Peter Stone
Professor
My main research interest in artificial intelligence is understanding how we can best create complete intelligent agents. I consider both adaptation and interaction to be essential capabilites of such agents. Thus, my research focuses mainly on machine learning and multiagent systems. Application domains include robot soccer, autonomous bidding agents, traffic management, and autonomic computing.
Homepage:
http://www.cs.utexas.edu/~pstone
Publications (267)
A Learning Agent for Heat-Pump Thermostat Control 2013
Daniel Urieli and Peter Stone
Ad Hoc Teamwork for Leading a Flock 2013
Katie Genter and Noa Agmon and Peter Stone
Cooperating with a Markovian Ad Hoc Teammate 2013
Doran Chakraborty and Peter Stone
Humanoid Robots Learning to Walk Faster: From the Real World to Simulation and Back 2013
Alon Farchy and Samuel Barrett and Patrick MacAlpine and Peter Stone
Learning Exploration Strategies in Model-Based Reinforcement Learning 2013
Todd Hester and Manuel Lopes and Peter Stone
Learning Non-Myopically from Human-Generated Reward 2013
W. Bradley Knox and Peter Stone
Multiagent Learning in the Presence of Memory-Bounded Agents 2013
Doran Chakraborty and Peter Stone
Positioning to Win: A Dynamic Role Assignment and Formation Positioning System 2013
Patrick MacAlpine and Francisco Barrera and Peter Stone
Simultaneous Learning and Reshaping of an Approximated Optimization Task 2013
Patrick MacAlpine and Elad Liebman and Peter Stone
Targeted Opponent Modeling of Memory-Bounded Agents 2013
Doran Chakraborty and Peter Stone
UT Austin Villa 2012: Standard Platform League World Champions 2013
Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone
{UT} {A}ustin {V}illa: {R}obo{C}up 2012 3{D} Simulation League Champion 2013
Patrick MacAlpine and Nick Collins and Adrian Lopez-Mobilia and Peter Stone
A Platform for Evaluating Autonomous Intersection Management Policies 2012
Chien-Liang Fok and Maykel Hanna and Seth Gee and Tsz-Chiu Au and Peter Stone and Christine Julien and Sriram Vishwanath
An Analysis Framework for Ad Hoc Teamwork Tasks 2012
Samuel Barrett and Peter Stone
Approximately Orchestrated Routing and Transportation Analyzer: Large-scale Traffic Simulation for Autonomous Vehicles 2012
Dustin Carlino and Mike Depinet and Piyush Khandelwal and Peter Stone
Design and Optimization of an Omnidirectional Humanoid Walk: A Winning Approach at the {R}obo{C}up 2011 3{D} Simulation Competition 2012
Patrick MacAlpine and Samuel Barrett and Daniel Urieli and Victor Vu and Peter Stone
Evasion Planning for Autonomous Vehicles at Intersections 2012
Tsz-Chiu Au and Chien-Liang Fok and Sriram Vishwanath and Christine Julien and Peter Stone
How Humans Teach Agents: A New Experimental Perspective 2012
W. Bradley Knox and Brian D. Glass and Bradley C. Love and W. Todd Maddox and Peter Stone
HyperNEAT-GGP: A HyperNEAT-based Atari General Game Player 2012
Matthew Hausknecht, Piyush Khandelwal, Risto Miikkulainen, Peter Stone
Intrinsically Motivated Model Learning for a Developing Curious Agent 2012
Todd Hester and Peter Stone
Intrinsically Motivated Model Learning for a Developing Curious Agent 2012
Todd Hester and Peter Stone
Leading Ad Hoc Agents in Joint Action Settings with Multiple Teammates 2012
Noa Agmon and Peter Stone
Learning from feedback on actions past and intended 2012
W. Bradley Knox and Cynthia Breazeal and Peter Stone
Learning Teammate Models for Ad Hoc Teamwork 2012
Samuel Barrett and Peter Stone and Sarit Kraus and Avi Rosenfeld
On Coordination in Practical Multi-Robot Patrol 2012
Noa Agmon and Chien-Liang Fok and Yehuda Emaliah and Peter Stone and Christine Julien and Sriram Vishwanath
PAC Subset Selection in Stochastioc Multi-armed Bandits 2012
Shivaram Kalyanakrishnan and Ambuj Tewari and Peter Auer and Peter Stone
Reinforcement Learning from Human Reward: Discounting in Episodic Tasks 2012
