeX     Download: [pdf] (220.7kB )  [ps] (325.4kB )  

• Matthew E. Taylor, Shimon Whiteson, and Peter Stone. Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning. In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
  AAMAS-2007
  Details     BibTeX     Download: [pdf] (222.5kB )  [ps] (525.2kB )  

• Matthew E. Taylor and Peter Stone. Representation Transfer for Reinforcement Learning. 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     BibTeX     Download: [pdf] (144.9kB )  [ps] (375.1kB )  

• Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone. Accelerating Search with Transferred Heuristics. In ICAPS-07 workshop on AI Planning and Learning, September 2007.
  ICAPS 2007 workshop on AI Planning and Learning
  Details     BibTeX     Download: [pdf] (139.9kB )  [ps] (215.4kB )  

• Michael P. Wellman, Amy Greenwald, and Peter Stone. Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition, MIT Press, 2007.
  Available from Details     BibTeX     Download: (unavailable)

• Shimon Whiteson, Matthew E. Taylor, and Peter Stone. Empirical Studies in Action Selection for Reinforcement Learning. Adaptive Behavior, 15(1):33–50, March 2007.
  Details     BibTeX     Download: [pdf] (828.6kB )  [ps] (1.5MB )  

• Shimon Whiteson, Matthew E. Taylor, and Peter Stone. Adaptive Tile Coding for Value Function Approximation. Technical Report AI-TR-07-339, University of Texas at Austin, 2007.
  Details     BibTeX     Download: [pdf] (329.4kB )  [ps] (942.5kB )  

• Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin. Machine Learning for On-Line Hardware Reconfiguration. In The 20th International Joint Conference on Artificial Intelligence, pp. 1113–1118, January 2007.
  IJCAI-07
  Details     BibTeX     Download: [pdf] (98.6kB )  [ps] (191.7kB )  

• Mazda Ahmadi and Peter Stone. Keeping in Touch: Maintaining Biconnected Structure by Homogeneous Robots. 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     BibTeX     Download: [pdf] (105.0kB )  [ps] (128.8kB )  

• Mazda Ahmadi and Peter Stone. A Multi-Robot System for Continuous Area Sweeping Tasks. 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     BibTeX     Download: [pdf] (171.3kB )  [ps] (314.6kB )  

• Bikramjit Banerjee, Gregory Kuhlmann, and Peter Stone. Value Function Transfer for General Game Playing. In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.
  ICML 2006 workshop on Structural Knowledge Transfer for Machine Learning
  Details     BibTeX     Download: [pdf] (172.9kB )  [ps] (464.0kB )  

• Kurt Dresner and Peter Stone. Multiagent Traffic Management: Opportunities for Multiagent Learning. 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     BibTeX     Download: [pdf] (81.4kB )  [ps] (168.2kB )  

• Kurt Dresner and Peter Stone. Human-Usable and Emergency Vehicle-Aware Control Policies for Autonomous Intersection Management. In AAMAS 2006 Workshop on Agents in Traffic and Transportation, May 2006.
  ATT 2006.
  The project page with videos from the paper.
  Details     BibTeX     Download: [pdf] (227.5kB )  [ps] (376.8kB )  

• Gregory Kuhlmann, Kurt Dresner, and Peter Stone. Automatic Heuristic Construction in a Complete General Game Player. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1457–62, July 2006.
  AAAI 2006
  Details     BibTeX     Download: [pdf] (124.1kB )  [ps] (156.2kB )  

• Gregory Kuhlmann, William B. Knox, and Peter Stone. Know Thine Enemy: A Champion RoboCup Coach Agent. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1463–68, July 2006.
  AAAI 2006
  Details     BibTeX     Download: [pdf] (126.0kB )  [ps] (286.1kB )  

• Yaxin Liu and Peter Stone. Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 415–20, July 2006.
  AAAI 2006
  Details     BibTeX     Download: [pdf] (151.7kB )  [ps] (1.6MB )  

• David Pardoe, Peter Stone, Maytal Saar-Tsechansky, and Kerem Tomak. Adaptive Mechanism Design: A Metalearning Approach. 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     BibTeX     Download: [pdf] (334.2kB )  [ps] (511.6kB )  

• David Pardoe and Peter Stone. TacTex-2005: A Champion Supply Chain Management Agent. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1489–94, July 2006.
  AAAI 2006
  Details     BibTeX     Download: [pdf] (200.7kB )  [ps] (196.5kB )  

• David Pardoe and Peter Stone. Predictive Planning for Supply Chain Management. In Proceedings of the International Conference on Automated Planning and Scheduling, June 2006.
  ICAPS 2006
  Details     BibTeX     Download: [pdf] (366.2kB )  [ps] (950.9kB )  

• Mohan Sridharan and Peter Stone. Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data. In The Ninth International Conference on Control, Automation, Robotics and Vision, December 2006.
  ICARCV 2006
  Details     BibTeX     Download: [pdf] (444.1kB )  [ps] (2.3MB )  

• Peter Stone, Mohan Sridharan, Daniel Stronger, Gregory Kuhlmann, Nate Kohl, Peggy Fidelman, and Nicholas K. Jong. From Pixels to Multi-Robot Decision-Making: A Study in Uncertainty. 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     BibTeX     Download: [pdf] (260.5kB )  [ps] (3.6MB )  

• Peter Stone, Gregory Kuhlmann, Matthew E. Taylor, and Yaxin Liu. Keepaway Soccer: From Machine Learning Testbed to Benchmark. 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     BibTeX     Download: [pdf] (567.7kB )  [ps] (2.3MB )  

• Peter Stone, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Tekin Mericli, Mohan Sridharan, and Shao-en Yu. The UT Austin Villa 2006 RoboCup Four-Legged Team. 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     BibTeX     Download: [pdf] (123.7kB )  [ps] (127.2kB )  

• Daniel Stronger and Peter Stone. Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot. 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     BibTeX     Download: [pdf] (372.6kB )  [ps] (1.4MB )  

• Harish Subramanian, Subramanian Ramamoorthy, Peter Stone, and Benjamin Kuipers. Designing Safe, Profitable Automated Stock Trading Agents Using Evolutionary Algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference, July 2006.
  GECCO 2006
  Details     BibTeX     Download: [pdf] (214.6kB )  [ps] (813.6kB )  

• Matthew Taylor, Shimon Whiteson, and Peter Stone. Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning. In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1321–28, July 2006.
  BEST PAPER AWARD at GECCO 2006
  Details     BibTeX     Download: [pdf] (235.9kB )  [ps] (562.2kB )  

• Shimon Whiteson and Peter Stone. Evolutionary Function Approximation for Reinforcement Learning. Journal of Machine Learning Research, 7:877–917, May 2006.
  Available from journal's web page.
  Details     BibTeX     Download: [pdf] (1.7MB )  [ps] (6.1MB )  

• Shimon Whiteson and Peter Stone. Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 518–23, July 2006.
  AAAI 2006
  Details     BibTeX     Download: [pdf] (316.7kB )  [ps] (2.7MB )  

• Shimon Whiteson and Peter Stone. On-Line Evolutionary Computation for Reinforcement Learning in Stochastic Domains. In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1577–84, July 2006.
  GECCO 2006
  Details     BibTeX     Download: [pdf] (754.2kB )  [ps] (1.4MB )  

• Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin. Adapting to Workload Changes Through On-The-Fly Reconfiguration. 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     BibTeX     Download: (unavailable)

• Mazda Ahmadi and Peter Stone. Continuous Area Sweeping: A Task Definition and Initial Approach. In The 12th International Conference on Advanced Robotics, July 2005.
  Some videos of the robot referenced in the paper.
  ICAR 2005
  Details     BibTeX     Download: [pdf] (186.7kB )  [ps] (243.1kB )  

• Kurt Dresner and Peter Stone. Multiagent Traffic Management: An Improved Intersection Control Mechanism. 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     BibTeX     Download: [pdf] (143.5kB )  [ps] (216.7kB )  

• Nicholas K. Jong and Peter Stone. State Abstraction Discovery from Irrelevant State Variables. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, pp. 752–757, August 2005.
  Details     BibTeX     Download: [pdf] (102.1kB )  [ps] (249.8kB )  

• Nicholas K. Jong and Peter Stone. Bayesian Models of Nonstationary Markov Decision Problems. In IJCAI 2005 workshop on Planning and Learning in A Priori Unknown or Dynamic Domains, August 2005.
  Workshop webpage.
  Details     BibTeX     Download: [pdf] (42.4kB )  

• Gregory Kuhlmann, Peter Stone, and Justin Lallinger. The UT Austin Villa 2003 Champion Simulator Coach: A Machine Learning Approach. 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     BibTeX     Download: [pdf] (112.7kB )  [ps] (287.8kB )  

• David Pardoe and Peter Stone. Developing Adaptive Auction Mechanisms. ACM SIGecom Exchanges, 5(3):1–10, April 2005.
  SIGecom Exchanges
  Details     BibTeX     Download: [pdf] (155.6kB )  [ps] (212.4kB )  

• David Pardoe and Peter Stone. Bidding for Customer Orders in TAC SCM. 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     BibTeX     Download: [pdf] (174.3kB )  [ps] (283.8kB )  

• Alexander Sherstov and Peter Stone. Three Automated Stock-Trading Agents: A Comparative Study. 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     BibTeX     Download: [pdf] (167.0kB )  [ps] (248.6kB )  

• Alexander A. Sherstov and Peter Stone. Function Approximation via Tile Coding: Automating Parameter Choice. 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     BibTeX     Download: [pdf] (187.7kB )  [ps] (583.4kB )  [slides.pdf] (193.7kB )  

• Alexander A. Sherstov and Peter Stone. Improving Action Selection in MDP's via Knowledge Transfer. In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
  AAAI 2005
  Details     BibTeX     Download: [pdf] (205.5kB )  [ps] (774.2kB )  

• Mohan Sridharan and Peter Stone. Towards Illumination Invariance in the Legged League. 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     BibTeX     Download: [pdf] (245.1kB )  [ps] (2.1MB )  

• Mohan Sridharan and Peter Stone. Autonomous Color Learning on a Mobile Robot. In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
  Some videos of the robot referenced in the paper.
  AAAI 2005
  Details     BibTeX     Download: [pdf] (901.5kB )  [ps] (6.4MB )  

• Mohan Sridharan and Peter Stone. Real-Time Vision on a Mobile Robot Platform. 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     BibTeX     Download: [pdf] (396.1kB )  [ps] (5.0MB )  

• Mohan Sridharan, Gregory Kuhlmann, and Peter Stone. Practical Vision-Based Monte Carlo Localization on a Legged Robot. In IEEE International Conference on Robotics and Automation, April 2005.
  ICRA 2005
  Details     BibTeX     Download: [pdf] (217.6kB )  [ps] (2.0MB )  

• Peter Stone, Kurt Dresner, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger. The UT Austin Villa 2005 RoboCup Four-Legged Team. 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     BibTeX     Download: [pdf] (186.2kB )  [ps] (243.4kB )  

• Daniel Stronger and Peter Stone. A Model-Based Approach to Robot Joint Control. 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     BibTeX     Download: [pdf] (235.3kB )  [ps] (489.4kB )  

• Matthew E. Taylor, Peter Stone, and Yaxin Liu. Value Functions for RL-Based Behavior Transfer: A Comparative Study. In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
  AAAI 2005
  Details     BibTeX     Download: [pdf] (147.3kB )  [ps] (449.9kB )  

• Matthew E. Taylor and Peter Stone. Behavior Transfer for Value-Function-Based Reinforcement Learning. 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     BibTeX     Download: [pdf] (230.4kB )  [ps] (620.1kB )  

• Shimon Whiteson, Nate Kohl, Risto Miikkulainen, and Peter Stone. Evolving Keepaway Soccer Players through Task Decomposition. 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     BibTeX     Download: [pdf] (278.8kB )  [ps] (566.8kB )  

• Shimon Whiteson, Peter Stone, Kenneth O. Stanley, Risto Miikkulainen, and Nate Kohl. Automatic Feature Selection via Neuroevolution. In Proceedings of the Genetic and Evolutionary Computation Conference, June 2005.
  Details     BibTeX     Download: [pdf] (181.4kB )  [ps] (1.6MB )  

• Jonathan Wildstrom, Peter Stone, Emmett Witchel, Raymond J. Mooney, and Mike Dahlin. Towards Self-Configuring Hardware for Distributed Computer Systems. 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     BibTeX     Download: [pdf] (74.0kB )  [ps] (104.6kB )  

