Peter Stone's Selected Publications
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NSF
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AFOSR
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AFRL
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ARL
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FLI
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ONR
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IBM
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DARPA
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FHWA
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TXDOT
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Fulbright
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Guggenheim
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Intel
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Raytheon
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Lockheed Martin
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Toyota
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ATT
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Alexander von Humboldt Foundation
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Bosch
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GM
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Unspecified
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NSF
- 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
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[pdf]
(1.8MB
)
[slides.pdf]
(1.8MB
)
- 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
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[pdf]
(415.0kB
)
- 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.
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[pdf]
(1014.3kB
)
- 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
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[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
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[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.
Details
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[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
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[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
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[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
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[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
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[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.
Details
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[pdf]
(1.2MB
)
- 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
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[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
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[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
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[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
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[pdf]
(405.1kB
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[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
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[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
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(327.2kB
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- 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
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[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
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[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
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[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.
Details
BibTeX
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[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
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(350.4kB
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- 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
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[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
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[pdf]
(1.5MB
)
[slides.pdf]
(3.1MB
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- 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.
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(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
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[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
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[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
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[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
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[pdf]
(813.5kB
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- 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
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[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
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[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
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[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
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[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
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[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
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[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
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[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
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[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
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[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.
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[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.
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[pdf]
(157.4kB
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[slides.pptx]
(45.5MB
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- 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
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(1.0MB
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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.
Details
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(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
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(651.5kB
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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.
Details
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(958.6kB
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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
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[pdf]
(471.1kB
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[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
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(670.7kB
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- 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.
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(2.5MB
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- 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
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[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
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[pdf]
(8.5MB
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[slides.pdf]
(983.4kB
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- 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
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[pdf]
(345.4kB
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- 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
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(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
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(2.6MB
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- 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
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[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
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(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
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(1.7MB
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- 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.
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[pdf]
(258.5kB
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- 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
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(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
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[pdf]
(973.5kB
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[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
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[pdf]
(538.3kB
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[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.
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(1.5MB
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- 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
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(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
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(2.9MB
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- 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
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(394.3kB
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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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[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
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[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.
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(1.4MB
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- 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.
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(1.6MB
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[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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(348.6kB
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[slides.pdf]
(2.8MB
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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.
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[pdf]
(366.4kB
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[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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[pdf]
(304.3kB
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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
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[pdf]
(608.2kB
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[slides.pdf]
(1.2MB
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- 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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(381.4kB
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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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(1.2MB
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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.
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[slides.pdf]
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- 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
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- 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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[pdf]
(518.7kB
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[ps]
(2.6MB
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[slides.pdf]
(45.5MB
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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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(1.7MB
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[ps]
(13.5MB
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[slides.pdf]
(157.3MB
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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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[ps]
(2.1MB
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[slides.pdf]
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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.
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[ps]
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[slides.pdf]
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- 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.
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- 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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[ps]
(7.1MB
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[slides.pptx]
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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.
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- 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.
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[pdf]
(1.2MB
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[ps]
(4.5MB
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[slides.pdf]
(433.7kB
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- 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.
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- 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.
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(117.5kB
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[ps]
(355.2kB
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[slides.pdf]
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- 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.
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[pdf]
(591.1kB
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[slides.pdf]
(678.6kB
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- 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
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- 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.
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(739.5kB
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[slides.pdf]
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- 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.
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(630.0kB
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[slides.pdf]
(10.2MB
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- 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.
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(6.6MB
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[slides.pdf]
(5.2MB
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- 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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[slides.pdf]
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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.
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(993.2kB
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(2.8MB
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- 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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(42.3MB
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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
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[ps]
(983.9kB
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[slides.pptx]
(6.2MB
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- 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.
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(1.4MB
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[slides.pdf]
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- 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.
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- 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.
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- 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.
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- 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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(846.3kB
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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.
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[pdf]
(832.6kB
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[ps]
(6.3MB
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[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.