W. Bradley Knox and Peter Stone
Reinforcement Learning with Human and MDP Reward 2012
W. Bradley Knox and Peter Stone
Role Selection in Ad Hoc Teamwork 2012
Katie Genter and Noa Agmon and Peter Stone
Setpoint Scheduling for Autonomous Vehicle Controllers 2012
Tsz-Chiu Au and Michael Quinlan and Peter Stone
The Nature of Belief-Directed Exploratory Choice in Human Decision-Making 2012
W. Bradley Knox and A. Ross Otto and Peter Stone and Bradley Love
Using a million cell simulation of the cerebellum: Network scaling and task generality 2012
Wen-Ke Li and Matthew J. Hausknecht and Peter Stone and Michael D. Mauk
Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk 2012
Patrick MacAlpine and Peter Stone
{A}ustin {V}illa 2011: Sharing is Caring: Better Awareness through Information Sharing 2012
Samuel Barrett and Katie Genter and Todd Hester and Piyush Khandelwal and Michael Quinlan and Peter Stone and Mohan Sridharan
{RTMBA}: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control 2012
Todd Hester and Michael Quinlan and Peter Stone
{TEXPLORE}: Real-Time Sample-Efficient Reinforcement Learning for Robots 2012
Todd Hester and Peter Stone
{UT} {A}ustin {V}illa 2011: A Champion Agent in the {R}obo{C}up 3{D} Soccer Simulation Competition 2012
Patrick MacAlpine and Daniel Urieli and Samuel Barrett and Shivaram Kalyanakrishnan and Francisco Barrera and Adrian Lopez-Mobilia and Nicolae Stiurca and Victor Vu and Peter Stone
{W}right {E}agle and {UT} {A}ustin {V}illa: {R}obo{C}up 2011 Simulation League Champions 2012
Aijun Bai and Xiaoping Chen and Patrick MacAlpine and Daniel Urieli and Samuel Barrett and Peter Stone
A Low Cost Ground Truth Detection System Using the Kinect 2011
Piyush Khandelwal and Peter Stone
A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations 2011
David Pardoe and Peter Stone
A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control 2011
Todd Hester and Michael Quinlan and Peter Stone
Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards 2011
Samuel Barrett and Peter Stone
An Introduction to Inter-task Transfer for Reinforcement Learning 2011
Matthew E. Taylor and Peter Stone
Austin Villa 2010 Standard Platform Team Report 2011
Samuel Barrett and Katie Genter and Matthew Hausknecht and Todd Hester and Piyush Khandelwal and Juhyun Lee and Michael Quinlan and Aibo Tian and Peter Stone and Mohan Sridharan
Autonomous Intersection Management: Multi-Intersection Optimization 2011
Matthew Hausknecht and Tsz-Chiu Au and Peter Stone
Characterizing Reinforcement Learning Methods through Parameterized Learning Problems 2011
Shivaram Kalyanakrishnan and Peter Stone
Comparing Agents: Success against People in Security Domains 2011
Raz Lin and Sarit Kraus and Noa Agmon and Samuel Barrett and Peter Stone
Dynamic Lane Reversal in Traffic Management 2011
Matthew Hausknecht and Tsz-Chiu Au and Peter Stone and David Fajardo and Travis Waller
Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain 2011
Samuel Barrett and Peter Stone and Sarit Kraus
Empowerment for Continuous Agent-Environment Systems 2011
Tobias Jung and Daniel Polani and Peter Stone
Enforcing Liveness in Autonomous Traffic Management 2011
Tsz-Chiu Au and Neda Shahidi and Peter Stone
Flood Disaster Mitigation: A Real-world Challenge Problem for Multi-Agent Unmanned Surface Vehicles 2011
Paul Scerri and Balajee Kannan and Pras Velagapudi and Kate Macarthur and Peter Stone and Matthew E. Taylor and John Dolan and Alessandro Farinelli and Archie Chapman and Bernadine Dias and George Kantor
Learning and Using Models 2011
Todd Hester and Peter Stone
Multiagent Patrol Generalized to Complex Environmental Conditions 2011
Noa Agmon and Daniel Urieli and Peter Stone
On Learning with Imperfect Representations 2011
Shivaram Kalyanakrishnan and Peter Stone
On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer 2011
