Planning
Classical AI planning considers how to change the state of the world from an initial state to a goal state given a set of possible operators. Relatively recently, the area has grown to include probabilistic domains and operators, bridging towards studies of Markov Decision Processes and learning.
Subareas:
Tsz-Chiu Au Postdoctoral Alumni chiu [at] cs utexas edu
Elad Liebman Ph.D. Student eladlieb [at] cs utexas edu
Peter Stone Faculty pstone [at] cs utexas edu
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Mobile Robot Planning using Action Language BC with Hierarchical Domain Abstractions 2014
Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone, In The 7th Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP), July 2014.
Multi-robot Human Guidance using Topological Graphs 2014
Piyush Khandelwal and Peter Stone, In AAAI Spring 2014 Symposium on Qualitative Representations for Robots (AAAI-SSS), March 2014.
Planning in Action Language BC while Learning Action Costs for Mobile Robots 2014
Piyush Khandelwal, Fangkai Yang, Matteo Leonetti, Vladimir Lifschitz, and Peter Stone, In International Conference on Automated Planning and Scheduling (ICAPS), June 2014.
Planning in Answer Set Programming while Learning Action Costs for Mobile Robots 2014
Fangkai Yang, Piyush Khandelwal, Matteo Leonetti, and Peter Stone,
A Learning Agent for Heat-Pump Thermostat Control 2013
Daniel Urieli and Peter Stone, In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'13), May 2013.
Adapting Discriminative Reranking to Grounded Language Learning 2013
Joohyun Kim and Raymond J. Mooney, In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL-2013), pp. 218--227, Sofia, Bulgaria, August 2013.
Learning Non-Myopically from Human-Generated Reward 2013
W. Bradley Knox and Peter Stone, In In Proceedings of the International Conference on Intelligent User Interfaces (IUI), March 2013.
Training a Robot via Human Feedback: A Case Study 2013
W. Bradley Knox, Peter Stone, and Cynthia Breazeal, In Social Robotics, October 2013.
Reinforcement Learning from Human Reward: Discounting in Episodic Tasks 2012
W. Bradley Knox and Peter Stone, In In Proceedings of the 21st IEEE International Symposium on Robot and Human Interactive Communication (Ro-Man), September 2012.
TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains. 2012
Todd Hester, PhD Thesis, The University of Texas at Austin. Code available at: http://www.ros.org/wiki/rl-texplore-ros-pkg.
A Neural Network-Based Approach to Robot Motion Control 2008
Uli Grasemann, Daniel Stronger, and Peter Stone, In RoboCup-2007: Robot Soccer World Cup XI, Ubbo Visser and Fernando Ribeiro and Takeshi Ohashi and Frank Dellaert (Eds.), Vol. 5001, pp. 480-87, Berlin 2008. Springer Verlag.
Hierarchical Model-Based Reinforcement Learning: Rmax + MAXQ 2008
Nicholas K. Jong and Peter Stone, In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
Instance-Based Action Models for Fast Action Planning 2008
Mazda Ahmadi and Peter Stone, In RoboCup-2007: Robot Soccer World Cup XI, Ubbo Visser and Fernando Ribeiro and Takeshi Ohashi and Frank Dellaert (Eds.), Vol. 5001, pp. 1-16, Berlin 2008. Springer Verlag.
Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting 2008
Juhyun Lee, W. Bradley Knox, and Peter Stone, Journal of Physical Agents, Vol. 2, 2 (2008), pp. 41-50. Special Issue on Human Interaction with Domestic Robots.
Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot 2008
Daniel Stronger and Peter Stone, In IEEE International Conference on Robotics and Automation, May 2008.
Negative Information and Line Observations for Monte Carlo Localization 2008
Todd Hester and Peter Stone, In IEEE International Conference on Robotics and Automation, May 2008.
Online Kernel Selection for Bayesian Reinforcement Learning 2008
Joseph Reisinger, Peter Stone, and Risto Miikkulainen, In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
Online Multiagent Learning against Memory Bounded Adversaries 2008
Doran Chakraborty and Peter Stone, In Machine Learning and Knowledge Discovery in Databases, Vol. 5212, pp. 211-26, September 2008.
Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents 2008
Daniel Stronger and Peter Stone, International Journal on Artificial Intelligence Tools, Vol. 17, 1 (2008), pp. 159-174.
The Utility of Temporal Abstraction in Reinforcement Learning 2008
Nicholas K. Jong, Todd Hester, and Peter Stone, In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
Transferring Instances for Model-Based Reinforcement Learning 2008
Matthew E. Taylor, Nicholas K. Jong, and Peter Stone, In Machine Learning and Knowledge Discovery in Databases, Vol. 5212, pp. 488-505, September 2008.