• Kurt Dresner and Peter Stone. Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism. 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     BibTeX     Download: [pdf] (233.8kB )  [ps] (492.0kB )  

• Yi Feng, Ronggang Yu, and Peter Stone. Two Stock-Trading Agents: Market Making and Technical Analysis. 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     BibTeX     Download: [pdf] (512.0kB )  [ps] (912.4kB )  

• Nate Kohl and Peter Stone. Machine Learning for Fast Quadrupedal Locomotion. 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     BibTeX     Download: [pdf] (210.0kB )  [ps] (1.4MB )  

• Nate Kohl and Peter Stone. Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion. 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     BibTeX     Download: [pdf] (301.5kB )  [ps] (3.2MB )  

• Gregory Kuhlmann, Peter Stone, Raymond Mooney, and Jude Shavlik. Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer. In The AAAI-2004 Workshop on Supervisory Control of Learning and Adaptive Systems, July 2004.
  Details     BibTeX     Download: [pdf] (170.3kB )  [ps] (498.2kB )  

• David Pardoe and Peter Stone. TacTex-03: A Supply Chain Management Agent. 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     BibTeX     Download: [pdf] (145.3kB )  [ps] (161.6kB )  

• Elizabeth Sklar, Simon Parsons, and Peter Stone. Using RoboCup in university-level computer science education. 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     BibTeX     Download: (unavailable)

• Peter Stone, Kurt Dresner, Peggy Fidelman, Nicholas K. Jong, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger. The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age. 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     BibTeX     Download: [pdf] (555.3kB )  [ps] (1.6MB )  

• 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. The UT Austin Villa 2003 Four-Legged Team. 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     BibTeX     Download: [pdf] (201.5kB )  [ps] (170.3kB )  

• Shimon Whiteson and Peter Stone. Adaptive Job Routing and Scheduling. 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     BibTeX     Download: [pdf] (664.7kB )  [ps] (1.1MB )  

AFOSR

• Josiah Hanna and Peter Stone. Reducing Sampling Error in Policy Gradient Learning. 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 )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Imitation Learning from Video by Leveraging Proprioception. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (1.1MB )  [slides.pptx] (20.3MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Recent Advances in Imitation Learning from Observation. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (157.4kB )  [slides.pptx] (45.5MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Generative Adversarial Imitation from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (1.0MB )  

• Faraz Torabi, Sean Geiger, Garrett Warnell, and Peter Stone. Sample-efficient Adversarial Imitation Learning from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (6.1MB )  

• Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, and Peter Stone. Leveraging Human Guidance for Deep Reinforcement Learning Tasks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (471.1kB )  [slides.pdf] (1.2MB )  

• Decebal Constantin Mocanu, Elena Mocanu, Peter Stone, Phuong H. Nguyen, Madeleine Gibescu, and Antonio Liotta. Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science. Nature Communications, 9(2383), June 2018.
  Official version from Publisher's Webpage.
  Details     BibTeX     Download: [pdf] (1.5MB )  

• Tarun Rambha, Stephen D. Boyles, Avinash Unnikrishnan, and Peter Stone. Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty. Transportation Research Part B: Methodological, 110:104–21, 2018.
  Official version from Publisher's Webpage
  Details     BibTeX     Download: [pdf] (1.6MB )  

• Michael Albert, Vincent Conitzer, and Peter Stone. Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), May 2017.
  Details     BibTeX     Download: [pdf] (348.6kB )  [slides.pdf] (2.8MB )  

• Michael Albert, Vincent Conitzer, and Peter Stone. Automated Design of Robust Mechanisms. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), Feb 2017.
  Details     BibTeX     Download: [pdf] (366.4kB )  [slides.pdf] (2.7MB )  

• Stefano Albrecht, Somchaya Liemhetcharat, and Peter Stone. Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial. Autonomous Agents and Multi-Agent Systems, 31(4):765–66, July 2017.
  Official version from Publisher's Webpage
  Details     BibTeX     Download: [pdf] (304.3kB )  

• Stefano Albrecht and Peter Stone. Reasoning about Hypothetical Agent Behaviours and their Parameters. 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 )  

• Katie Genter, Tim Laue, and Peter Stone. Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale Ad Hoc Teamwork Robotics Competition. 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 )  

• Santiago Gonzalez, Vijay Chidambaram, Jivko Sinapov, and Peter Stone. CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression. In Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '17), July 2017.
  Details     BibTeX     Download: [pdf] (241.6kB )  

• Josiah Hanna, Philip Thomas, Peter Stone, and Scott Niekum. Data-Efficient Policy Evaluation Through Behavior Policy Search. In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
  Details     BibTeX     Download: [pdf] (1.2MB )  [slides.pdf] (1.1MB )  

• Josiah Hanna, Peter Stone, and Scott Niekum. Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. 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 )  

• Josiah Hanna and Peter Stone. Grounded Action Transformation for Robot Learning in Simulation. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
  Details     BibTeX     Download: [pdf] (1.3MB )  [slides.pdf] (1.3MB )  

• Matthew Hausknecht, Wen-Ke Li, Michael Mauk, and Peter Stone. Machine Learning Capabilities of a Simulated Cerebellum. "IEEE Transactions on Neural Networks and Learning Systems", 28(3):510–22, March 2017.
  Details     BibTeX     Download: [pdf] (1.1MB )  

• 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. BWIBots: A platform for bridging the gap between AI and human--robot interaction research. The International Journal of Robotics Research, 36(5--7):635–59, 2017.
  Accompanying videos at https://youtu.be/2UJG4-ejVww
  Details     BibTeX     Download: [pdf] (4.4MB )  

• Piyush Khandelwal and Peter Stone. Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.
  Details     BibTeX     Download: [pdf] (1.8MB )  

• Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, and Peter Stone. Designing Better Playlists with Monte Carlo Tree Search. In Proceedings of the Twenty-Ninth Conference On Innovative Applications Of Artificial Intelligence (IAAI-17), February 2017.
  Details     BibTeX     Download: [pdf] (377.0kB )  

• Patrick MacAlpine and Peter Stone. Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges. 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     BibTeX     Download: [pdf] (518.7kB )  [ps] (2.6MB )  [slides.pdf] (45.5MB )  

• Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, and Peter Stone. Fast and Precise Black and White Ball Detection for RoboCup Soccer. In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
  Details     BibTeX     Download: [pdf] (254.2kB )  [ps] (716.1kB )  [slides.pdf] (1.5MB )  

• Sanmit Narvekar, Jivko Sinapov, and Peter Stone. Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August 2017.
  Details     BibTeX     Download: [pdf] (826.2kB )  [slides.pdf] (5.8MB )  

• Guni Sharon, Michael W. Levin, Josiah P. Hanna, Tarun Rambha, Stephen D. Boyles, and Peter Stone. Network-wide Adaptive Tolling for Connected and Automated vehicles. 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: [pdf] (2.8MB )  [ps] (4.2MB )  

• Guni Sharon and Peter Stone. A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections. 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 )  

• Maxwell Svetlik, Matteo Leonetti, Jivko Sinapov, Rishi Shah, Nick Walker, and Peter Stone. Automatic Curriculum Graph Generation for Reinforcement Learning Agents. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
  Details     BibTeX     Download: [pdf] (2.0MB )  

• Shiqi Zhang, Yuqian Jiang, Guni Sharon, and Peter Stone. Multirobot Symbolic Planning under Temporal Uncertainty. 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 )  

• Shiqi Zhang, Piyush Khandelwal, and Peter Stone. Dynamically Constructed (PO)MDPs for Adaptive Robot Planning. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
  Details     BibTeX     Download: [pdf] (3.2MB )  

• Samuel Barrett, Avi Rosenfeld, Sarit Kraus, and Peter Stone. Making Friends on the Fly: Cooperating with New Teammates. Artificial Intelligence, October 2016.
  Official version from journal website.
  Details     BibTeX     Download: [pdf] (917.9kB )  

• Ginevra Gaudioso, Matteo Leonetti, and Peter Stone. State Aggregation through Reasoning in Answer Set Programming. In Proceedings of the IJCAI Workshop on Autonomous Mobile Service Robots (WSR 16), July 2016.
  Details     BibTeX     Download: [pdf] (776.6kB )  

• Katie Genter and Peter Stone. Ad Hoc Teamwork Behaviors for Influencing a Flock. Acta Polytechnica, 56(1), 2016.
  Details     BibTeX     Download: [pdf] (421.5kB )  [ps] (1.6MB )  

• Katie Genter and Peter Stone. Adding Influencing Agents to a Flock. 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 )  

• Jonathan Grizou, Samuel Barrett, Manuel Lopes, and Peter Stone. Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (339.0kB )  

• Josiah P. Hanna, Michael Albert, Donna Chen, and Peter Stone. Minimum Cost Matching for Autonomous Carsharing. 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 )  

• Matthew Hausknecht and Peter Stone. Deep Reinforcement Learning in Parameterized Action Space. In Proceedings of the International Conference on Learning Representations (ICLR), May 2016.
  Details     BibTeX     Download: [pdf] (468.3kB )  

• Matthew Hausknecht and Peter Stone. Grounded Semantic Networks for Learning Shared Communication Protocols. In Deep Reinforcement Learning, NIPS Workshop, December 2016.
  Details     BibTeX     Download: [pdf] (899.9kB )  

• Matthew Hausknecht and Peter Stone. On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning. In Deep Reinforcement Learning: Frontiers and Challenges, IJCAI Workshop, July 2016.
  Details     BibTeX     Download: [pdf] (2.5MB )  

• Matthew Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan, and Peter Stone. Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (253.9kB )  

• Matthew Hausknecht, Yilun Chen, and Peter Stone. Deep Imitation Learning for Parameterized Action Spaces. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (483.4kB )  

• Piyush Khandelwal, Elad Liebman, Scott Niekum, and Peter Stone. On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search. In Proceedings of The 33rd International Conference on Machine Learning, pp. 1319–1328, June 2016.
  Details     BibTeX     Download: [pdf] (1.3MB )  [slides.pdf] (1.7MB )  

• Matteo Leonetti, Luca Iocchi, and Peter Stone. A synthesis of automated planning and reinforcement learning for efficient, robust decision-making. Artificial Intelligence, 241:103 – 130, September 2016.
  Details     BibTeX     Download: [pdf] (3.2MB )  

• Elad Liebman, Peter Stone, and Corey N. White. Impact of Music on Decision Making in Quantitative Tasks. In 17th International Society for Music Information retrieval Conference (ISMIR), August 2016.
  Details     BibTeX     Download: [pdf] (591.1kB )  [slides.pdf] (678.6kB )  

• Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, and Peter Stone. Source Task Creation for Curriculum Learning. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
  Details     BibTeX     Download: [pdf] (630.0kB )  [slides.pdf] (10.2MB )  

• Jivko Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone. Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
  Details     BibTeX     Download: [pdf] (6.6MB )  [slides.pdf] (5.2MB )  

• Jesse Thomason, Jivko Sinapov, Maxwell Svetlik, Peter Stone, and Raymond Mooney. Learning Multi-Modal Grounded Linguistic Semantics by Playing I Spy. In Proceedings of the 25th international joint conference on Artificial Intelligence (IJCAI), July 2016.
  Demo Video
  Details     BibTeX     Download: [pdf] (3.1MB )  [slides.pdf] (1.0MB )  

• Daniel Urieli and Peter Stone. An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
  Details     BibTeX     Download: [pdf] (11.9MB )  

• Daniel Urieli and Peter Stone. Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market. In Proceedings of the 30th Conference on Artificial Intelligence (AAAI 2016), February 2016.
  Details     BibTeX     Download: [pdf] (1.2MB )  

• Fei Fang, Peter Stone, and Milind Tambe. When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing. 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     BibTeX     Download: [pdf] (456.7kB )  [ps] (983.9kB )  [slides.pptx] (6.2MB )  

• Katie Genter, Shun Zhang, and Peter Stone. Determining Placements of Influencing Agents in a Flock. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
  Details     BibTeX     Download: [pdf] (426.7kB )  [ps] (1.4MB )  [slides.pdf] (1.6MB )  

• Matthew Hausknecht and Peter Stone. The Impact of Determinism on Learning Atari 2600 Games. In AAAI Workshop on Learning for General Competency in Video Games, January 2015.
  Details     BibTeX     Download: [pdf] (65.1kB )  