Daniel Urieli and Patrick MacAlpine and Shivaram Kalyanakrishnan and Yinon Bentor and Peter Stone
Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning 2011
Shimon Whiteson and Brian Tanner and Matthew E. Taylor and Peter Stone
Role-Based Ad Hoc Teamwork 2011
Katie Genter and Noa Agmon and Peter Stone
Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree 2011
Doran Chakraborty and Peter Stone
Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report 2011
W. Bradley Knox and Peter Stone
{UT} {A}ustin {V}illa 2011 3{D} {S}imulation {T}eam Report 2011
Patrick MacAlpine and Daniel Urieli and Samuel Barrett and Shivaram Kalyanakrishnan and Francisco Barrera and Adrian Lopez-Mobilia and Nicolae Stiurca and Victor Vu and Peter Stone
A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations 2010
David Pardoe and Peter Stone
Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge 2010
David Pardoe and Peter Stone and Maytal Saar-Tsechansky and Tayfun Keskin and Kerem Tomak
Boosting for Regression Transfer 2010
David Pardoe and Peter Stone
Bringing Simulation to Life: A Mixed Reality Autonomous Intersection 2010
Michael Quinlan and Tsz-Chiu Au and Jesse Zhu and Nicolae Stiurca and Peter Stone
Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning 2010
W. Bradley Knox and Peter Stone
Controlled Kicking under Uncertainty 2010
Samuel Barrett and Katie Genter and Todd Hester and Michael Quinlan and Peter Stone
Convergence, Targeted Optimality and Safety in Multiagent Learning 2010
Doran Chakraborty and Peter Stone
Efficient Selection of Multiple Bandit Arms: Theory and Practice 2010
Shivaram Kalyanakrishnan and Peter Stone
Gaussian processes for sample efficient reinforcement learning with RMAX-like exploration 2010
Tobias Jung and Peter Stone
Generalized Model Learning for Reinforcement Learning on a Humanoid Robot 2010
Todd Hester and Michael Quinlan and Peter Stone
Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker 2010
Matthew Hausknecht and Peter Stone
MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training 2010
Adam Setapen and Michael Quinlan and Peter Stone
Motion Planning Algorithms for Autonomous Intersection Management 2010
Tsz-Chiu Au and Peter Stone
Online Model Learning in Adversarial Markov Decision Processes (Extended Abstract) 2010
Doran Chakraborty and Peter Stone
Optimizing Interdependent Skills for Simulated 3D Humanoid Robot Soccer 2010
Daniel Urieli and Patrick MacAlpine and Shivaram Kalyanakrishnan and Yinon Bentor and Peter Stone
Real Time Targeted Exploration in Large Domains 2010
Todd Hester and Peter Stone
TacTex09: A Champion Bidding Agent for Ad Auctions 2010
David Pardoe and Doran Chakraborty and Peter Stone
Transfer Learning for Reinforcement Learning on a Physical Robot 2010
Samuel Barrett and Matthew E. Taylor and Peter Stone
Vision Calibration and Processing on a Humanoid Soccer Robot 2010
Piyush Khandelwal and Matthew Hausknecht and Juhyun Lee and Aibo Tian and Peter Stone
An Empirical Analysis of Value Function-Based and Policy Search Reinforcement Learning 2009
Shivaram Kalyanakrishnan and Peter Stone
An Empirical Comparison of Abstraction in Models of Markov Decision Processes 2009
Todd Hester and Peter Stone
Color Learning and Illumination Invariance on Mobile Robots: A Survey 2009
Mohan Sridharan and Peter Stone
Compositional Models for Reinforcement Learning 2009
Nicholas K. Jong and Peter Stone
Connectivity-based Localization in Robot Networks 2009
Tobias Jung and Mazda Ahmadi and Peter Stone
Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning 2009
Shimon Whiteson and Matthew E. Taylor and Peter Stone
Design Principles for Creating Human-Shapable Agents 2009
W. Bradley Knox and Ian Fasel and Peter Stone
Feature Selection for Value Function Approximation Using Bayesian Model Selection 2009
Tobias Jung and Peter Stone