A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot 2007
Daniel Stronger and Peter Stone, In IEEE International Conference on Robotics and Automation, pp. 3915-3920, April 2007.
Action Selection for Illumination Invariant Color Learning 2007
Mohan Sridharan and Peter Stone, In The IEEE International Conference on Intelligent Robots and Systems (IROS) 2007.
Adapting Price Predictions in TAC SCM 2007
David Pardoe and Peter Stone, In AAMAS 2007 Workshop on Agent Mediated Electronic Commerce 2007.
Autonomous Return on Investment Analysis of Additional Processing Resources 2007
Jonathan Wildstrom, Peter Stone, and Emmett Witchel, In 2007 Workshop on Adaptive Methods in Autonomic Computing Systems, June 2007.
Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination 2007
Mohan Sridharan and Peter Stone, In The 20th International Joint Conference on Artificial Intelligence, pp. 2212-2217, January 2007.
DARPA Urban Challenge Technical Report: Austin Robot Technology 2007
Peter Stone, Patrick Beeson, Tekin Mericli, and Ryan Madigan, Available from http://www.darpa.mil/grandchallenge/rules.asp.
Learning and Multiagent Reasoning for Autonomous Agents 2007
Peter Stone, In The 20th International Joint Conference on Artificial Intelligence, pp. 13-30, January 2007.
Machine Learning for On-Line Hardware Reconfiguration 2007
Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin, In The 20th International Joint Conference on Artificial Intelligence, pp. 1113-1118, January 2007.
Multiagent learning is not the answer. It is the question 2007
Peter Stone, Artificial Intelligence, Vol. 171 (2007), pp. 402-05.
Planning Actions to Enable Color Learning on a Mobile Robot 2007
Mohan Sridharan and Peter Stone, International Journal of Information and Systems Sciences, Vol. 3, 3 (2007), pp. 510-25.
Sharing the Road: Autonomous Vehicles meet Human Drivers 2007
Kurt Dresner and Peter Stone, In The 20th International Joint Conference on Artificial Intelligence, pp. 1263-68, January 2007.
Structure Based Color Learning on a Mobile Robot under Changing Illumination 2007
Mohan Sridharan and Peter Stone, Autonomous Robots, Vol. 23, 3 (2007), pp. 161-182.
Adapting to Workload Changes Through On-The-Fly Reconfiguration 2006
Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin, Technical Report UT-AI-TR-06-330, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data 2006
Mohan Sridharan and Peter Stone, In The Ninth International Conference on Control, Automation, Robotics and Vision, December 2006.
Designing Safe, Profitable Automated Stock Trading Agents Using Evolutionary Algorithms 2006
Harish Subramanian, Subramanian Ramamoorthy, Peter Stone, and Benjamin Kuipers, In Proceedings of the Genetic and Evolutionary Computation Conference, July 2006.
From Pixels to Multi-Robot Decision-Making: A Study in Uncertainty 2006
Peter Stone, Mohan Sridharan, Daniel Stronger, Gregory Kuhlmann, Nate Kohl, Peggy Fidelman, and Nicholas K. Jong, Robotics and Autonomous Systems, Vol. 54, 11 (2006), pp. 933-43. Special issue on Planning Under Uncertainty in Robotics..
Human-Usable and Emergency Vehicle-Aware Control Policies for Autonomous Intersection Management 2006
Kurt Dresner and Peter Stone, In AAMAS 2006 Workshop on Agents in Traffic and Transportation, May 2006.
Multiagent Traffic Management: Opportunities for Multiagent Learning 2006
Kurt Dresner and Peter Stone, In LAMAS 2005, K. Tuyls et al. (Eds.), Vol. 3898, pp. 129-138, Berlin 2006. Springer Verlag.
Predictive Planning for Supply Chain Management 2006
David Pardoe and Peter Stone, In Proceedings of the International Conference on Automated Planning and Scheduling, June 2006.
Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot 2006
Daniel Stronger and Peter Stone, Connection Science, Vol. 18, 2 (2006), pp. 97-119. Special Issue on Developmental Robotics..
A Model-Based Approach to Robot Joint Control 2005
Daniel Stronger and Peter Stone, In RoboCup-2004: Robot Soccer World Cup VIII, Daniele Nardi and Martin Riedmiller and Claude Sammut (Eds.), Vol. 3276, pp. 297-309, Berlin 2005. Springer Verlag.
A Polynomial-time Nash Equilibrium Algorithm for Repeated Games 2005
Michael L. Littman and Peter Stone, Decision Support Systems, Vol. 39 (2005), pp. 55-66.