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(1.5MB
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[ps]
(38.4MB
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[slides.pdf]
(2.6MB
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- 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
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(235.7kB
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[ps]
(1.9MB
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- 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
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(714.7kB
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(2.5MB
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[slides.pdf]
(105.3MB
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- 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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(260.3kB
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[ps]
(676.5kB
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[slides.pdf]
(40.3MB
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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.
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(693.2kB
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(18.4MB
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- 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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[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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(2.6MB
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[slides.pdf]
(1.3MB
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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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(306.0kB
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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
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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.
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- 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
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- 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. 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 R. 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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- 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
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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
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A follow-up
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- 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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- 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.
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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
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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: 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
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- 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.
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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
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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.
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- 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
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- 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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(2.0MB
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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.
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- 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.
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- 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.
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- 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
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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.
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- 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.
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- 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.
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- 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.
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- 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
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- 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
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- 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
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- 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
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- 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.
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- 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.
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- 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.
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- 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.
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- 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
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- 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.
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- 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
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- 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
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- 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.
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- 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
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- 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.
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- 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.
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- 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.
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- 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
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- 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.
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- 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
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- 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
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- 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.
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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
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- 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
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- 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.
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- 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.
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- 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.
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- Nicholas K. Jong and Peter
Stone. Model-Based Exploration in Continuous State Spaces. In The Seventh Symposium on Abstraction, Reformulation,
and Approximation, July 2007.
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- 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.
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- 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
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- 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.
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- 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.
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- 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.
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- 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.
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- 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
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- Mohan Sridharan and Peter Stone.
Action Selection for Illumination Invariant Color Learning. In The IEEE International Conference on Intelligent
Robots and Systems (IROS), 2007.
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(176.5kB
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- 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
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- 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
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- 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.
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- 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
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- 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.
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- 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.
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- 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.
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- 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
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- 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
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- 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
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- 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
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- 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
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- Michael P. Wellman, Amy
Greenwald, and Peter Stone. Autonomous Bidding Agents: Strategies
and Lessons from the Trading Agent Competition, MIT Press, 2007.
Available from
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- Shimon Whiteson, Matthew
E. Taylor, and Peter Stone. Empirical Studies in Action Selection
for Reinforcement Learning. Adaptive Behavior, 15(1):33–50, March 2007.
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- 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.
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- 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
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- 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).
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- 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
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- 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
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- 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
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- 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
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- 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.
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- 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
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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
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[pdf]
(186.7kB
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[ps]
(243.1kB
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- 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
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(143.5kB
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- 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.
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- 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.
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- 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
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(112.7kB
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[ps]
(287.8kB
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- David Pardoe and Peter Stone.
Developing Adaptive Auction Mechanisms. ACM SIGecom Exchanges, 5(3):1–10, April 2005.
SIGecom
Exchanges
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- 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
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- 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
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- 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
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(583.4kB
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[slides.pdf]
(193.7kB
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- 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
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- 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
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[pdf]
(245.1kB
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[ps]
(2.1MB
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- 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
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(901.5kB
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[ps]
(6.4MB
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- 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
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(396.1kB
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(5.0MB
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- 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
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- 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
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- 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
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[pdf]
(235.3kB
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[ps]
(489.4kB
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- 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
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(147.3kB
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[ps]
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- 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
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(230.4kB
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[ps]
(620.1kB
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- 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
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(566.8kB
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- 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.
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- 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
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(74.0kB
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(104.6kB
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- 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
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[pdf]
(233.8kB
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[ps]
(492.0kB
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- 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
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(512.0kB
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[ps]
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- 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
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(210.0kB
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(1.4MB
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- 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
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(301.5kB
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[ps]
(3.2MB
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- 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
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[pdf]
(170.3kB
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[ps]
(498.2kB
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- 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
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[pdf]
(145.3kB
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[ps]
(161.6kB
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- 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
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- 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
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- 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
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(201.5kB
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(170.3kB
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- 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)
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)
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.