Generalized Domains for Empirical Evaluations in Reinforcement Learning 2009
Shimon Whiteson and Brian Tanner and Matthew E. Taylor and Peter Stone
Generalized Model Learning for Reinforcement Learning in Factored Domains 2009
Todd Hester and Peter Stone
Improving Particle Filter Performance Using SSE Instructions 2009
Peter Djeu and Michael Quinlan and Peter Stone
Interactively Shaping Agents via Human Reinforcement: The TAMER Framework 2009
W. Bradley Knox and Peter Stone
Leading a Best-Response Teammate in an Ad Hoc Team 2009
Peter Stone and Gal A. Kaminka and Jeffrey S. Rosenschein
Learning Complementary Multiagent Behaviors: A Case Study 2009
Shivaram Kalyanakrishnan and Peter Stone
The UT Austin Villa 3D Simulation Soccer Team 2008 2009
Shivaram Kalyanakrishnan and Yinon Bentor and Peter Stone
Three Humanoid Soccer Platforms: Comparison and Synthesis 2009
Shivaram Kalyanakrishnan and Todd Hester and Michael Quinlan and Yinon Bentor and Peter Stone
Transfer Learning for Reinforcement Learning Domains: A Survey 2009
Matthew E. Taylor and Peter Stone
TT-UT Austin Villa 2009: Naos across Texas 2009
Todd Hester and Michael Quinlan and Peter Stone and Mohan Sridharan
A General Purpose Task Specification Language for Bootstrap Learning 2008
Ian Fasel and Michael Quinlan and Peter Stone
A Multiagent Approach to Autonomous Intersection Management 2008
Kurt Dresner and Peter Stone
A Neural Network-Based Approach to Robot Motion Control 2008
Uli Grasemann and Daniel Stronger and Peter Stone
Autonomous Transfer for Reinforcement Learning 2008
Matthew E. Taylor and Gregory Kuhlmann and Peter Stone
Hierarchical Model-Based Reinforcement Learning: Rmax + MAXQ 2008
Nicholas K. Jong and Peter Stone
Instance-Based Action Models for Fast Action Planning 2008
Mazda Ahmadi and Peter Stone
Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting 2008
Juhyun Lee and W. Bradley Knox and Peter Stone
Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot 2008
Daniel Stronger and Peter Stone
Mitigating Catastrophic Failure at Intersections of Autonomous Vehicles 2008
Kurt Dresner and Peter Stone
Model-based Reinforcement Learning in a Complex Domain 2008
Shivaram Kalyanakrishnan and Peter Stone and Yaxin Liu
Multiagent Interactions in Urban Driving 2008
Patrick Beeson and Jack O'Quin and Bartley Gillan and Tarun Nimmagadda and Mickey Ristroph and David Li and Peter Stone
Negative Information and Line Observations for Monte Carlo Localization 2008
Todd Hester and Peter Stone
Online Kernel Selection for Bayesian Reinforcement Learning 2008
Joseph Reisinger and Peter Stone and Risto Miikkulainen
Online Multiagent Learning against Memory Bounded Adversaries 2008
Doran Chakraborty and Peter Stone
Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents 2008
Daniel Stronger and Peter Stone
Replacing the Stop Sign: Unmanaged Intersection Control for Autonomous Vehicles 2008
Mark VanMiddlesworth and Kurt Dresner and Peter Stone
The 2007 TAC SCM Prediction Challenge 2008
David Pardoe and Peter Stone
The Utility of Temporal Abstraction in Reinforcement Learning 2008
Nicholas K. Jong and Todd Hester and Peter Stone
Transfer Learning and Intelligence: an Argument and Approach 2008
Matthew E. Taylor and Gregory Kuhlmann and Peter Stone
Transferring Instances for Model-Based Reinforcement Learning 2008
Matthew E. Taylor and Nicholas K. Jong and Peter Stone
UT Austin Villa 2008: Standing on Two Legs 2008
Todd Hester, Michael Quinlan, and Peter Stone
A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot 2007
Daniel Stronger and Peter Stone
Accelerating Search with Transferred Heuristics 2007
Matthew E. Taylor and Gregory Kuhlmann and Peter Stone
Action Selection for Illumination Invariant Color Learning 2007
Mohan Sridharan and Peter Stone
Adapting Price Predictions in TAC SCM 2007
David Pardoe and Peter Stone
Adaptive Tile Coding for Value Function Approximation 2007