• Matthew Hausknecht and Peter Stone. Deep Recurrent Q-Learning for Partially Observable MDPs. In AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents (AAAI-SDMIA15), November 2015.
  Details     BibTeX     Download: [pdf] (1.5MB )  [slides.pdf] (3.8MB )  

• Elad Liebman, Benny Chor, and Peter Stone. Representative Selection in Nonmetric Datasets. "Applied Artificial Intelligence", 29:807–838, 2015.
  Details     BibTeX     Download: [pdf] (846.3kB )  

• Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone. DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
  Details     BibTeX     Download: [pdf] (1.5MB )  [ps] (38.4MB )  [slides.pdf] (2.6MB )  

• Jacob Menashe and Peter Stone. Monte Carlo Hierarchical Model Learning. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
  Details     BibTeX     Download: [pdf] (693.2kB )  [ps] (18.4MB )  

• Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, and Peter Stone. Learning Inter-Task Transferability in the Absence of Target Task Samples. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2015.
  Details     BibTeX     Download: [pdf] (337.2kB )  

• Katie Genter and Peter Stone. Influencing a Flock via Ad Hoc Teamwork. In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
  Details     BibTeX     Download: [pdf] (358.4kB )  [ps] (1.4MB )  [slides.pdf] (15.3MB )  

• Katie Genter, Noa Agmon, and Peter Stone. Role-Based Ad Hoc Teamwork. 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     BibTeX     Download: [pdf] (1.5MB )  [ps] (1.6MB )  

AFRL

• Faraz Torabi, Garrett Warnell, and Peter Stone. Imitation Learning from Video by Leveraging Proprioception. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (1.1MB )  [slides.pptx] (20.3MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Recent Advances in Imitation Learning from Observation. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (157.4kB )  [slides.pptx] (45.5MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Generative Adversarial Imitation from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (1.0MB )  

• Faraz Torabi, Sean Geiger, Garrett Warnell, and Peter Stone. Sample-efficient Adversarial Imitation Learning from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (6.1MB )  

• Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, and Peter Stone. Leveraging Human Guidance for Deep Reinforcement Learning Tasks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (471.1kB )  [slides.pdf] (1.2MB )  

• Stefano Albrecht, Somchaya Liemhetcharat, and Peter Stone. Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial. Autonomous Agents and Multi-Agent Systems, 31(4):765–66, July 2017.
  Official version from Publisher's Webpage
  Details     BibTeX     Download: [pdf] (304.3kB )  

• Katie Genter, Tim Laue, and Peter Stone. Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale Ad Hoc Teamwork Robotics Competition. 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 )  

• Katie Genter and Peter Stone. Ad Hoc Teamwork Behaviors for Influencing a Flock. Acta Polytechnica, 56(1), 2016.
  Details     BibTeX     Download: [pdf] (421.5kB )  [ps] (1.6MB )  

• Katie Genter and Peter Stone. Adding Influencing Agents to a Flock. 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 )  

• Jonathan Grizou, Samuel Barrett, Manuel Lopes, and Peter Stone. Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (339.0kB )  

• Josiah P. Hanna, Michael Albert, Donna Chen, and Peter Stone. Minimum Cost Matching for Autonomous Carsharing. 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 )  

• Matthew Hausknecht and Peter Stone. Deep Reinforcement Learning in Parameterized Action Space. In Proceedings of the International Conference on Learning Representations (ICLR), May 2016.
  Details     BibTeX     Download: [pdf] (468.3kB )  

• Matthew Hausknecht and Peter Stone. Grounded Semantic Networks for Learning Shared Communication Protocols. In Deep Reinforcement Learning, NIPS Workshop, December 2016.
  Details     BibTeX     Download: [pdf] (899.9kB )  

• Matthew Hausknecht and Peter Stone. On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning. In Deep Reinforcement Learning: Frontiers and Challenges, IJCAI Workshop, July 2016.
  Details     BibTeX     Download: [pdf] (2.5MB )  

• Matthew Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan, and Peter Stone. Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (253.9kB )  

• Matthew Hausknecht, Yilun Chen, and Peter Stone. Deep Imitation Learning for Parameterized Action Spaces. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (483.4kB )  

• Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, and Peter Stone. Source Task Creation for Curriculum Learning. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
  Details     BibTeX     Download: [pdf] (630.0kB )  [slides.pdf] (10.2MB )  

• Daniel Urieli and Peter Stone. An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
  Details     BibTeX     Download: [pdf] (11.9MB )  

• Daniel Urieli and Peter Stone. Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market. In Proceedings of the 30th Conference on Artificial Intelligence (AAAI 2016), February 2016.
  Details     BibTeX     Download: [pdf] (1.2MB )  

• Fei Fang, Peter Stone, and Milind Tambe. When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing. 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     BibTeX     Download: [pdf] (456.7kB )  [ps] (983.9kB )  [slides.pptx] (6.2MB )  

• Katie Genter, Shun Zhang, and Peter Stone. Determining Placements of Influencing Agents in a Flock. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
  Details     BibTeX     Download: [pdf] (426.7kB )  [ps] (1.4MB )  [slides.pdf] (1.6MB )  

• Matthew Hausknecht and Peter Stone. The Impact of Determinism on Learning Atari 2600 Games. In AAAI Workshop on Learning for General Competency in Video Games, January 2015.
  Details     BibTeX     Download: [pdf] (65.1kB )  

• Matthew Hausknecht and Peter Stone. Deep Recurrent Q-Learning for Partially Observable MDPs. In AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents (AAAI-SDMIA15), November 2015.
  Details     BibTeX     Download: [pdf] (1.5MB )  [slides.pdf] (3.8MB )  

• Elad Liebman, Peter Stone, and Corey N. White. How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification. In 16th International Society for Music Information retrieval Conference (ISMIR), October 2015.
  Details     BibTeX     Download: [pdf] (832.6kB )  [ps] (6.3MB )  [slides.pdf] (2.0MB )  

• Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone. DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
  Details     BibTeX     Download: [pdf] (1.5MB )  [ps] (38.4MB )  [slides.pdf] (2.6MB )  

• Jacob Menashe and Peter Stone. Monte Carlo Hierarchical Model Learning. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
  Details     BibTeX     Download: [pdf] (693.2kB )  [ps] (18.4MB )  

• Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, and Peter Stone. Learning Inter-Task Transferability in the Absence of Target Task Samples. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2015.
  Details     BibTeX     Download: [pdf] (337.2kB )  

• Katie Genter and Peter Stone. Influencing a Flock via Ad Hoc Teamwork. In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
  Details     BibTeX     Download: [pdf] (358.4kB )  [ps] (1.4MB )  [slides.pdf] (15.3MB )  

• Katie Genter, Noa Agmon, and Peter Stone. Role-Based Ad Hoc Teamwork. 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     BibTeX     Download: [pdf] (1.5MB )  [ps] (1.6MB )  

ARL

• Yunshu Du, Garrett Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew E. Taylor. Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy. Neural Computing and Applications, May 2021.
  Details     BibTeX     Download: [pdf] (2.2MB )  

• Josiah P. Hanna, Scott Niekum, and Peter Stone. Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy. Machine Learning (MLJ), 110:1267–1317, May 2021.
  Details     BibTeX     Download: [pdf] (3.7MB )  

• Eddy Hudson, Garrett Warnell, and Peter Stone. RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning. 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 )  

• Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone. Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
  Details     BibTeX     Download: [pdf] (1.8MB )  [slides.pdf] (1.8MB )  

• Alec Koppel, Garrett Warnell, Ethan Stump, Peter Stone, and Alejandro Ribeiro. Policy Evaluation in Continuous MDPs with Efficient Kernelized Gradient Temporal Difference. IEEE Transactions on Automatic Control, 66(4):1856–63, April 2021.
  official online version
  Details     BibTeX     Download: [pdf] (648.8kB )  

• Guni Sharon, James Ault, Peter Stone, Varun Kompella, and Roberto Capobianco. Multiagent Epidemiologic Inference through Realtime Contact Tracing. In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2021), May 2021.
  Details     BibTeX     Download: [pdf] (1014.3kB )  

• Zizhao Wang, Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone. APPLI: Adaptive Planner Parameter Learning From Interventions. In Proceedings of the International Conference on Robotics and Automation (ICRA 2021), May 2021.
  Video presentation
  Details     BibTeX     Download: [pdf] (4.2MB )  

• Xuesu Xiao, Joydeep Biswas, and Peter Stone. Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain. IEEE Robotics and Automation Letters, July 2021.
  Contains material that was previously presented in an ICRA21 workshop paper Video
  Details     BibTeX     Download: [pdf] (3.2MB )  [slides.pdf] (23.2MB )  

• Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone. Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination. IEEE Robotics and Automation Letters, January 2021.
  5-minute video demonstration
  Project webpage
  Details     BibTeX     Download: [pdf] (3.2MB )  

• Xuesu Xiao, Bo Liu, and Peter Stone. Agile Robot Navigation through Hallucinated Learning and Sober Deployment. In Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), June 2021.
  Video
  Details     BibTeX     Download: [pdf] (3.1MB )  

• Xuesu Xiao, Joydeep Biswas, and Peter Stone. Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain. In Opportunities and Challenges with Autonomous Racing Workshop at the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), June 2021.
  Video
  Details     BibTeX     Download: [pdf] (9.7MB )  [slides.pdf] (23.2MB )  

• Siddarth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, and Peter Stone. An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch. In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020), December 2020.
  Poster
  Details     BibTeX     Download: [pdf] (1.3MB )  

• Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, and Peter Stone. Stochastic Grounded Action Transformation for Robot Learning in Simulation. In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
  11-minute video presentation.
  Details     BibTeX     Download: [pdf] (1.9MB )  

• Ishan Durugkar, Elad Liebman, and Peter Stone. Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July 2020.
  15-minute presentation
  Details     BibTeX     Download: [pdf] (3.9MB )  

• Justin Hart, Reuth Mirsky, Xuesu Xiao, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter Stone. Using Human-Inspired Signals to Disambiguate Navigational Intentions. In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
  Video presentation
  Details     BibTeX     Download: [pdf] (3.2MB )  

• Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, and Peter Stone. Reinforced Grounded Action Transformation for Sim-to-Real Transfer. In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
  14-minute video presentation.
  Details     BibTeX     Download: [pdf] (506.6kB )  

• Shih-Yun Lo, Shiqi Zhang, and Peter Stone. The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation. 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 )  

• Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, and Peter Stone. Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. Journal of Machine Learning Research, 21(181):1–50, 2020.
  Details     BibTeX     Download: [pdf] (1.4MB )  

• Sanmit Narvekar and Peter Stone. Generalizing Curricula for Reinforcement Learning. 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 )  

• Brahma Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, and Peter Stone. RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration. IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS), 5:6262–69, October 2020.
  Video of the experiments; 13-minute video presentation.
  Details     BibTeX     Download: [pdf] (405.1kB )  [slides.pptx] (115.4MB )  

• Brahma Pavse, Ishan Durugkar, Josiah Hanna, and Peter Stone. Reducing Sampling Error in Batch Temporal Difference Learning. 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 )  

• Brahma S. Pavse, Josiah P. Hanna, Ishan Durugkar, and Peter Stone. On Sampling Error in Batch Action-Value Prediction Algorithms. In In the Offline Reinforcement Learning Workshop at Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
  5-mins Video Presentation
  Details     BibTeX     Download: [pdf] (327.2kB )  

• Daniel Perille, Abigail Truong, Xuesu Xiao, and Peter Stone. Benchmarking Metric Ground Navigation. In Proceedings of the 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2016), November 2020.
  Video presentation
  Details     BibTeX     Download: [pdf] (2.1MB )  

• Rishi Shah, Yuqian Jiang, Justin Hart, and Peter Stone. Deep R-Learning for Continual Area Sweeping. 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 )  

• Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, and Peter Stone. APPLD: Adaptive Planner Parameter Learning from Demonstration. IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS), June 2020.
  5-minute Video presentation; 15-minute Video presentation
  Project webpage
  Details     BibTeX     Download: [pdf] (2.2MB )  [slides.pdf] (21.1MB )  

• Manish Ravula, Shani Alkobi and Peter Stone. Ad hoc Teamwork with Behavior Switching Agents. In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (350.4kB )  

• Josiah Hanna, Scott Niekum, and Peter Stone. Importance Sampling Policy Evaluation with an Estimated Behavior Policy. In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
  Details     BibTeX     Download: [pdf] (2.7MB )  [slides.pdf] (4.0MB )  