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[pdf]
(1.5MB
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[slides.pdf]
(3.1MB
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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
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[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
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[pdf]
(157.4kB
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[slides.pptx]
(45.5MB
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- 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
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[pdf]
(1.0MB
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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.
Details
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[pdf]
(6.1MB
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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
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[pdf]
(471.1kB
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[slides.pdf]
(1.2MB
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- 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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(1.6MB
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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.
Details
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(348.6kB
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[slides.pdf]
(2.8MB
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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.
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(366.4kB
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[slides.pdf]
(2.7MB
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- 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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[pdf]
(304.3kB
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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
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Download:
[pdf]
(608.2kB
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[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
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[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
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[pdf]
(241.6kB
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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.
Details
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[pdf]
(1.2MB
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[slides.pdf]
(1.1MB
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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.
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[pdf]
(663.8kB
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[ps]
(572.6kB
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[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
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(1.3MB
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[slides.pdf]
(1.3MB
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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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- 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
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(4.4MB
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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.
Details
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(1.8MB
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- 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
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[pdf]
(377.0kB
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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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[pdf]
(518.7kB
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[ps]
(2.6MB
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[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
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[pdf]
(254.2kB
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[ps]
(716.1kB
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[slides.pdf]
(1.5MB
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- 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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(826.2kB
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[slides.pdf]
(5.8MB
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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
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[pdf]
(2.8MB
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[ps]
(4.2MB
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- 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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[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
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(2.0MB
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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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(2.3MB
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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.
Details
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(3.2MB
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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.
Details
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[pdf]
(917.9kB
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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.
Details
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[pdf]
(776.6kB
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- Katie Genter and Peter Stone.
Ad Hoc Teamwork Behaviors for Influencing a Flock. Acta Polytechnica, 56(1), 2016.
Details
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[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
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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
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[pdf]
(483.4kB
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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.
Details
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[pdf]
(1.3MB
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[slides.pdf]
(1.7MB
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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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[pdf]
(3.2MB
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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
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[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.
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[pdf]
(6.6MB
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[slides.pdf]
(5.2MB
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- 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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(3.1MB
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[slides.pdf]
(1.0MB
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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.
Details
BibTeX
Download:
[pdf]
(11.9MB
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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.
Details
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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
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[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
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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
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- 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
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Download:
[pdf]
(1.5MB
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[slides.pdf]
(3.8MB
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- Elad Liebman, Benny Chor, and
Peter Stone. Representative Selection in Nonmetric Datasets. "Applied
Artificial Intelligence", 29:807–838, 2015.
Details
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[pdf]
(846.3kB
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- 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
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[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
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[pdf]
(693.2kB
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[ps]
(18.4MB
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- 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
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[pdf]
(337.2kB
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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
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[pdf]
(358.4kB
)
[ps]
(1.4MB
)
[slides.pdf]
(15.3MB
)
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.
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(832.6kB
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[ps]
(6.3MB
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- 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.
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(1.5MB
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(38.4MB
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(2.6MB
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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.
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(693.2kB
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[ps]
(18.4MB
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- 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
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[pdf]
(337.2kB
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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
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[pdf]
(358.4kB
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[ps]
(1.4MB
)
[slides.pdf]
(15.3MB
)
ARL
- 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
)
- 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
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Download:
[pdf]
(1014.3kB
)
- 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
Details
BibTeX
Download:
[pdf]
(4.6MB
)
- 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.
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
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- 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, 2020.
Details
BibTeX
Download:
[pdf]
(648.8kB
)
- 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.
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
- 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
)
- 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
)
- 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.
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.
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
- 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
)
- 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
)
- 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.
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- 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
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- 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.
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- 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
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- 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
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- 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.
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- 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.
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(330.4kB
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[slides.pdf]
(3.8MB
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- 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
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- 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.