Autonomous Color Learning on a Mobile Robot 2005
Mohan Sridharan and Peter Stone, In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
Continuous Area Sweeping: A Task Definition and Initial Approach 2005
Mazda Ahmadi and Peter Stone, In The 12th International Conference on Advanced Robotics, July 2005.
Multiagent Traffic Management: An Improved Intersection Control Mechanism 2005
Kurt Dresner and Peter Stone, In The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, Frank Dignum and Virginia Dignum and Sven Koenig and Sarit Kraus and Munindar P. Singh and Michael Woo...
Real-Time Vision on a Mobile Robot Platform 2005
Mohan Sridharan and Peter Stone, In IEEE/RSJ International Conference on Intelligent Robots and Systems, August 2005.
Three Automated Stock-Trading Agents: A Comparative Study 2005
Alexander Sherstov and Peter Stone, In Agent Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems (AMEC 2004), P. Faratin and J.A. Rodriguez-Aguilar (Eds.), Vol. 3435, pp. 173-187, ...
Towards Illumination Invariance in the Legged League 2005
Mohan Sridharan and Peter Stone, In RoboCup-2004: Robot Soccer World Cup VIII, Daniele Nardi and Martin Riedmiller and Claude Sammut (Eds.), Vol. 3276, pp. 196-208, Berlin 2005. Springer Verlag.
Towards Self-Configuring Hardware for Distributed Computer Systems 2005
Jonathan Wildstrom, Peter Stone, E. Witchel, Raymond Mooney and M. Dahlin, In The Second International Conference on Autonomic Computing, pp. 241-249, June 2005.
Adaptive Job Routing and Scheduling 2004
Shimon Whiteson and Peter Stone, Engineering Applications of Artificial Intelligence, Vol. 17(7), 7 (2004), pp. 855-869. Corrected version.
Goal-Converging Behavior Networks and Self-Solving Planning Domains 2004
Bernhard Nebel and Yuliya Lierler, In 16th European Conference on Artificial Intelligence 2004.
Irrelevant Actions in Plan Generation (extended abstract) 2004
Vladimir Lifschitz and Wanwan Ren, In IX Ibero-American Workshops on Artificial Intelligence, pp. 71-78 2004.
Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism 2004
Kurt Dresner and Peter Stone, In The Third International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 530-537, July 2004.
Two Stock-Trading Agents: Market Making and Technical Analysis 2004
Yi Feng, Ronggang Yu, and Peter Stone, In Agent Mediated Electronic Commerce V: Designing Mechanisms and Systems, Peyman Faratin and David C. Parkes and Juan A. Rodriguez-Aguilar and William E. Walsh (Eds.), Vol. 3048, pp. 18-36 200...
Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions 2003
Peter Stone, Robert E. Schapire, Michael L. Littman, J'anos A. Csirik, and David McAllester, Journal of Artificial Intelligence Research, Vol. 19 (2003), pp. 209-242.
Guest Editors' Introduction: Agents and Markets 2003
Amy Greenwald, Nicholas R. Jennings, and Peter Stone, IEEE Intelligent Systems, Vol. 18, 6 (2003), pp. 12-14.
Multiagent Competitions and Research: Lessons from RoboCup and TAC 2003
Peter Stone, In RoboCup-2002: Robot Soccer World Cup VI, Gal A. Kaminka and Pedro U. Lima and Raul Rojas (Eds.), Vol. 2752, pp. 224-237, Berlin 2003. Springer Verlag.
Performance Analysis of a Counter-intuitive Automated Stock-Trading Strategy 2003
Ronggang Yu and Peter Stone, In Proceedings of the Fifth International Conference on Electronic Commerce, Pittsburgh, PA, October 2003.
The RoboCup Soccer Server and CMUnited Clients: Implemented Infrastructure for MAS Research 2003
Itsuki Noda and Peter Stone, Autonomous Agents and Multi-Agent Systems, Vol. 7, 1--2 (2003), pp. 101-120.
Answer Set Programming and Plan Generation 2002
Vladimir Lifschitz, Artificial Intelligence, Vol. 138 (2002), pp. 39-54.
Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation 2002
Robert E. Schapire, Peter Stone, David McAllester, Michael L. Littman, and J'anos A. Csirik, In Proceedings of the Nineteenth International Conference on Machine Learning 2002.
An Architecture for Action Selection in Robotic Soccer 2001
Peter Stone and David McAllester, In Proceedings of the Fifth International Conference on Autonomous Agents, Elisabeth Andre and Sandip Sen and Claude Frasson and Jörg P. Müller (Eds.), pp. 316-323, New York, NY 2001. ACM Pres...