• Yuqian Jiang, Fangkai Yang, Shiqi Zhang, and Peter Stone. Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
  Details     BibTeX     Download: [pdf] (925.2kB )  

• Yuqian Jiang, Nick Walker, Justin Hart, and Peter Stone. Open-World Reasoning for Service Robots. In Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
  Accompanying video
  Details     BibTeX     Download: [pdf] (813.5kB )  

• Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone Peter Stone. The right music at the right time: adaptive personalized playlists based on sequence modeling. 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 )  

• Rishi Shah, Yuqian Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta, Rachel Schlossman, Marika Murphy, Justin Hart, Luis Sentis, and Peter Stone. Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report. 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: [pdf] (4.5MB )  

• Felipe Leno Da Silva, Garrett Warnell, Anna Helena Reali Costa, and Peter Stone. Agents teaching agents: a survey on inter-agent transfer learning. Autonomous Agents and Multi-Agent Systems, Dec 2019.
  Official version from JAAMAS
  Details     BibTeX     Download: [pdf] (572.4kB )  

• Felipe Leno Da Silva, Anna Helena Reali Costa, and Peter Stone. Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games. In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
  Details     BibTeX     Download: [pdf] (1.6MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Imitation Learning from Video by Leveraging Proprioception. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (1.1MB )  [slides.pptx] (20.3MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Recent Advances in Imitation Learning from Observation. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (157.4kB )  [slides.pptx] (45.5MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Generative Adversarial Imitation from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (1.0MB )  

• Faraz Torabi, Sean Geiger, Garrett Warnell, and Peter Stone. Sample-efficient Adversarial Imitation Learning from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (6.1MB )  

• Nick Walker, Yuqian Jiang, Maya Cakmak, and Peter Stone. Desiderata for Planning Systems in General-Purpose Service Robots. In Proceedings of the ICAPS Workshop on Planning and Robotics (PlanRob 2019), July 2019.
  Details     BibTeX     Download: [pdf] (651.5kB )  

• Harel Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter Stone, and Raymond Mooney. Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance. In International Conference on Social Robotics (ICSR), pp. 133–143, November 2019.
  Details     BibTeX     Download: [pdf] (958.6kB )  

• Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, and Peter Stone. Leveraging Human Guidance for Deep Reinforcement Learning Tasks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (471.1kB )  [slides.pdf] (1.2MB )  

FLI

• Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, and Peter Stone. Scalable Multiagent Driving Policies For Reducing Traffic Congestion. In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2021.
  Details     BibTeX     Download: [pdf] (1.0MB )  [slides.pptx] (1.5MB )  

• Yunshu Du, Garrett Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew E. Taylor. Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy. Neural Computing and Applications, May 2021.
  Details     BibTeX     Download: [pdf] (2.2MB )  

• Josiah P. Hanna, Scott Niekum, and Peter Stone. Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy. Machine Learning (MLJ), 110:1267–1317, May 2021.
  Details     BibTeX     Download: [pdf] (3.7MB )  

• Eddy Hudson, Garrett Warnell, and Peter Stone. RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning. 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 )  

• Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone. Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
  Details     BibTeX     Download: [pdf] (1.8MB )  [slides.pdf] (1.8MB )  

• W Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, and Peter Stone. Reward (Mis)design for Autonomous Driving. arXiv preprint arXiv:2104.13906, 2021.
  Paper webpage
  Details     BibTeX     Download: [pdf] (1.2MB )  

• Bo Liu, Xuesu Xiao, and Peter Stone. Team Orienteering Coverage Planning with Uncertain Reward. In International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
  Details     BibTeX     Download: [pdf] (3.9MB )  

• Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, and Animashree Anandkumar. Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition. 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 )  

• Bo Liu, Xuesu Xiao, and Peter Stone. A Lifelong Learning Approach to Mobile Robot Navigation. In IEEE International Conference on Robotics and Automation (ICRA), 2021, June 2021.
  Video presentation
  Details     BibTeX     Download: [pdf] (3.6MB )  

• Guni Sharon, James Ault, Peter Stone, Varun Kompella, and Roberto Capobianco. Multiagent Epidemiologic Inference through Realtime Contact Tracing. In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2021), May 2021.
  Details     BibTeX     Download: [pdf] (1014.3kB )  

• Jennifer Suriadinata, William Macke, Reuth Mirsky, and Peter Stone. Reasoning about Human Behavior in Ad Hoc Teamwork. In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
  Video Presentation
  Details     BibTeX     Download: [pdf] (926.2kB )  

• Zifan Xu, Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Bo Liu, Zizhao Wang, and Peter Stone. APPLR: Adaptive Planner Parameter Learning from Reinforcement. 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 )  

• Harel Yedidsion, Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter Stone. A Scavenger Hunt for Service Robots. In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
  Video presentation
  Details     BibTeX     Download: [pdf] (1.5MB )  

• Harel Yedidsion, Shani Alkoby, and Peter Stone. Sequential Online Chore Division for Autonomous Vehicle Convoy Formation. Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
  arXiv
  Details     BibTeX     Download: [pdf] (478.9kB )  

• Siddarth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, and Peter Stone. An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch. In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020), December 2020.
  Poster
  Details     BibTeX     Download: [pdf] (1.3MB )  

• Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, and Peter Stone. Stochastic Grounded Action Transformation for Robot Learning in Simulation. In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
  11-minute video presentation.
  Details     BibTeX     Download: [pdf] (1.9MB )  

• Ishan Durugkar, Elad Liebman, and Peter Stone. Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July 2020.
  15-minute presentation
  Details     BibTeX     Download: [pdf] (3.9MB )  

• Justin Hart, Reuth Mirsky, Xuesu Xiao, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter Stone. Using Human-Inspired Signals to Disambiguate Navigational Intentions. In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
  Video presentation
  Details     BibTeX     Download: [pdf] (3.2MB )  

• Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, and Peter Stone. Reinforced Grounded Action Transformation for Sim-to-Real Transfer. In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
  14-minute video presentation.
  Details     BibTeX     Download: [pdf] (506.6kB )  

• Shih-Yun Lo, Shiqi Zhang, and Peter Stone. The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation. 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 )  

• Keting Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen. Learning and Reasoning for Robot Dialog and Navigation Tasks. 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 )  

• Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, and Peter Stone. Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. Journal of Machine Learning Research, 21(181):1–50, 2020.
  Details     BibTeX     Download: [pdf] (1.4MB )  

• Sanmit Narvekar and Peter Stone. Generalizing Curricula for Reinforcement Learning. 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 )  

• Jin-Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone. Learning to Improve Multi-Robot Hallway Navigation. In Proceedings of the 4th Conference on Robot Learning (CoRL), November 2020.
  Video presentation
  Details     BibTeX     Download: [pdf] (1.3MB )  

• Brahma Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, and Peter Stone. RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration. IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS), 5:6262–69, October 2020.
  Video of the experiments; 13-minute video presentation.
  Details     BibTeX     Download: [pdf] (405.1kB )  [slides.pptx] (115.4MB )  

• Brahma Pavse, Ishan Durugkar, Josiah Hanna, and Peter Stone. Reducing Sampling Error in Batch Temporal Difference Learning. 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 )  

• Brahma S. Pavse, Josiah P. Hanna, Ishan Durugkar, and Peter Stone. On Sampling Error in Batch Action-Value Prediction Algorithms. In In the Offline Reinforcement Learning Workshop at Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
  5-mins Video Presentation
  Details     BibTeX     Download: [pdf] (327.2kB )  

• Rishi Shah, Yuqian Jiang, Justin Hart, and Peter Stone. Deep R-Learning for Continual Area Sweeping. 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 )  

• Lemeng Wu, Bo Liu, Peter Stone, and Qiang Liu. Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks. In Advances in Neural Information Processing Systems 34 (2020), December 2020.
  Details     BibTeX     Download: [pdf] (8.1MB )  [slides.pdf] (744.8kB )  

• Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, and Peter Stone. APPLD: Adaptive Planner Parameter Learning from Demonstration. IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS), June 2020.
  5-minute Video presentation; 15-minute Video presentation
  Project webpage
  Details     BibTeX     Download: [pdf] (2.2MB )  [slides.pdf] (21.1MB )  

• Manish Ravula, Shani Alkobi and Peter Stone. Ad hoc Teamwork with Behavior Switching Agents. In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (350.4kB )  

• Josiah Hanna, Scott Niekum, and Peter Stone. Importance Sampling Policy Evaluation with an Estimated Behavior Policy. In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
  Details     BibTeX     Download: [pdf] (2.7MB )  [slides.pdf] (4.0MB )  

• Yuqian Jiang, Shiqi Zhang, Piyush Khandelwal, and Peter Stone. Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems. 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 )  

• Yuqian Jiang, Harel Yedidsion, Shiqi Zhang, Guni Sharon, and Peter Stone. Multi-Robot Planning with Conflicts and Synergies. Autonomous Robots, Springer, March 2019.
  Official version from Publisher's Webpage
  Details     BibTeX     Download: [pdf] (2.0MB )  

• Yuqian Jiang, Fangkai Yang, Shiqi Zhang, and Peter Stone. Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
  Details     BibTeX     Download: [pdf] (925.2kB )  

• Yuqian Jiang, Nick Walker, Justin Hart, and Peter Stone. Open-World Reasoning for Service Robots. In Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
  Accompanying video
  Details     BibTeX     Download: [pdf] (813.5kB )  

• Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone Peter Stone. The right music at the right time: adaptive personalized playlists based on sequence modeling. 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 )  

• Rishi Shah, Yuqian Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta, Rachel Schlossman, Marika Murphy, Justin Hart, Luis Sentis, and Peter Stone. Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report. 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: [pdf] (4.5MB )  

• Felipe Leno Da Silva, Garrett Warnell, Anna Helena Reali Costa, and Peter Stone. Agents teaching agents: a survey on inter-agent transfer learning. Autonomous Agents and Multi-Agent Systems, Dec 2019.
  Official version from JAAMAS
  Details     BibTeX     Download: [pdf] (572.4kB )  

• Felipe Leno Da Silva, Anna Helena Reali Costa, and Peter Stone. Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games. In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
  Details     BibTeX     Download: [pdf] (1.6MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Imitation Learning from Video by Leveraging Proprioception. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (1.1MB )  [slides.pptx] (20.3MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Recent Advances in Imitation Learning from Observation. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (157.4kB )  [slides.pptx] (45.5MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Generative Adversarial Imitation from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (1.0MB )  

• Faraz Torabi, Sean Geiger, Garrett Warnell, and Peter Stone. Sample-efficient Adversarial Imitation Learning from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
  Details     BibTeX     Download: [pdf] (6.1MB )  

• Nick Walker, Yuqian Jiang, Maya Cakmak, and Peter Stone. Desiderata for Planning Systems in General-Purpose Service Robots. In Proceedings of the ICAPS Workshop on Planning and Robotics (PlanRob 2019), July 2019.
  Details     BibTeX     Download: [pdf] (651.5kB )  

• Harel Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter Stone, and Raymond Mooney. Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance. In International Conference on Social Robotics (ICSR), pp. 133–143, November 2019.
  Details     BibTeX     Download: [pdf] (958.6kB )  

• Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, and Peter Stone. Leveraging Human Guidance for Deep Reinforcement Learning Tasks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (471.1kB )  [slides.pdf] (1.2MB )  

ONR

• Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, and Peter Stone. Scalable Multiagent Driving Policies For Reducing Traffic Congestion. In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2021.
  Details     BibTeX     Download: [pdf] (1.0MB )  [slides.pptx] (1.5MB )  

• Yunshu Du, Garrett Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew E. Taylor. Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy. Neural Computing and Applications, May 2021.
  Details     BibTeX     Download: [pdf] (2.2MB )  

• Josiah P. Hanna, Scott Niekum, and Peter Stone. Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy. Machine Learning (MLJ), 110:1267–1317, May 2021.
  Details     BibTeX     Download: [pdf] (3.7MB )  

• Eddy Hudson, Garrett Warnell, and Peter Stone. RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning. 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 )  

• Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone. Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.
  Details     BibTeX     Download: [pdf] (1.8MB )  [slides.pdf] (1.8MB )  

• Bo Liu, Xuesu Xiao, and Peter Stone. Team Orienteering Coverage Planning with Uncertain Reward. In International Conference on Intelligent Robots and Systems (IROS), 2021, September 2021.
  Details     BibTeX     Download: [pdf] (3.9MB )  

• Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, and Animashree Anandkumar. Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition. 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 )  

• Bo Liu, Xuesu Xiao, and Peter Stone. A Lifelong Learning Approach to Mobile Robot Navigation. In IEEE International Conference on Robotics and Automation (ICRA), 2021, June 2021.
  Video presentation
  Details     BibTeX     Download: [pdf] (3.6MB )  

• Guni Sharon, James Ault, Peter Stone, Varun Kompella, and Roberto Capobianco. Multiagent Epidemiologic Inference through Realtime Contact Tracing. In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2021), May 2021.
  Details     BibTeX     Download: [pdf] (1014.3kB )  

• Jennifer Suriadinata, William Macke, Reuth Mirsky, and Peter Stone. Reasoning about Human Behavior in Ad Hoc Teamwork. In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
  Video Presentation
  Details     BibTeX     Download: [pdf] (926.2kB )  

• Zifan Xu, Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Bo Liu, Zizhao Wang, and Peter Stone. APPLR: Adaptive Planner Parameter Learning from Reinforcement. 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 )  

• Harel Yedidsion, Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter Stone. A Scavenger Hunt for Service Robots. In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), May 2021.
  Video presentation
  Details     BibTeX     Download: [pdf] (1.5MB )  

• Harel Yedidsion, Shani Alkoby, and Peter Stone. Sequential Online Chore Division for Autonomous Vehicle Convoy Formation. Technical Report arXiv e-Prints 2104.04159, arXiv, 2021.
  arXiv
  Details     BibTeX     Download: [pdf] (478.9kB )  

• Siddarth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, and Peter Stone. An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch. In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020), December 2020.
  Poster
  Details     BibTeX     Download: [pdf] (1.3MB )  

• Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, and Peter Stone. Stochastic Grounded Action Transformation for Robot Learning in Simulation. In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
  11-minute video presentation.
  Details     BibTeX     Download: [pdf] (1.9MB )  

• Ishan Durugkar, Elad Liebman, and Peter Stone. Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July 2020.
  15-minute presentation
  Details     BibTeX     Download: [pdf] (3.9MB )  

• Justin Hart, Reuth Mirsky, Xuesu Xiao, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter Stone. Using Human-Inspired Signals to Disambiguate Navigational Intentions. In Proceedings of the 12th International Conference on Social Robotics (ICSR), November 2020.
  Video presentation
  Details     BibTeX     Download: [pdf] (3.2MB )  

• Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, and Peter Stone. Reinforced Grounded Action Transformation for Sim-to-Real Transfer. In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
  14-minute video presentation.
  Details     BibTeX     Download: [pdf] (506.6kB )  

• Shih-Yun Lo, Shiqi Zhang, and Peter Stone. The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation. 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 )  

• Keting Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen. Learning and Reasoning for Robot Dialog and Navigation Tasks. 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 )  

• Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, and Peter Stone. Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. Journal of Machine Learning Research, 21(181):1–50, 2020.
  Details     BibTeX     Download: [pdf] (1.4MB )  

• Sanmit Narvekar and Peter Stone. Generalizing Curricula for Reinforcement Learning. 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 )  

• Jin-Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone. Learning to Improve Multi-Robot Hallway Navigation. In Proceedings of the 4th Conference on Robot Learning (CoRL), November 2020.
  Video presentation
  Details     BibTeX     Download: [pdf] (1.3MB )  

• Brahma Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, and Peter Stone. RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration. IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS), 5:6262–69, October 2020.
  Video of the experiments; 13-minute video presentation.
  Details     BibTeX     Download: [pdf] (405.1kB )  [slides.pptx] (115.4MB )  

• Brahma Pavse, Ishan Durugkar, Josiah Hanna, and Peter Stone. Reducing Sampling Error in Batch Temporal Difference Learning. 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 )  

• Brahma S. Pavse, Josiah P. Hanna, Ishan Durugkar, and Peter Stone. On Sampling Error in Batch Action-Value Prediction Algorithms. In In the Offline Reinforcement Learning Workshop at Neural Information Processing Systems (NeurIPS), December 2020., December 2020.
  5-mins Video Presentation
  Details     BibTeX     Download: [pdf] (327.2kB )  

• Rishi Shah, Yuqian Jiang, Justin Hart, and Peter Stone. Deep R-Learning for Continual Area Sweeping. 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 )  

• Lemeng Wu, Bo Liu, Peter Stone, and Qiang Liu. Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks. In Advances in Neural Information Processing Systems 34 (2020), December 2020.
  Details     BibTeX     Download: [pdf] (8.1MB )  [slides.pdf] (744.8kB )  

• Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, and Peter Stone. APPLD: Adaptive Planner Parameter Learning from Demonstration. IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS), June 2020.
  5-minute Video presentation; 15-minute Video presentation
  Project webpage
  Details     BibTeX     Download: [pdf] (2.2MB )  [slides.pdf] (21.1MB )  

• Manish Ravula, Shani Alkobi and Peter Stone. Ad hoc Teamwork with Behavior Switching Agents. In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (350.4kB )  

• Josiah Hanna, Scott Niekum, and Peter Stone. Importance Sampling Policy Evaluation with an Estimated Behavior Policy. In Proceedings of the 36th International Conference on Machine Learning (ICML), June 2019.
  Details     BibTeX     Download: [pdf] (2.7MB )  [slides.pdf] (4.0MB )  

• Josiah Hanna and Peter Stone. Reducing Sampling Error in Policy Gradient Learning. 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 )  

• Yuqian Jiang, Shiqi Zhang, Piyush Khandelwal, and Peter Stone. Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems. Frontiers of Information Technology and Electronic Engineering, 20(3):363–373, Springer, March 2019.
  Official version from Publisher's Webpage
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• Yuqian Jiang, Harel Yedidsion, Shiqi Zhang, Guni Sharon, and Peter Stone. Multi-Robot Planning with Conflicts and Synergies. Autonomous Robots, Springer, March 2019.
  Official version from Publisher's Webpage
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• Yuqian Jiang, Fangkai Yang, Shiqi Zhang, and Peter Stone. Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), November 2019.
  Details     BibTeX     Download: [pdf] (925.2kB )  

• Yuqian Jiang, Nick Walker, Justin Hart, and Peter Stone. Open-World Reasoning for Service Robots. In Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), July 2019.
  Accompanying video
  Details     BibTeX     Download: [pdf] (813.5kB )  

• Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone Peter Stone. The right music at the right time: adaptive personalized playlists based on sequence modeling. 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.
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• Patrick MacAlpine, Faraz Torabi, Brahma Pavse, and Peter Stone. UT Austin Villa: RoboCup 2019 3D Simulation League Competition and Technical Challenge Champions. 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     BibTeX     Download: [pdf] (233.2kB )  [ps] (3.8MB )  

• Patrick MacAlpine, Faraz Torabi, Brahma Pavse, John Sigmon, and Peter Stone. UT Austin Villa: RoboCup 2018 3D Simulation League Champions. 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     BibTeX     Download: [pdf] (486.2kB )  [ps] (6.0MB )  

• Rishi Shah, Yuqian Jiang, Haresh Karnan, Gilberto Briscoe-Martinez, Dominick Mulder, Ryan Gupta, Rachel Schlossman, Marika Murphy, Justin Hart, Luis Sentis, and Peter Stone. Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report. In AAAI Fall Symposium on Artificial Intelligence and Human-Robot Interaction for Service Robots in Human Environments (AI-HRI 2019), November 2019.
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• Felipe Leno Da Silva, Garrett Warnell, Anna Helena Reali Costa, and Peter Stone. Agents teaching agents: a survey on inter-agent transfer learning. Autonomous Agents and Multi-Agent Systems, Dec 2019.
  Official version from JAAMAS
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• Felipe Leno Da Silva, Anna Helena Reali Costa, and Peter Stone. Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games. In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), October 2019.
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• Faraz Torabi, Garrett Warnell, and Peter Stone. Imitation Learning from Video by Leveraging Proprioception. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (1.1MB )  [slides.pptx] (20.3MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Recent Advances in Imitation Learning from Observation. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (157.4kB )  [slides.pptx] (45.5MB )  

• Faraz Torabi, Garrett Warnell, and Peter Stone. Generative Adversarial Imitation from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
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• Faraz Torabi, Sean Geiger, Garrett Warnell, and Peter Stone. Sample-efficient Adversarial Imitation Learning from Observation. In Imitation, Intent, and Interaction (I3) Workshop at ICML 2019, June 2019.
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• Nick Walker, Yuqian Jiang, Maya Cakmak, and Peter Stone. Desiderata for Planning Systems in General-Purpose Service Robots. In Proceedings of the ICAPS Workshop on Planning and Robotics (PlanRob 2019), July 2019.
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• Harel Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter Stone, and Raymond Mooney. Optimal Use of Verbal Instructions for Multi-robot Human Navigation Guidance. In International Conference on Social Robotics (ICSR), pp. 133–143, November 2019.
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• Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, and Peter Stone. Leveraging Human Guidance for Deep Reinforcement Learning Tasks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
  Details     BibTeX     Download: [pdf] (471.1kB )  [slides.pdf] (1.2MB )  

• 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. Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas --- Final Report. Technical Report 0-6838-3, The University of Texas at Austin Center for Transportation Research, 2018.
  Available online
  Details     BibTeX     Download: (unavailable)

• Patrick MacAlpine and Peter Stone. Overlapping Layered Learning. 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     BibTeX     Download: [pdf] (1.2MB )  [ps] (3.8MB )  

• Patrick MacAlpine and Peter Stone. UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions. 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     BibTeX     Download: [pdf] (973.5kB )  [ps] (19.4MB )  

• Decebal Constantin Mocanu, Elena Mocanu, Peter Stone, Phuong H. Nguyen, Madeleine Gibescu, and Antonio Liotta. Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity Inspired by Network Science. Nature Communications, 9(2383), June 2018.
  Official version from Publisher's Webpage.
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• Tarun Rambha, Stephen D. Boyles, Avinash Unnikrishnan, and Peter Stone. Marginal Cost Pricing for System Optimal Traffic Assignment with Recourse under Supply-Side Uncertainty. Transportation Research Part B: Methodological, 110:104–21, 2018.
  Official version from Publisher's Webpage
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• Michael Albert, Vincent Conitzer, and Peter Stone. Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms?. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), May 2017.
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• Michael Albert, Vincent Conitzer, and Peter Stone. Automated Design of Robust Mechanisms. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), Feb 2017.
  Details     BibTeX     Download: [pdf] (366.4kB )  [slides.pdf] (2.7MB )  

• Stefano Albrecht, Somchaya Liemhetcharat, and Peter Stone. Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial. Autonomous Agents and Multi-Agent Systems, 31(4):765–66, July 2017.
  Official version from Publisher's Webpage
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• Stefano Albrecht and Peter Stone. Reasoning about Hypothetical Agent Behaviours and their Parameters. 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 )  

• Katie Genter, Tim Laue, and Peter Stone. Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale Ad Hoc Teamwork Robotics Competition. Autonomous Agents and Multi-Agent Systems (JAAMAS), 31(4):790–820, Springer, July 2017.
  Official version from Publisher's Webpage
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• Santiago Gonzalez, Vijay Chidambaram, Jivko Sinapov, and Peter Stone. CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression. In Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '17), July 2017.
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• Josiah Hanna, Philip Thomas, Peter Stone, and Scott Niekum. Data-Efficient Policy Evaluation Through Behavior Policy Search. In Proceedings of the 34th International Conference on Machine Learning (ICML), August 2017.
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• Josiah Hanna, Peter Stone, and Scott Niekum. Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. 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 )  

• Josiah Hanna and Peter Stone. Grounded Action Transformation for Robot Learning in Simulation. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
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• Matthew Hausknecht, Wen-Ke Li, Michael Mauk, and Peter Stone. Machine Learning Capabilities of a Simulated Cerebellum. "IEEE Transactions on Neural Networks and Learning Systems", 28(3):510–22, March 2017.
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• Todd Hester and Peter Stone. Intrinsically motivated model learning for developing curious robots. Artificial Intelligence, 247:170–86, June 2017.
  from journal website.
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• 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. BWIBots: A platform for bridging the gap between AI and human--robot interaction research. The International Journal of Robotics Research, 36(5--7):635–59, 2017.
  Accompanying videos at https://youtu.be/2UJG4-ejVww
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• Piyush Khandelwal and Peter Stone. Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.
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• 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. An Assessment of Autonomous Vehicles: Traffic Impacts and Infrastructure Needs --- Final Report. Technical Report 0-6847-1, The University of Texas at Austin Center for Transportation Research, 2017.
  Available online
  Details     BibTeX     Download: (unavailable)

• Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, and Peter Stone. Designing Better Playlists with Monte Carlo Tree Search. In Proceedings of the Twenty-Ninth Conference On Innovative Applications Of Artificial Intelligence (IAAI-17), February 2017.
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• Dongcai Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen. Leveraging Commonsense Reasoning and Multimodal Perception for Robot Spoken Dialog Systems. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2017.
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• Patrick MacAlpine and Peter Stone. Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges. 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     BibTeX     Download: [pdf] (518.7kB )  [ps] (2.6MB )  [slides.pdf] (45.5MB )  

• Patrick MacAlpine and Peter Stone. UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions. 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     BibTeX     Download: [pdf] (555.8kB )  [ps] (14.4MB )  

• Patrick MacAlpine and Peter Stone. Prioritized Role Assignment for Marking. 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     BibTeX     Download: [pdf] (1.7MB )  [ps] (13.5MB )  [slides.pdf] (157.3MB )  

• Patrick MacAlpine and Peter Stone. UT Austin Villa RoboCup 3D Simulation Base Code Release. 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     BibTeX     Download: [pdf] (394.2kB )  [ps] (2.1MB )  [slides.pdf] (107.1MB )  

• Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, and Peter Stone. Fast and Precise Black and White Ball Detection for RoboCup Soccer. In RoboCup-2017: Robot Soccer World Cup XXI, pp. 45–59, Springer, July 2017.
  Details     BibTeX     Download: [pdf] (254.2kB )  [ps] (716.1kB )  [slides.pdf] (1.5MB )  

• Sanmit Narvekar, Jivko Sinapov, and Peter Stone. Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), August 2017.
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• Guni Sharon, Michael W. Levin, Josiah P. Hanna, Tarun Rambha, Stephen D. Boyles, and Peter Stone. Network-wide Adaptive Tolling for Connected and Automated vehicles. 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: [pdf] (2.8MB )  [ps] (4.2MB )  

• Guni Sharon and Peter Stone. A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections. 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 )  

• Maxwell Svetlik, Matteo Leonetti, Jivko Sinapov, Rishi Shah, Nick Walker, and Peter Stone. Automatic Curriculum Graph Generation for Reinforcement Learning Agents. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
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• Shiqi Zhang, Yuqian Jiang, Guni Sharon, and Peter Stone. Multirobot Symbolic Planning under Temporal Uncertainty. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS), May 2017.
  Accompanying videos at https://youtu.be/ADbH3sppLHQ
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• Shiqi Zhang, Piyush Khandelwal, and Peter Stone. Dynamically Constructed (PO)MDPs for Adaptive Robot Planning. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), February 2017.
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• Shiqi Zhang and Peter Stone. Integrated Commonsense Reasoning and Probabilistic Planning. In Proceedings of 2017 ICAPS Workshop on Planning and Robotics, June 2017.
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• Tsz-Chiu Au, Shun Zhang, and Peter Stone. Autonomous Intersection Management for Semi-Autonomous Vehicles. In Dusan Teodorovi'c, editors, Handbook of Transportation, pp. 88–104, Routledge, 2016.
  Details     BibTeX     Download: [pdf] (2.6MB )  

• Samuel Barrett, Avi Rosenfeld, Sarit Kraus, and Peter Stone. Making Friends on the Fly: Cooperating with New Teammates. Artificial Intelligence, October 2016.
  Official version from journal website.
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• Ginevra Gaudioso, Matteo Leonetti, and Peter Stone. State Aggregation through Reasoning in Answer Set Programming. In Proceedings of the IJCAI Workshop on Autonomous Mobile Service Robots (WSR 16), July 2016.
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• Katie Genter and Peter Stone. Ad Hoc Teamwork Behaviors for Influencing a Flock. Acta Polytechnica, 56(1), 2016.
  Details     BibTeX     Download: [pdf] (421.5kB )  [ps] (1.6MB )  

• Katie Genter and Peter Stone. Adding Influencing Agents to a Flock. 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 )  

• Jonathan Grizou, Samuel Barrett, Manuel Lopes, and Peter Stone. Collaboration in Ad Hoc Teamwork: Ambiguous Tasks, Roles, and Communication. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (339.0kB )  

• Josiah P. Hanna, Michael Albert, Donna Chen, and Peter Stone. Minimum Cost Matching for Autonomous Carsharing. 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 )  

• Matthew Hausknecht and Peter Stone. Deep Reinforcement Learning in Parameterized Action Space. In Proceedings of the International Conference on Learning Representations (ICLR), May 2016.
  Details     BibTeX     Download: [pdf] (468.3kB )  

• Matthew Hausknecht and Peter Stone. Grounded Semantic Networks for Learning Shared Communication Protocols. In Deep Reinforcement Learning, NIPS Workshop, December 2016.
  Details     BibTeX     Download: [pdf] (899.9kB )  

• Matthew Hausknecht and Peter Stone. On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning. In Deep Reinforcement Learning: Frontiers and Challenges, IJCAI Workshop, July 2016.
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• Matthew Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan, and Peter Stone. Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (253.9kB )  

• Matthew Hausknecht, Yilun Chen, and Peter Stone. Deep Imitation Learning for Parameterized Action Spaces. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2016.
  Details     BibTeX     Download: [pdf] (483.4kB )  

• Kazunori Iwata, Elad Liebman, Peter Stone, Toyoshiro Nakashima, Yoshiyuki Anan, and Naohiro Ishii. Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines. In Roger Lee, editors, Computer and Information Science 2015, Studies in Computational Intelligence, Springer Verlag, Berlin, 2016.
  Details     BibTeX     Download: [pdf] (807.5kB )  

• Piyush Khandelwal, Elad Liebman, Scott Niekum, and Peter Stone. On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search. In Proceedings of The 33rd International Conference on Machine Learning, pp. 1319–1328, June 2016.
  Details     BibTeX     Download: [pdf] (1.3MB )  [slides.pdf] (1.7MB )  

• 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. Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas --- Final Report. Technical Report 0-6838-2, The University of Texas at Austin Center for Transportation Research, 2016.
  Available online
  Details     BibTeX     Download: (unavailable)

• Matteo Leonetti, Luca Iocchi, and Peter Stone. A synthesis of automated planning and reinforcement learning for efficient, robust decision-making. Artificial Intelligence, 241:103 – 130, September 2016.
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• David L. Leottau, Javier Ruiz-del-Solar, Patrick MacAlpine, and Peter Stone. A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer. 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     BibTeX     Download: [pdf] (625.8kB )  

• Elad Liebman, Peter Stone, and Corey N. White. Impact of Music on Decision Making in Quantitative Tasks. In 17th International Society for Music Information retrieval Conference (ISMIR), August 2016.
  Details     BibTeX     Download: [pdf] (591.1kB )  [slides.pdf] (678.6kB )  

• Patrick MacAlpine, Josiah Hanna, Jason Liang, and Peter Stone. UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions. 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     BibTeX     Download: [pdf] (790.2kB )  [ps] (7.2MB )  

• Patrick MacAlpine, Elad Liebman, and Peter Stone. Adaptation of Surrogate Tasks for Bipedal Walk Optimization. In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, July 2016.
  Details     BibTeX     Download: [pdf] (172.1kB )  [ps] (739.5kB )  [slides.pdf] (165.0MB )  

• Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, and Peter Stone. Source Task Creation for Curriculum Learning. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), May 2016.
  Details     BibTeX     Download: [pdf] (630.0kB )  [slides.pdf] (10.2MB )  

• Jivko Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone. Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
  Details     BibTeX     Download: [pdf] (6.6MB )  [slides.pdf] (5.2MB )  

• Jesse Thomason, Jivko Sinapov, Maxwell Svetlik, Peter Stone, and Raymond Mooney. Learning Multi-Modal Grounded Linguistic Semantics by Playing I Spy. In Proceedings of the 25th international joint conference on Artificial Intelligence (IJCAI), July 2016.
  Demo Video
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• Daniel Urieli and Peter Stone. An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis. In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
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• Daniel Urieli and Peter Stone. Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market. In Proceedings of the 30th Conference on Artificial Intelligence (AAAI 2016), February 2016.
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• Shiqi Zhang, Dongcai Lu, Xiaoping Chen, and Peter Stone. Robot Scavenger Hunt: A Standardized Framework for Evaluating Intelligent Mobile Robots. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2016.
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• Samuel Barrett and Peter Stone. Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 2015.
  Details     BibTeX     Download: [pdf] (993.2kB )  [ps] (2.8MB )  

• Mike Depinet, Patrick MacAlpine, and Peter Stone. Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League. 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     BibTeX     Download: [pdf] (905.3kB )  [ps] (42.3MB )  

• Fei Fang, Peter Stone, and Milind Tambe. When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing. 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     BibTeX     Download: [pdf] (456.7kB )  [ps] (983.9kB )  [slides.pptx] (6.2MB )  

• Katie Genter, Shun Zhang, and Peter Stone. Determining Placements of Influencing Agents in a Flock. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), May 2015.
  Details     BibTeX     Download: [pdf] (426.7kB )  [ps] (1.4MB )  [slides.pdf] (1.6MB )  

• Matthew Hausknecht and Peter Stone. The Impact of Determinism on Learning Atari 2600 Games. In AAAI Workshop on Learning for General Competency in Video Games, January 2015.
  Details     BibTeX     Download: [pdf] (65.1kB )  

• Matthew Hausknecht and Peter Stone. Deep Recurrent Q-Learning for Partially Observable MDPs. In AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents (AAAI-SDMIA15), November 2015.
  Details     BibTeX     Download: [pdf] (1.5MB )  [slides.pdf] (3.8MB )  

• Piyush Khandelwal, Samuel Barrett, and Peter Stone. Leading the Way: An Efficient Multi-robot Guidance System. 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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• W. Bradley Knox and Peter Stone. Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance. 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.
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• Elad Liebman, Benny Chor, and Peter Stone. Representative Selection in Nonmetric Datasets. "Applied Artificial Intelligence", 29:807–838, 2015.
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• Elad Liebman, Peter Stone, and Corey N. White. How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification. In 16th International Society for Music Information retrieval Conference (ISMIR), October 2015.
  Details     BibTeX     Download: [pdf] (832.6kB )  [ps] (6.3MB )  [slides.pdf] (2.0MB )  

• Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone. DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
  Details     BibTeX     Download: [pdf] (1.5MB )  [ps] (38.4MB )  [slides.pdf] (2.6MB )  

• Patrick MacAlpine, Mike Depinet, Jason Liang, and Peter Stone. UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions. 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     BibTeX     Download: [pdf] (235.7kB )  [ps] (1.9MB )  

• Patrick MacAlpine, Mike Depinet, and Peter Stone. UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning. 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     BibTeX     Download: [pdf] (714.7kB )  [ps] (2.5MB )  [slides.pdf] (105.3MB )  

• Patrick MacAlpine, Eric Price, and Peter Stone. SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning. 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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• Jacob Menashe and Peter Stone. Monte Carlo Hierarchical Model Learning. In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2015.
  Details     BibTeX     Download: [pdf] (693.2kB )  [ps] (18.4MB )  

• Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, and Peter Stone. Learning Inter-Task Transferability in the Absence of Target Task Samples. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2015.
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• Jesse Thomason, Shiqi Zhang, Raymond Mooney, and Peter Stone. Learning to Interpret Natural Language Commands through Human-Robot Dialog. In Proceedings of the 2015 International Joint Conference on Artificial Intelligence (IJCAI), July 2015.
  Demo
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• Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone. Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy. In Proceedings of the 13th International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR), September 2015.
  Demo Video
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• Shiqi Zhang and Peter Stone. CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot. In Proceedings of the 29th Conference on Artificial Intelligence (AAAI), January 2015.
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• Noa Agmon, Samuel Barrett, and Peter Stone. Modeling Uncertainty in Leading Ad Hoc Teams. In Proc. of 13th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2014.
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• Samuel Barrett, Noa Agmon, Noam Hazon, Sarit Kraus, and Peter Stone. Communicating with Unknown Teammates. In Proceedings of the Twenty-First European Conference on Artificial Intelligence, August 2014.
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• Katie Genter and Peter Stone. Influencing a Flock via Ad Hoc Teamwork. In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
  Details     BibTeX     Download: [pdf] (358.4kB )  [ps] (1.4MB )  [slides.pdf] (15.3MB )  