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(115.4MB
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- 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.
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(738.4kB
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[slides.pdf]
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- 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
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- 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.
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(374.2kB
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[slides.pdf]
(1.1MB
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- 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.
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(8.1MB
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[slides.pdf]
(744.8kB
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- 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.
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[slides.pdf]
(21.1MB
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- Manish Ravula, Shani Alkobi and Peter Stone. Ad hoc Teamwork with Behavior
Switching Agents. In International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
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- 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.
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(2.7MB
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[slides.pdf]
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- 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.
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[slides.pdf]
(3.1MB
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- 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.
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- 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
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- 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
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- 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
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- 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.
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(1.1MB
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[slides.pptx]
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- 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.
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(157.4kB
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[slides.pptx]
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- 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.
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(471.1kB
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[slides.pdf]
(1.2MB
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- 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
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(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
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(1.2MB
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(3.8MB
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- 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
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(19.4MB
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- 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
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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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(348.6kB
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[slides.pdf]
(2.8MB
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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.
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[slides.pdf]
(2.7MB
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- 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
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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
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(608.2kB
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[slides.pdf]
(1.2MB
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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
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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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[slides.pdf]
(1.1MB
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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.
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(663.8kB
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(572.6kB
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[slides.pdf]
(1.3MB
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- 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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(1.3MB
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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
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- 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.
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[pdf]
(518.7kB
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[ps]
(2.6MB
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[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
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(555.8kB
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(14.4MB
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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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(1.7MB
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[ps]
(13.5MB
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[slides.pdf]
(157.3MB
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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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(394.2kB
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[ps]
(2.1MB
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[slides.pdf]
(107.1MB
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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
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(254.2kB
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[ps]
(716.1kB
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[slides.pdf]
(1.5MB
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- 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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(826.2kB
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[slides.pdf]
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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.
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- 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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[pdf]
(1.1MB
)
[ps]
(7.1MB
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[slides.pptx]
(140.9MB
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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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- 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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(495.4kB
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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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(917.9kB
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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
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(421.5kB
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- 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.
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- 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.
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- 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.
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- 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.
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- 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
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- 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.
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- 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.
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- 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.
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- 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.
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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.
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- 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
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- 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.
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- 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.
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- 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.
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- 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.
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- 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.
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- 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
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- 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
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- 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.
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- 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.
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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.
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- 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
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- 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. 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 R. 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.
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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
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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
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A follow-up
commentary by Erica Yu.
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- 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
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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: 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
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- 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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[slides.pdf]
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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.
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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)
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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.
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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
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- 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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- 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.
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- 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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- 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.
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- 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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- 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.
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- 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.
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- 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.
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- 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
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- 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.
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- 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
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- 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
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- 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.
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- 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.
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- 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.
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- 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.
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- 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
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- 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
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- 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.
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- 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.
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- 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.
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- 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
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- Mohan Sridharan and Peter Stone.
Action Selection for Illumination Invariant Color Learning. In The IEEE International Conference on Intelligent
Robots and Systems (IROS), 2007.
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- 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
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(184.9kB
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- 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
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(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
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[pdf]
(308.5kB
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[ps]
(379.3kB
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- 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.
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(159.7kB
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[ps]
(342.4kB
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- 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.
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(271.4kB
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[ps]
(2.2MB
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- 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).
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(105.0kB
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(128.8kB
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- 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
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[pdf]
(171.3kB
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[ps]
(314.6kB
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- 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
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(444.1kB
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[ps]
(2.3MB
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- 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.
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(260.5kB
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[ps]
(3.6MB
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- 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
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[pdf]
(567.7kB
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[ps]
(2.3MB
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- 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
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(123.7kB
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[ps]
(127.2kB
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- 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.