Shimon Whiteson and Matthew E. Taylor and Peter Stone
An Autonomous Agent for Supply Chain Management 2007
David Pardoe and Peter Stone
Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition 2007
Michael P. Wellman and Amy Greenwald and Peter Stone
Autonomous Learning of Stable Quadruped Locomotion 2007
Manish Saggar and Thomas D'Silva and Nate Kohl and Peter Stone
Autonomous Return on Investment Analysis of Additional Processing Resources 2007
Jonathan Wildstrom and Peter Stone and Emmett Witchel
Batch Reinforcement Learning in a Complex Domain 2007
Shivaram Kalyanakrishnan and Peter Stone
Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination 2007
Mohan Sridharan and Peter Stone
Cross-Domain Transfer for Reinforcement Learning 2007
Matthew E. Taylor and Peter Stone
DARPA Urban Challenge Technical Report: Austin Robot Technology 2007
Peter Stone and Patrick Beeson and Tekin Mericli and Ryan Madigan
Empirical Studies in Action Selection for Reinforcement Learning 2007
Shimon Whiteson and Matthew E. Taylor and Peter Stone
General Game Learning using Knowledge Transfer 2007
Bikramjit Banerjee and Peter Stone
Graph-Based Domain Mapping for Transfer Learning in General Games 2007
Gregory Kuhlmann and Peter Stone
Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study 2007
Shivaram Kalyanakrishnan and Yaxin Liu and Peter Stone
IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks 2007
Mazda Ahmadi and Matthew E. Taylor and Peter Stone
Intelligent Autonomous Robotics: A Robot Soccer Case Study 2007
Peter Stone
Learning and Multiagent Reasoning for Autonomous Agents 2007
Peter Stone
Learning Policy Selection for Autonomous Intersection Management 2007
Kurt Dresner and Peter Stone
Machine Learning for On-Line Hardware Reconfiguration 2007
Jonathan Wildstrom and Peter Stone and Emmett Witchel and Mike Dahlin
Model-Based Exploration in Continuous State Spaces 2007
Nicholas K. Jong and Peter Stone
Model-Based Function Approximation for Reinforcement Learning 2007
Nicholas K. Jong and Peter Stone
Multiagent learning is not the answer. It is the question 2007
Peter Stone
Planning Actions to Enable Color Learning on a Mobile Robot 2007
Mohan Sridharan and Peter Stone
Representation Transfer for Reinforcement Learning 2007
Matthew E. Taylor and Peter Stone
Selective Visual Attention for Object Detection on a Legged Robot 2007
Daniel Stronger and Peter Stone
Sharing the Road: Autonomous Vehicles meet Human Drivers 2007
Kurt Dresner and Peter Stone
Structure Based Color Learning on a Mobile Robot under Changing Illumination 2007
Mohan Sridharan and Peter Stone
Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison 2007
Matthew E. Taylor and Shimon Whiteson and Peter Stone
The Chin Pinch: A Case Study in Skill Learning on a Legged Robot 2007
Peggy Fidelman and Peter Stone
The UT Austin Villa 3D Simulation Soccer Team 2007 2007
Shivaram Kalyanakrishnan and Peter Stone
Transfer Learning via Inter-Task Mappings for Temporal Difference Learning 2007
Matthew E. Taylor and Peter Stone and Yaxin Liu
Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning 2007
Matthew E. Taylor and Shimon Whiteson and Peter Stone
A Multi-Robot System for Continuous Area Sweeping Tasks 2006
Mazda Ahmadi and Peter Stone
Adapting to Workload Changes Through On-The-Fly Reconfiguration 2006
Jonathan Wildstrom and Peter Stone and Emmett Witchel and Mike Dahlin
Adaptive Mechanism Design: A Metalearning Approach 2006
David Pardoe and Peter Stone and Maytal Saar-Tsechansky and Kerem Tomak
Automatic Heuristic Construction in a Complete General Game Player 2006
Gregory Kuhlmann and Kurt Dresner and Peter Stone
Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data 2006
Mohan Sridharan and Peter Stone
Cobot in LambdaMOO: An Adaptive Social Statistics Agent 2006
Charles Lee Isbell and Michael Kearns and Satinder Singh and Christian Shelton and Peter Stone and Dave Kormann
Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning 2006
Matthew Taylor and Shimon Whiteson and Peter Stone
Designing Safe, Profitable Automated Stock Trading Agents Using Evolutionary Algorithms 2006
Harish Subramanian and Subramanian Ramamoorthy and Peter Stone and Benjamin Kuipers
Evolutionary Function Approximation for Reinforcement Learning 2006
Shimon Whiteson and Peter Stone
From Pixels to Multi-Robot Decision-Making: A Study in Uncertainty 2006
Peter Stone and Mohan Sridharan and Daniel Stronger and Gregory Kuhlmann and Nate Kohl and Peggy Fidelman and Nicholas K. Jong
Human-Usable and Emergency Vehicle-Aware Control Policies for Autonomous Intersection Management 2006
Kurt Dresner and Peter Stone
Keepaway Soccer: From Machine Learning Testbed to Benchmark 2006
Peter Stone and Gregory Kuhlmann and Matthew E. Taylor and Yaxin Liu
Keeping in Touch: Maintaining Biconnected Structure by Homogeneous Robots 2006
Mazda Ahmadi and Peter Stone
Know Thine Enemy: A Champion RoboCup Coach Agent 2006
Gregory Kuhlmann and William B. Knox and Peter Stone
Multiagent Traffic Management: Opportunities for Multiagent Learning 2006
Kurt Dresner and Peter Stone
On-Line Evolutionary Computation for Reinforcement Learning in Stochastic Domains 2006
Shimon Whiteson and Peter Stone
Predictive Planning for Supply Chain Management 2006
David Pardoe and Peter Stone
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning 2006
Shimon Whiteson and Peter Stone
TacTex-2005: A Champion Supply Chain Management Agent 2006
David Pardoe and Peter Stone
The UT Austin Villa 2006 RoboCup Four-Legged Team 2006
Peter Stone and Peggy Fidelman and Nate Kohl and Gregory Kuhlmann and Tekin Mericli and Mohan Sridharan and Shao-en Yu
Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot 2006
Daniel Stronger and Peter Stone
Value Function Transfer for General Game Playing 2006
Bikramjit Banerjee and Gregory Kuhlmann and Peter Stone
Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping 2006
Yaxin Liu and Peter Stone
A Model-Based Approach to Robot Joint Control 2005
Daniel Stronger and Peter Stone
A Polynomial-time Nash Equilibrium Algorithm for Repeated Games 2005
Michael L. Littman and Peter Stone
Automatic Feature Selection via Neuroevolution 2005
Shimon Whiteson and Peter Stone and Kenneth O. Stanley and Risto Miikkulainen and Nate Kohl
Autonomous Color Learning on a Mobile Robot 2005
Mohan Sridharan and Peter Stone
Bayesian Models of Nonstationary Markov Decision Problems 2005
Nicholas K. Jong and Peter Stone
Behavior Transfer for Value-Function-Based Reinforcement Learning 2005
Matthew E. Taylor and Peter Stone
Bidding for Customer Orders in TAC SCM 2005
David Pardoe and Peter Stone
Continuous Area Sweeping: A Task Definition and Initial Approach 2005
Mazda Ahmadi and Peter Stone
Developing Adaptive Auction Mechanisms 2005
David Pardoe and Peter Stone
Evolving Keepaway Soccer Players through Task Decomposition 2005
Shimon Whiteson and Nate Kohl and Risto Miikkulainen and Peter Stone
Function Approximation via Tile Coding: Automating Parameter Choice 2005
Alexander A. Sherstov and Peter Stone
Improving Action Selection in MDP's via Knowledge Transfer 2005
Alexander A. Sherstov and Peter Stone
Multiagent Traffic Management: An Improved Intersection Control Mechanism 2005
Kurt Dresner and Peter Stone
Practical Vision-Based Monte Carlo Localization on a Legged Robot 2005
Mohan Sridharan and Gregory Kuhlmann and Peter Stone
Real-Time Vision on a Mobile Robot Platform 2005
Mohan Sridharan and Peter Stone
Reinforcement Learning for RoboCup-Soccer Keepaway 2005
Peter Stone and Richard S. Sutton and Gregory Kuhlmann
State Abstraction Discovery from Irrelevant State Variables 2005
Nicholas K. Jong and Peter Stone
The First International Trading Agent Competition: Autonomous Bidding Agents 2005