ATTac-2000: An Adaptive Autonomous Bidding Agent 2001
Peter Stone, Michael L. Littman, Satinder Singh, and Michael Kearns, Journal of Artificial Intelligence Research, Vol. 15 (2001), pp. 189-206.
Fages' Theorem and Answer Set Programming 2000
Yuliya Lierler, Esra Erdem and Vladimir Lifschitz, In Proceedings of International Workshop on Nonmonotonic Reasoning (NMR), pp. 33-35" ) INPROCEEDINGS(bab00, 2000. Springer.
Getting to the Airport: the Oldest Planning Problem in AI 2000
Vladimir Lifschitz, Norman McCain, Emilio Remolina and Armando Tacchella, In Logic-Based Artificial Intelligence, Jack Minker (Eds.), pp. 147-165 2000. Kluwer.
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer 2000
Peter Stone,
Multiagent Systems: A survey from a machine learning perspective 2000
Peter Stone and Manuela Veloso, Autonomous Robots, Vol. 8, 3 (2000), pp. 345-383.
Wire Routing and Satisfiability Planning 2000
Esra Erdem, Vladimir Lifschitz and Martin Wong, In Proceedings of International Conference on Computational Logic, pp. 822-836 2000.
Action Languages, Answer Sets and Planning 1999
Vladimir Lifschitz, In The Logic Programming Paradigm: a 25-Year Perspective, pp. 357-373 1999. Springer Verlag.
Answer Set Planning 1999
Vladimir Lifschitz, In Proceedings ICLP-99, pp. 23-37 1999.
Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork 1999
Peter Stone and Manuela Veloso, Artificial Intelligence, Vol. 110, 2 (1999), pp. 241-273.
Transformations of Logic Programs Related to Causality and Planning 1999
Esra Erdem and Vladimir Lifschitz, In Logic Programming and Non-monotonic Reasoning: Proceedings Fifth Int'l Conf. (Lecture Notes in Artificial Intelligence 1730), pp. 107-116 1999.
Satisfiability Planning with Causal Theories 1998
Norman McCain and Hudson Turner, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), Cohn, Anthony and Schubert, Lenhart and Shapiro, Stuart (Eds.), pp. 212-223 1998.
Using Decision Tree Confidence Factors for Multiagent Control 1998
Peter Stone and Manuela Veloso, In RoboCup-97: Robot Soccer World Cup I, Hiroaki Kitano (Eds.), Vol. 1395, pp. 99-111, Berlin 1998. Springer Verlag.
Interactive, Repair-Based Planning and Scheduling for Shuttle Payload Operations 1997
Gregg Rabideau, Steve Chien, Peter Stone, Jason Willis, Curt Eggemeyer, and Tobias Mann, In Proceedings of the 1997 IEEE Aerospace Conference, pp. 325-341, Aspen, CO, February 1997.
A Compositional Approach to Representing Planning Operators 1996
Peter Clark, Bruce Porter, and Don Batory , Technical Report AI06-331, University of Texas at Austin.
Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function 1996
Peter Stone and Manuela Veloso, In Advances in Neural Information Processing Systems 8, David S. Touretzky and Michael C. Mozer and Michael E. Hasselmo (Eds.), pp. 896-902, Cambridge, MA 1996. MIT Press.
User-guided Interleaving of Planning and Execution 1996
Peter Stone and Manuela Veloso, In New Directions in AI Planning, M. Ghallab and A. Milani (Eds.), pp. 103-112 1996. IOS Press.
FLECS: Planning with a Flexible Commitment Strategy 1995
Manuela Veloso and Peter Stone, Journal of Artificial Intelligence Research, Vol. 3 (1995), pp. 25-52.
Using Testing to Iteratively Improve Training 1995
Peter Stone and Manuela Veloso, In Working Notes of the AAAI 1995 Fall Symposium on Active Learning, pp. 110-111, Boston, MA, November 1995.
Learning to Solve Complex Planning Problems: Finding Useful Auxiliary Problems 1994
Peter Stone and Manuela Veloso, In Technical Report of the AAAI 1994 Fall Symposium on Planning and Learning: On to Real Applications, pp. 137-141, New Orleans, LA, November 1994.
The need for different domain-independent heuristics 1994
Peter Stone, Manuela Veloso, and Jim Blythe, In Proceedings of the Second International Conference on AI Planning Systems, pp. 164-169, June 1994.
On the Semantics of STRIPS 1987
Vladimir Lifschitz, In Reasoning about Actions and Plans, Georgeff, Michael and Lansky, Amy (Eds.), pp. 1-9, San Mateo, CA 1987. Morgan Kaufmann.