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[pdf]
(372.6kB
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[ps]
(1.4MB
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- 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
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[pdf]
(186.7kB
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[ps]
(243.1kB
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- 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
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[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
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[pdf]
(396.1kB
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[ps]
(5.0MB
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- 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
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[pdf]
(217.6kB
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[ps]
(2.0MB
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- 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
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[pdf]
(186.2kB
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[ps]
(243.4kB
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- 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
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[pdf]
(555.3kB
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[ps]
(1.6MB
)
IBM
- 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
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[pdf]
(2.7MB
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[slides.pdf]
(4.0MB
)
- 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
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[pdf]
(2.2MB
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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
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[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
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[pdf]
(1.0MB
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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.
Details
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[pdf]
(6.1MB
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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
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[pdf]
(471.1kB
)
[slides.pdf]
(1.2MB
)
- 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
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(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
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[pdf]
(308.5kB
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[ps]
(379.3kB
)
- 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
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[pdf]
(1.7MB
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[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
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[pdf]
(316.7kB
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[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
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[pdf]
(754.2kB
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[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
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(unavailable)
- 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
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[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
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[pdf]
(74.0kB
)
[ps]
(104.6kB
)
- 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
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[pdf]
(664.7kB
)
[ps]
(1.1MB
)
DARPA
- 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
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[pdf]
(1.8MB
)
[slides.pdf]
(1.8MB
)
- 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
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[pdf]
(415.0kB
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- 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
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[pdf]
(1014.3kB
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- 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
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[pdf]
(1.3MB
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- 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
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[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.
Details
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[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
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[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
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(506.6kB
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- 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
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[pdf]
(4.0MB
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- 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
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(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.
Details
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[pdf]
(1.2MB
)
- 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
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[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
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[pdf]
(330.4kB
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[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
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[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
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[pdf]
(405.1kB
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[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
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[pdf]
(738.4kB
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[slides.pdf]
(5.2MB
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- 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
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(327.2kB
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- 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
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[pdf]
(374.2kB
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[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
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[pdf]
(8.1MB
)
[slides.pdf]
(744.8kB
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- 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.
Details
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[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
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[pdf]
(350.4kB
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- 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
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[pdf]
(2.7MB
)
[slides.pdf]
(4.0MB
)
- 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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[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
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[pdf]
(925.2kB
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- 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
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(813.5kB
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- 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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(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
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(4.5MB
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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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[pdf]
(572.4kB
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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.
Details
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[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
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[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
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[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
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[pdf]
(651.5kB
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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.
Details
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[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
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[pdf]
(471.1kB
)
[slides.pdf]
(1.2MB
)
- 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
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[pdf]
(2.0MB
)
- 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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(1.1MB
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[ps]
(32.8MB
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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.
Details
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(223.3kB
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[ps]
(521.1kB
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- Matthew Hausknecht and Peter Stone.
Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker. In Javier
Ruiz-del-Solar, Eric Chown, and Paul G. Plöger, editors, RoboCup-2010: Robot Soccer World Cup XIV, Lecture
Notes in Artificial Intelligence, pp. 254–65, Springer Verlag, Berlin, 2011.
Video and source code available at
http://www.cs.utexas.edu/~AustinVilla/?p=research/aibo_kick
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- 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
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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.
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- 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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- 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.
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- Shivaram Kalyanakrishnan and Peter
Stone. Learning Complementary Multiagent Behaviors: A Case Study. In Jacky Baltes, Michail G. Lagoudakis, Tadashi
Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot Soccer World Cup XIII, pp. 153–165, Springer Verlag,
2010.
BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
Some simulations
referenced in the paper.
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- Shivaram Kalyanakrishnan, Todd
Hester, Michael Quinlan, Yinon
Bentor, and Peter Stone. Three Humanoid Soccer Platforms: Comparison
and Synthesis. In Jacky Baltes, Michail G. Lagoudakis, Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009:
Robot Soccer World Cup XIII, pp. 140–152, Springer Verlag, 2010.
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- 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.
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- 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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- 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.
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- 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.
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- 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.
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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
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- 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.