Peter Stone and Amy Greenwald
The UT Austin Villa 2003 Champion Simulator Coach: A Machine Learning Approach 2005
Gregory Kuhlmann and Peter Stone and Justin Lallinger
The UT Austin Villa 2005 RoboCup Four-Legged Team 2005
Peter Stone and Kurt Dresner and Peggy Fidelman and Nate Kohl and Gregory Kuhlmann and Mohan Sridharan and Daniel Stronger
Three Automated Stock-Trading Agents: A Comparative Study 2005
Alexander Sherstov and Peter Stone
Towards Illumination Invariance in the Legged League 2005
Mohan Sridharan and Peter Stone
Towards Self-Configuring Hardware for Distributed Computer Systems 2005
Jonathan Wildstrom, Peter Stone, E. Witchel, Raymond Mooney and M. Dahlin
Value Functions for RL-Based Behavior Transfer: A Comparative Study 2005
Matthew E. Taylor and Peter Stone and Yaxin Liu
Adaptive Job Routing and Scheduling 2004
Shimon Whiteson and Peter Stone
Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer 2004
Gregory Kuhlmann, Peter Stone, Raymond J. Mooney, and Jude W. Shavlik
Learning Ball Acquisition on a Physical Robot 2004
Peggy Fidelman and Peter Stone
Machine Learning for Fast Quadrupedal Locomotion 2004
Nate Kohl and Peter Stone
Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism 2004
Kurt Dresner and Peter Stone
Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion 2004
Nate Kohl and Peter Stone
RoboCup as an Introduction to CS Research 2004
Peter Stone
TacTex-03: A Supply Chain Management Agent 2004
David Pardoe and Peter Stone
The Champion UT Austin Villa 2003 Simulator Online Coach Team 2004
Gregory Kuhlmann and Peter Stone and Justin Lallinger
The UT Austin Villa 2003 Four-Legged Team 2004
Peter Stone and Kurt Dresner and Selim T. Erdougan and Peggy Fidelman and Nicholas K. Jong and Nate Kohl and Gregory Kuhlmann and Ellie Lin and Mohan Sridharan and Daniel Stronger and Gurushyam Hariharan
The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age 2004
Peter Stone and Kurt Dresner and Peggy Fidelman and Nicholas K. Jong and Nate Kohl and Gregory Kuhlmann and Mohan Sridharan and Daniel Stronger
Towards Employing PSRs in a Continuous Domain 2004
Nicholas K. Jong and Peter Stone
Towards Learning to Ignore Irrelevant State Variables 2004
Nicholas K. Jong and Peter Stone
Two Stock-Trading Agents: Market Making and Technical Analysis 2004
Yi Feng and Ronggang Yu and Peter Stone
Using RoboCup in university-level computer science education 2004
Elizabeth Sklar and Simon Parsons and Peter Stone
Concurrent Layered Learning 2003
Shimon Whiteson and Peter Stone
Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions 2003
Peter Stone and Robert E. Schapire and Michael L. Littman and J'anos A. Csirik and David McAllester
Guest Editors' Introduction: Agents and Markets 2003
Amy Greenwald and Nicholas R. Jennings and Peter Stone
Learning Predictive State Representations 2003
Satinder Singh and Michael L. Littman and Nicholas K. Jong and David Pardoe and Peter Stone
Multiagent Competitions and Research: Lessons from RoboCup and TAC 2003
Peter Stone
Performance Analysis of a Counter-intuitive Automated Stock-Trading Strategy 2003
Ronggang Yu and Peter Stone
The 2001 Trading Agent Competition 2003
Michael P. Wellman and Amy Greenwald and Peter Stone and Peter R. Wurman
The RoboCup Soccer Server and CMUnited Clients: Implemented Infrastructure for MAS Research 2003
Itsuki Noda and Peter Stone
ATTUnited-2001: Using Heterogeneous Players 2002
Peter Stone
Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation 2002
Robert E. Schapire and Peter Stone and David McAllester and Michael L. Littman and J'anos A. Csirik
Self-enforcing Strategic Demand Reduction 2002
Paul S. A. Reitsma and Peter Stone and J'anos A. Csirik and Michael L. Littman
A Social Reinforcement Learning Agent 2001
Charles Lee Isbell and Christian R. Shelton and Michael Kearns and Satinder Singh and Peter Stone