• Matthew Hausknecht, Joel Lehman, Risto Miikkulainen, and Peter Stone. A Neuroevolution Approach to General Atari Game Playing. IEEE Transactions on Computational Intelligence and AI in Games, 2014.
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• Piyush Khandelwal, Fangkai Yang, Matteo Leonetti, Vladimir Lifschitz, and Peter Stone. Planning in Action Language $\cal BC$ while Learning Action Costs for Mobile Robots. In International Conference on Automated Planning and Scheduling (ICAPS), June 2014.
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• Piyush Khandelwal and Peter Stone. Multi-robot Human Guidance using Topological Graphs. In AAAI Spring 2014 Symposium on Qualitative Representations for Robots (AAAI-SSS), March 2014.
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• Patrick MacAlpine, Katie Genter, Samuel Barrett, and Peter Stone. The RoboCup 2013 Drop-In Player Challenges: Experiments in Ad Hoc Teamwork. 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
  Details     BibTeX     Download: [pdf] (491.0kB )  [ps] (4.0MB )  [slides.pdf] (30.4MB )  

• Daniel Urieli and Peter Stone. TacTex'13: A Champion Adaptive Power Trading Agent. In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI 2014), July 2014.
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• Fangkai Yang, Piyush Khandelwal, Matteo Leonetti, and Peter Stone. Planning in Answer Set Programming while Learning Action Costs for Mobile Robots. In AAAI Spring 2014 Symposium on Knowledge Representation and Reasoning in Robotics (AAAI-SSS), March 2014.
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• Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone. The 2012 UT Austin Villa Code Release. In RoboCup-2013: Robot Soccer World Cup XVII, Springer Verlag, 2013.
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• Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone. UT Austin Villa 2012: Standard Platform League World Champions. 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.
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• Samuel Barrett, Peter Stone, Sarit Kraus, and Avi Rosenfeld. Teamwork with Limited Knowledge of Teammates. In Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, July 2013.
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• Dustin Carlino, Stephen D. Boyles, and Peter Stone. Auction-based autonomous intersection management. In Proceedings of the 16th IEEE Intelligent Transportation Systems Conference (ITSC), October 2013.
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• Doran Chakraborty and Peter Stone. Multiagent Learning in the Presence of Memory-Bounded Agents. Autonomous Agents and Multiagent Systems (JAAMAS), Springer, 2013.
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• Doran Chakraborty and Peter Stone. Cooperating with a Markovian Ad Hoc Teammate. In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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• Doran Chakraborty, Noa Agmon, and Peter Stone. Targeted Opponent Modeling of Memory-Bounded Agents. In Proceedings of the Adaptive Learning Agents Workshop (ALA), May 2013.
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• Alon Farchy, Samuel Barrett, Patrick MacAlpine, and Peter Stone. Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back. 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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• Katie Genter, Noa Agmon, and Peter Stone. Role-Based Ad Hoc Teamwork. 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.
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• Katie Genter, Noa Agmon, and Peter Stone. Ad Hoc Teamwork for Leading a Flock. In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), May 2013.
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• Katie Genter, Noa Agmon, and Peter Stone. Improving Efficiency of Leading a Flock in Ad Hoc Teamwork Settings. In AAMAS Autonomous Robots and Multirobot Systems (ARMS) Workshop, May 2013.
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• Todd Hester and Peter Stone. TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots. Machine Learning, 90(3):385–429, 2013.
  Official version from journal website.
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• Todd Hester and Peter Stone. The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots. 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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• Todd Hester, Manuel Lopes, and Peter Stone. Learning Exploration Strategies in Model-Based Reinforcement Learning. In The Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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• W. Bradley Knox, Peter Stone, and Cynthia Breazeal. Training a Robot via Human Feedback: A Case Study. In International Conference on Social Robotics, October 2013.
  BEST PAPER AWARD WINNER at ICSR 2013
  An associated video summarizing the paper (direct link).
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• Patrick MacAlpine, Nick Collins, Adrian Lopez-Mobilia, and Peter Stone. UT Austin Villa: RoboCup 2012 3D Simulation League Champion. 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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• Patrick MacAlpine, Francisco Barrera, and Peter Stone. Positioning to Win: A Dynamic Role Assignment and FormationPositioning System. 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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• Patrick MacAlpine, Elad Liebman, and Peter Stone. Simultaneous Learning and Reshaping of an Approximated Optimization Task. In AAMAS Adaptive Learning Agents (ALA) Workshop, May 2013.
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• Jacob Menashe, Katie Genter, Samuel Barrett, and Peter Stone. UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy. In The Eighth Workshop on Humanoid Soccer Robots at Humanoids 2013, October 2013.
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• Peter Stone, Gal A. Kaminka, Sarit Kraus, Jeffrey S. Rosenschein, and Noa Agmon. Teaching and leading an ad hoc teammate: Collaboration without pre-coordination. Artificial Intelligence, 203:35–65, Elsevier, October 2013.
  Official version from journal website.
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• Daniel Urieli and Peter Stone. Model-Selection for Non-Parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System. 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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• Daniel Urieli and Peter Stone. A Learning Agent for Heat-Pump Thermostat Control. In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
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• Noa Agmon and Peter Stone. Leading Ad Hoc Agents in Joint Action Settings with Multiple Teammates. In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
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• Noa Agmon, Chien-Liang Fok, Yehuda Emaliah, Peter Stone, Christine Julien, and Sriram Vishwanath. On Coordination in Practical Multi-Robot Patrol. In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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• Tsz-Chiu Au, Michael Quinlan, and Peter Stone. Setpoint Scheduling for Autonomous Vehicle Controllers. In Proceedings of IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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• Aijun Bai, Xiaoping Chen, Patrick MacAlpine, Daniel Urieli, Samuel Barrett, and Peter Stone. Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions. 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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• Samuel Barrett and Peter Stone. An Analysis Framework for Ad Hoc Teamwork Tasks. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
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• Samuel Barrett, Katie Genter, Todd Hester, Piyush Khandelwal, Michael Quinlan, Peter Stone, and Mohan Sridharan. Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing. Technical Report UT-AI-TR-12-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2012.
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• Dustin Carlino, Mike Depinet, Piyush Khandelwal, and Peter Stone. Approximately Orchestrated Routing and Transportation Analyzer: Large-scale Traffic Simulation for Autonomous Vehicles. In Proceedings of the 15th IEEE Intelligent Transportation Systems Conference (ITSC), September 2012.
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• Todd Hester, Michael Quinlan, and Peter Stone. RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control. In IEEE International Conference on Robotics and Automation (ICRA), May 2012.
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• Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, and Peter Stone. PAC Subset Selection in Stochastic Multi-armed Bandits. 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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• Piyush Khandelwal and Peter Stone. A Low Cost Ground Truth Detection System Using the Kinect. 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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• W. Bradley Knox, Brian D. Glass, Bradley C. Love, W. Todd Maddox, and Peter Stone. How Humans Teach Agents: A New Experimental Perspective. 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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• W. Bradley Knox, A. Ross Otto, Peter Stone, and Bradley Love. The Nature of Belief-Directed Exploratory Choice in Human Decision-Making. Frontiers in Psychology, 2(398), January 2012.
  Frontiers in Psychology
  Download article from publisher (free)
  A follow-up commentary by Erica Yu.
  Details     BibTeX     Download: (unavailable)

• W. Bradley Knox and Peter Stone. Reinforcement Learning from Simultaneous Human and MDP Reward. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2012.
  AAMAS 2012
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• W. Bradley Knox, Cynthia Breazeal, and Peter Stone. Learning from feedback on actions past and intended. 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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• Patrick MacAlpine, Samuel Barrett, Daniel Urieli, Victor Vu, and Peter Stone. Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition. 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     BibTeX     Download: [pdf] (461.2kB )  [ps] (2.0MB )  [slides.pdf] (204.2MB )  

• Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae \cStiurc\ua, Victor Vu, and Peter Stone. UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition. 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     BibTeX     Download: [pdf] (646.3kB )  [ps] (2.7MB )  [slides.pdf] (135.4MB )  

• Patrick MacAlpine and Peter Stone. Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk. 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
  Ukrainian translation by Domri team
  Details     BibTeX     Download: [pdf] (525.6kB )  [ps] (2.2MB )  [slides.pdf] (159.5MB )  

• Noa Agmon, Daniel Urieli, and Peter Stone. Multiagent Patrol Generalized to Complex Environmental Conditions. In Proceedings of the Twenty-Fifth Conference on ArtificialIntelligence (AAAI), August 2011.
  Extended version, book chapter
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• Tsz-Chiu Au, Neda Shahidi, and Peter Stone. Enforcing Liveness in Autonomous Traffic Management. In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
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• Samuel Barrett, Peter Stone, and Sarit Kraus. Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain. In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
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• Samuel Barrett and Peter Stone. Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards. In Tenth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
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• Samuel Barrett, Katie Genter, Matthew Hausknecht, Todd Hester, Piyush Khandelwal, Juhyun Lee, Michael Quinlan, Aibo Tian, Peter Stone, and Mohan Sridharan. Austin Villa 2010 Standard Platform Team Report. Technical Report UT-AI-TR-11-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, 2011.
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• Doran Chakraborty and Peter Stone. Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree. In Proceedings of the Twenty Eighth International Conference on Machine Learning (ICML), 2011.
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• Matthew Hausknecht, Tsz-Chiu Au, Peter Stone, David Fajardo, and Travis Waller. Dynamic Lane Reversal in Traffic Management. In Proceedings of IEEE Intelligent Transportation Systems Conference (ITSC), 2011.
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• Matthew Hausknecht, Tsz-Chiu Au, and Peter Stone. Autonomous Intersection Management: Multi-Intersection Optimization. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2011.
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• Todd Hester and Peter Stone. Learning and Using Models. In Marco Wiering and Martijn van Otterlo, editors, Reinforcement Learning: State of the Art, Springer Verlag, Berlin, Germany, 2011.
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• Shivaram Kalyanakrishnan and Peter Stone. Characterizing Reinforcement Learning Methods through Parameterized Learning Problems. Machine Learning (MLJ), 84(1--2):205–247, July 2011.
  Publisher's on-line version
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• Shivaram Kalyanakrishnan and Peter Stone. On Learning with Imperfect Representations. In Proceedings of the 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, pp. 17–24, IEEE, April 2011.
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• W. Bradley Knox and Peter Stone. Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report. 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     BibTeX     Download: [pdf] (372.4kB )  [ps] (41.6MB )  

• Raz Lin, Sarit Kraus, Noa Agmon, Samuel Barrett, and Peter Stone. Comparing Agents: Success against People in Security Domains. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, August 2011.
  Details     BibTeX     Download: [pdf] (387.5kB )  

• Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae\cStiurc\ua, Victor Vu, and Peter Stone. UT Austin Villa 2011 3D Simulation Team Report. Technical Report AI11-10, The University of Texas at Austin, Department of Computer Science, AI Laboratory, 2011.
  Details     BibTeX     Download: [pdf] (1.2MB )  [ps] (5.3MB )  

• David Pardoe and Peter Stone. A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2011.
  Details     BibTeX     Download: [pdf] (313.6kB )  [ps] (280.8kB )  

• Matthew E. Taylor and Peter Stone. An Introduction to Inter-task Transfer for Reinforcement Learning. AI Magazine, 32(1):15–34, 2011.
  Details     BibTeX     Download: [pdf] (237.0kB )  [ps] (773.0kB )  

• Daniel Urieli, Patrick MacAlpine, Shivaram Kalyanakrishnan, Yinon Bentor, and Peter Stone. On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer. 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     BibTeX     Download: [pdf] (530.9kB )  [ps] (1.6MB )  [slides.pptx] (3.8MB )  

• Shimon Whiteson, Brian Tanner, Matthew E. Taylor, and Peter Stone. Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning. 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     BibTeX     Download: [pdf] (165.3kB )  

• Samuel Barrett, Katie Genter, Todd Hester, Michael Quinlan, and Peter Stone. Controlled Kicking under Uncertainty. In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
  Details     BibTeX     Download: [pdf] (357.3kB )  [ps] (17.7MB )  