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- 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.
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- 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
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- 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.
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- 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
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- 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
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- 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.
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- 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
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- Nicholas K. Jong and Peter
Stone. Model-Based Exploration in Continuous State Spaces. In The Seventh Symposium on Abstraction, Reformulation,
and Approximation, July 2007.
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- 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.
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- 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
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- 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.
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- 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.
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- 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.
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- 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
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- 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
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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.
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- 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.
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- 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
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- 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
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- 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
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- 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
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- 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
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- Shimon Whiteson, Matthew
E. Taylor, and Peter Stone. Empirical Studies in Action Selection
for Reinforcement Learning. Adaptive Behavior, 15(1):33–50, March 2007.
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- 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.
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- 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
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- 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
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- 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
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- 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.
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- 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
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- 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.
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- 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
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- 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.
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- 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.
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- 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
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- 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
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- 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
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- 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
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(449.9kB
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- 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
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FHWA
- 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.
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- 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.
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- 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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- 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.
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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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- 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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- 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. 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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- 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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- 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, Chien-Liang Fok,
Sriram Vishwanath, Christine
Julien, and Peter Stone. Evasion Planning for Autonomous Vehicles at
Intersections. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, October 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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- 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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- Chien-Liang Fok, Maykel
Hanna, Seth Gee, Tsz-Chiu Au, Peter
Stone, Christine Julien, and Sriram
Vishwanath. A Platform for Evaluating Autonomous Intersection Management Policies. In Proceedings of the ACM/IEEE
Third International Conference on Cyber-Physical Systems (ICCPS), April 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, 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
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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: 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
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- 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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[slides.pdf]
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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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- Matthew Hausknecht and Peter Stone.
Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker. In Javier
Ruiz-del-Solar, Eric Chown, and Paul G. Plöger, editors, RoboCup-2010: Robot Soccer World Cup XIV, Lecture
Notes in Artificial Intelligence, pp. 254–65, Springer Verlag, Berlin, 2011.
Video and source code available at
http://www.cs.utexas.edu/~AustinVilla/?p=research/aibo_kick
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- 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. 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.
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(5.3MB
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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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- 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
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[slides.pptx]
(3.8MB
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- 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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- 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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- Shivaram Kalyanakrishnan and Peter
Stone. Learning Complementary Multiagent Behaviors: A Case Study. In Jacky Baltes, Michail G. Lagoudakis, Tadashi
Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009: Robot Soccer World Cup XIII, pp. 153–165, Springer Verlag,
2010.
BEST STUDENT PAPER AWARD WINNER at RoboCup International Symposium.
Some simulations
referenced in the paper.
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- Shivaram Kalyanakrishnan, Todd
Hester, Michael Quinlan, Yinon
Bentor, and Peter Stone. Three Humanoid Soccer Platforms: Comparison
and Synthesis. In Jacky Baltes, Michail G. Lagoudakis, Tadashi Naruse, and Saeed Shiry Ghidary, editors, RoboCup 2009:
Robot Soccer World Cup XIII, pp. 140–152, Springer Verlag, 2010.
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- 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 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.
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- 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.
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- 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
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- 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
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[slides.pdf]
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- 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
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- 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.
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- 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.
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- 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.
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TXDOT
- 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
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- 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.
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- 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.
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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.
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(1.1MB
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- 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.
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- 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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- 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
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(471.1kB
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- 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.
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- 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.
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- 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
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- 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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- 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.
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[pdf]
(1002.7kB
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(5.2MB
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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
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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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- 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.
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- 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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(7.1MB
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- 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.
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(355.2kB
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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
Details
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Fulbright
- 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
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Download:
[pdf]
(1.1MB
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[slides.pptx]
(20.3MB
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- 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
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Download:
[pdf]
(157.4kB
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[slides.pptx]
(45.5MB
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- 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
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(1.0MB
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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.
Details
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[pdf]
(6.1MB
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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
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[pdf]
(471.1kB
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[slides.pdf]
(1.2MB
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- Peter Stone, Gal A. Kaminka,
Sarit Kraus, Jeffrey R. 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.
Details
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[pdf]
(499.6kB
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[ps]
(734.2kB
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- Peter Stone, Gal A. Kaminka,
and Jeffrey S. Rosenschein. Leading a Best-Response Teammate in an Ad
Hoc Team. In Esther David, Enrico Gerding, David Sarne, and Onn
Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets,
pp. 132–146, Springer Verlag, November 2010.
Official version from publisher's
webpage
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[pdf]
(179.3kB
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[ps]
(226.4kB
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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
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[pdf]
(119.0kB
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(266.6kB
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[slides.pdf]
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- 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
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(180.6kB
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(285.3kB
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Guggenheim
- 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
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Download:
[pdf]
(1.1MB
)
[slides.pptx]
(20.3MB
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- 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
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Download:
[pdf]
(157.4kB
)
[slides.pptx]
(45.5MB
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- 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
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[pdf]
(1.0MB
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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.
Details
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[pdf]
(6.1MB
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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
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[pdf]
(471.1kB
)
[slides.pdf]
(1.2MB
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- Peter Stone, Gal A. Kaminka,
Sarit Kraus, Jeffrey R. 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.
Details
BibTeX
Download:
[pdf]
(499.6kB
)
[ps]
(734.2kB
)
- Peter Stone, Gal A. Kaminka,
and Jeffrey S. Rosenschein. Leading a Best-Response Teammate in an Ad
Hoc Team. In Esther David, Enrico Gerding, David Sarne, and Onn
Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets,
pp. 132–146, Springer Verlag, November 2010.
Official version from publisher's
webpage
Details
BibTeX
Download:
[pdf]
(179.3kB
)
[ps]
(226.4kB
)
- 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
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[pdf]
(119.0kB
)
[ps]
(266.6kB
)
[slides.pdf]
(8.1MB
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- 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
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Download:
[pdf]
(180.6kB
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[ps]
(285.3kB
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Intel
- 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
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- 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
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[pdf]
(2.7MB
)
[slides.pdf]
(4.0MB
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- 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
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(2.2MB
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- 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, 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
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- 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.
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(953.0kB
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[slides.pdf]
(5.6MB
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- 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
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(1.7MB
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[slides.pptx]
(6.5MB
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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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(1.6MB
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- 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
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[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
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(651.5kB
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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
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[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
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- 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
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- 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
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[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
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[pdf]
(8.5MB
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[slides.pdf]
(983.4kB
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- 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
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[pdf]
(345.4kB
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- 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
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[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
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(2.6MB
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- 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
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(5.8MB
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[slides.pptx]
(32.7MB
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- 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
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(1.7MB
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- 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
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- 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
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(538.3kB
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(5.3MB
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- 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
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- 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
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(2.9MB
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- 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
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[pdf]
(1.4MB
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- 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
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[pdf]
(1.6MB
)
[slides.pptx]
(16.2MB
)
- Ishan Durugkar and Peter Stone.
TD Learning with Constrained Gradients. In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017,
December 2017.
Details
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[pdf]
(381.4kB
)
- 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.
Details
BibTeX
Download:
[pdf]
(2.0MB
)
Raytheon
- 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
)
- 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
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- 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.
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- 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.
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- 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.
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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.
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- 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
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- 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.
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- 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.
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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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- 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.
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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.
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- 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.
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- 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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- 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.
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- 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
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- 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.
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- 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.
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- 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.
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- Josiah Hanna and Peter Stone.
Towards a Data Efficient Off-Policy Policy Gradient. In AAAI Spring Symposium on Data Efficient Reinforcement Learning,
March 2018.
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- 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.
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- 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
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- 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
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- 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.
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- 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.
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- 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.
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- 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.
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- 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.
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- 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
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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.
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- 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)