• Samuel Barrett, Matt E. Taylor, and Peter Stone. Transfer Learning for Reinforcement Learning on a Physical Robot. In Ninth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2010.
  AAMAS ALA 2010
  Details     BibTeX     Download: [pdf] (688.8kB )  [ps] (5.7MB )  

• Doran Chakraborty and Peter Stone. Convergence, Targeted Optimality and Safety in Multiagent Learning. In Proceedings of the Twenty-seventh International Conference on Machine Learning (ICML), June 2010.
  Details     BibTeX     Download: [pdf] (196.9kB )  [ps] (474.1kB )  

• Todd Hester and Peter Stone. Real Time Targeted Exploration in Large Domains. In The Ninth International Conference on Development and Learning (ICDL), August 2010.
  ICDL 2010
  Details     BibTeX     Download: [pdf] (253.9kB )  [ps] (554.1kB )  

• Todd Hester, Michael Quinlan, and Peter Stone. Generalized Model Learning for Reinforcement Learning on a Humanoid Robot. 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     BibTeX     Download: [pdf] (1.5MB )  [ps] (25.3MB )  

• Shivaram Kalyanakrishnan and Peter Stone. Efficient Selection of Multiple Bandit Arms: Theory and Practice. In Proceedings of the Twenty-seventh International Conference on Machine Learning (ICML), 2010.
  Details     BibTeX     Download: [pdf] (257.1kB )  [ps] (679.3kB )  

• Piyush Khandelwal, Matthew Hausknecht, Juhyun Lee, Aibo Tian, and Peter Stone. Vision Calibration and Processing on a Humanoid Soccer Robot. In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
  Details     BibTeX     Download: [pdf] (402.6kB )  [ps] (14.8MB )  

• W. Bradley Knox and Peter Stone. Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning. 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     BibTeX     Download: [pdf] (422.9kB )  [ps] (3.5MB )  

• David Pardoe, Peter Stone, Maytal Saar-Tsechansky, Tayfun Keskin, and Kerem Tomak. Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge. Informs Journal on Computing, 22(3):353–370, 2010.
  Details     BibTeX     Download: [pdf] (530.9kB )  [ps] (9.2MB )  

• David Pardoe and Peter Stone. Boosting for Regression Transfer. In Proceedings of the 27th International Conference on Machine Learning (ICML), June 2010.
  Some of the data used in the experiments.
  Details     BibTeX     Download: [pdf] (600.5kB )  [ps] (1.7MB )  

• David Pardoe, Doran Chakraborty, and Peter Stone. TacTex09: A Champion Bidding Agent for Ad Auctions. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), May 2010.
  Details     BibTeX     Download: [pdf] (564.3kB )  [ps] (1.0MB )  

• Michael Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter Stone. Bringing Simulation to Life: A Mixed Reality Autonomous Intersection. 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     BibTeX     Download: [pdf] (1.3MB )  [ps] (10.6MB )  

• Adam Setapen, Michael Quinlan, and Peter Stone. MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training. 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     BibTeX     Download: [pdf] (533.2kB )  [ps] (9.7MB )  

• Peter Stone, Michael Quinlan, and Todd Hester. The Essence of Soccer, Can Robots Play Too?. 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)
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• Peter Stone, Gal A. Kaminka, Sarit Kraus, and Jeffrey S. Rosenschein . Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination. 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 )  

• Peter Stone and Sarit Kraus. To Teach or not to Teach? Decision Making Under Uncertainty in Ad Hoc Teams. 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     BibTeX     Download: [pdf] (180.6kB )  [ps] (285.3kB )  

• Shimon Whiteson, Matthew E. Taylor, and Peter Stone. Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning. Journal of Autonomous Agents and Multi-Agent Systems, 21(1):1–27, 2010.
  Details     BibTeX     Download: [pdf] (760.6kB )  [ps] (1.9MB )  

• Todd Hester, Michael Quinlan, Peter Stone, and Mohan Sridharan. TT-UT Austin Villa 2009: Naos across Texas. Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory, 2009.
  Details     BibTeX     Download: [pdf] (787.9kB )  [ps] (7.0MB )  

• Tobias Jung, Mazda Ahmadi, and Peter Stone. Connectivity-based Localization in Robot Networks. In International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09), June 2009.
  Details     BibTeX     Download: [pdf] (176.8kB )  [ps] (514.7kB )  

• Mohan Sridharan and Peter Stone. Color Learning and Illumination Invariance on Mobile Robots: A Survey. Robotics and Autonomous Systems (RAS) Journal, 57(60-7):629–44, June 2009.
  Details     BibTeX     Download: [pdf] (1.3MB )  [ps] (6.0MB )  

• Mazda Ahmadi and Peter Stone. Instance-Based Action Models for Fast Action Planning. 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     BibTeX     Download: [pdf] (466.3kB )  [ps] (3.0MB )  

• Patrick Beeson, Jack O'Quin, Bartley Gillan, Tarun Nimmagadda, Mickey Ristroph, David Li, and Peter Stone. Multiagent Interactions in Urban Driving. Journal of Physical Agents, 2(1):15–30, March 2008. Special issue on Multi-Robot Systems
  JoPhA
  Details     BibTeX     Download: [pdf] (2.1MB )  [ps] (6.6MB )  

• Uli Grasemann, Daniel Stronger, and Peter Stone. A Neural Network-Based Approach to Robot Motion Control. 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     BibTeX     Download: [pdf] (280.9kB )  [ps] (1.6MB )  

• Todd Hester and Peter Stone. Negative Information and Line Observations for Monte Carlo Localization. In IEEE International Conference on Robotics and Automation, May 2008.
  ICRA 2008
  Details     BibTeX     Download: [pdf] (128.7kB )  [ps] (501.7kB )  

• Juhyun Lee, W. Bradley Knox, and Peter Stone. Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting. 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     BibTeX     Download: [pdf] (2.4MB )  [ps] (3.4MB )  

• Daniel Stronger and Peter Stone. Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents. International Journal on Artificial Intelligence Tools, 17(1):159–174, February 2008.
  official published version
  Details     BibTeX     Download: [pdf] (236.4kB )  [ps] (1.0MB )  

• Daniel Stronger and Peter Stone. Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot. In IEEE International Conference on Robotics and Automation, May 2008.
  ICRA 2008
  Details     BibTeX     Download: [pdf] (182.1kB )  [ps] (902.7kB )  

• Mazda Ahmadi, Matthew E. Taylor, and Peter Stone. IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks. In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
  BEST PAPER AWARD NOMINEE.
  AAMAS-2007
  Details     BibTeX     Download: [pdf] (261.6kB )  [ps] (1.0MB )  

• Peggy Fidelman and Peter Stone. The Chin Pinch: A Case Study in Skill Learning on a Legged Robot. 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     BibTeX     Download: [pdf] (186.9kB )  [ps] (1.6MB )  

• Manish Saggar, Thomas D'Silva, Nate Kohl, and Peter Stone. Autonomous Learning of Stable Quadruped Locomotion. 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     BibTeX     Download: [pdf] (1.1MB )  [ps] (26.8MB )  

• Mohan Sridharan and Peter Stone. Structure Based Color Learning on a Mobile Robot under Changing Illumination. Autonomous Robots, 23(3):161–182, 2007.
  Official versionfrom the Autonomous Robots publisher's webpage.
  Details     BibTeX     Download: [pdf] (2.0MB )  [ps] (8.6MB )  

• Mohan Sridharan and Peter Stone. Planning Actions to Enable Color Learning on a Mobile Robot. International Journal of Information and Systems Sciences, 3(3):510–25, 2007.
  official published version
  Details     BibTeX     Download: (unavailable)

• Mohan Sridharan and Peter Stone. Action Selection for Illumination Invariant Color Learning. In The IEEE International Conference on Intelligent Robots and Systems (IROS), 2007.
  Details     BibTeX     Download: [pdf] (176.5kB )  [ps] (490.5kB )  

• Mohan Sridharan and Peter Stone. Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination. In The 20th International Joint Conference on Artificial Intelligence, pp. 2212–2217, January 2007.
  IJCAI-07
  Details     BibTeX     Download: [pdf] (129.5kB )  [ps] (184.9kB )  

• Peter Stone. Intelligent Autonomous Robotics: A Robot Soccer Case Study, Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan \& Claypool Publishers, 2007.
  Available from Synthesis page.
  ISBN: 9781598291262
  Details     BibTeX     Download: (unavailable)

• Peter Stone. Learning and Multiagent Reasoning for Autonomous Agents. In The 20th International Joint Conference on Artificial Intelligence, pp. 13–30, January 2007.
  IJCAI-07
  Details     BibTeX     Download: [pdf] (308.5kB )  [ps] (379.3kB )  

• Peter Stone, Patrick Beeson, Tekin Mericli, and Ryan Madigan. DARPA Urban Challenge Technical Report: Austin Robot Technology. June 2007. Available from http://www.darpa.mil/grandchallenge/rules.asp
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• Daniel Stronger and Peter Stone. Selective Visual Attention for Object Detection on a Legged Robot. 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     BibTeX     Download: [pdf] (159.7kB )  [ps] (342.4kB )  

• Daniel Stronger and Peter Stone. A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot. In IEEE International Conference on Robotics and Automation, pp. 3915–3920, April 2007.
  Details     BibTeX     Download: [pdf] (271.4kB )  [ps] (2.2MB )  

• Mazda Ahmadi and Peter Stone. Keeping in Touch: Maintaining Biconnected Structure by Homogeneous Robots. 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     BibTeX     Download: [pdf] (105.0kB )  [ps] (128.8kB )  

• Mazda Ahmadi and Peter Stone. A Multi-Robot System for Continuous Area Sweeping Tasks. 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     BibTeX     Download: [pdf] (171.3kB )  [ps] (314.6kB )  

• Mohan Sridharan and Peter Stone. Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data. In The Ninth International Conference on Control, Automation, Robotics and Vision, December 2006.
  ICARCV 2006
  Details     BibTeX     Download: [pdf] (444.1kB )  [ps] (2.3MB )  

• Peter Stone, Mohan Sridharan, Daniel Stronger, Gregory Kuhlmann, Nate Kohl, Peggy Fidelman, and Nicholas K. Jong. From Pixels to Multi-Robot Decision-Making: A Study in Uncertainty. 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     BibTeX     Download: [pdf] (260.5kB )  [ps] (3.6MB )  

• Peter Stone, Gregory Kuhlmann, Matthew E. Taylor, and Yaxin Liu. Keepaway Soccer: From Machine Learning Testbed to Benchmark. 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     BibTeX     Download: [pdf] (567.7kB )  [ps] (2.3MB )  

• Peter Stone, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Tekin Mericli, Mohan Sridharan, and Shao-en Yu. The UT Austin Villa 2006 RoboCup Four-Legged Team. 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     BibTeX     Download: [pdf] (123.7kB )  [ps] (127.2kB )  

• Daniel Stronger and Peter Stone. Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot. 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     BibTeX     Download: [pdf] (372.6kB )  [ps] (1.4MB )  

• Mazda Ahmadi and Peter Stone. Continuous Area Sweeping: A Task Definition and Initial Approach. In The 12th International Conference on Advanced Robotics, July 2005.
  Some videos of the robot referenced in the paper.
  ICAR 2005
  Details     BibTeX     Download: [pdf] (186.7kB )  [ps] (243.1kB )  

• Mohan Sridharan and Peter Stone. Autonomous Color Learning on a Mobile Robot. In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
  Some videos of the robot referenced in the paper.
  AAAI 2005
  Details     BibTeX     Download: [pdf] (901.5kB )  [ps] (6.4MB )  

• Mohan Sridharan and Peter Stone. Real-Time Vision on a Mobile Robot Platform. 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     BibTeX     Download: [pdf] (396.1kB )  [ps] (5.0MB )  

• Mohan Sridharan, Gregory Kuhlmann, and Peter Stone. Practical Vision-Based Monte Carlo Localization on a Legged Robot. In IEEE International Conference on Robotics and Automation, April 2005.
  ICRA 2005
  Details     BibTeX     Download: [pdf] (217.6kB )  [ps] (2.0MB )  

• Peter Stone, Kurt Dresner, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger. The UT Austin Villa 2005 RoboCup Four-Legged Team. 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     BibTeX     Download: [pdf] (186.2kB )  [ps] (243.4kB )  

• Peter Stone, Kurt Dresner, Peggy Fidelman, Nicholas K. Jong, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger. The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age. 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     BibTeX     Download: [pdf] (555.3kB )  [ps] (1.6MB )