An Architecture for Action Selection in Robotic Soccer 2001
Peter Stone and David McAllester
ATT-CMUnited-2000: Third Place Finisher in the RoboCup-2000 Simulator League 2001
Patrick Riley and Peter Stone and David McAllester and Manuela Veloso
ATTac-2000: An Adaptive Autonomous Bidding Agent 2001
Peter Stone and Michael L. Littman and Satinder Singh and Michael Kearns
Autonomous Bidding Agents in the Trading Agent Competition 2001
Amy Greenwald and Peter Stone
Cobot in LambdaMOO: A Social Statistics Agent 2001
Charles Lee Isbell Jr. and Michael Kearns and Dave Kormann and Satinder Singh and Peter Stone
FAucS: An FCC Spectrum Auction Simulator for Autonomous Bidding Agents 2001
J'anos A. Csirik and Michael L. Littman and Satinder Singh and Peter Stone
Implicit Negotiation in Repeated Games 2001
Michael L. Littman and Peter Stone
Keeping the Ball from CMUnited-99 2001
David McAllester and Peter Stone
Layered Disclosure: Revealing Agents' Internals 2001
Patrick Riley and Peter Stone and Manuela Veloso
RoboCup-2000: The Fourth Robotic Soccer World Championships 2001
Peter Stone and Minoru Asada and Tucker Balch and Raffaelo D'Andrea and Masahiro Fujita and Bernhard Hengst and Gerhard Kraetzschmar and Pedro Lima and Nuno Lau and Henrik Lund and Daniel Polani and Paul Scerri and Satoshi Tadokoro and Thilo Weigel and Gordon Wyeth
Defining and Using Ideal Teammate and Opponent Models 2000
Peter Stone and Patrick Riley and Manuela Veloso
Layered Learning 2000
Peter Stone and Manuela Veloso
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
Overview of RoboCup-99 2000
Silvia Coradeschi and Lars Karlsson and Peter Stone and Tucker Balch and Gerhard Kraetzschmar and Minoru Asada
The CMUnited-97 Robotic Soccer Team: Perception and Multi-agent Control 2000
Manuela Veloso and Peter Stone and Kwun Han
The CMUnited-99 Champion Simulator Team 2000
Peter Stone and Patrick Riley and Manuela Veloso
TPOT-RL Applied to Network Routing 2000
Peter Stone
Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer 1999
Manuela Veloso and Peter Stone and Michael Bowling
Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork 1999
Peter Stone and Manuela Veloso
Team-Partitioned, Opaque-Transition Reinforcement Learning 1999
Peter Stone and Manuela Veloso
The CMUnited-98 Champion Simulator Team 1999
Peter Stone and Manuela Veloso and Patrick Riley
The CMUnited-98 Champion Small Robot Team 1999
Manuela Veloso and Michael Bowling and Sorin Achim and Kwun Han and Peter Stone
A Layered Approach to Learning Client Behaviors in the RoboCup Soccer Server 1998
Peter Stone and Manuela Veloso
The CMUnited-97 Simulator Team 1998
Peter Stone and Manuela Veloso
The CMUnited-97 Small-Robot Team 1998
Manuela Veloso and Peter Stone and Kwun Han and Sorin Achim
The RoboCup Physical Agent Challenge: Phase-I 1998
Minoru Asada and Yasuo Kuniyoshi and Alexis Drogoul and Hajime Asama and Maja Mataric and Dominique Duhaut and Peter Stone and Hiroaki Kitano
Towards Collaborative and Adversarial Learning: A Case Study in Robotic Soccer 1998
Peter Stone and Manuela Veloso
Using Decision Tree Confidence Factors for Multiagent Control 1998
Peter Stone and Manuela Veloso
Interactive, Repair-Based Planning and Scheduling for Shuttle Payload Operations 1997
Gregg Rabideau and Steve Chien and Peter Stone and Jason Willis and Curt Eggemeyer and Tobias Mann
The RoboCup Synthetic Agent Challenge 97 1997
Hiroaki Kitano and Milind Tambe and Peter Stone and Manuela Veloso and Silvia Coradeschi and Eiichi Osawa and Hitoshi Matsubara and Itsuki Noda and Minoru Asada
Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function 1996
Peter Stone and Manuela Veloso
Building a Dedicated Robotic Soccer System 1996
Sorin Achim and Peter Stone and Manuela Veloso
Predictive Memory for an Inaccessible Environment 1996
Mike Bowling and Peter Stone and Manuela Veloso
User-guided Interleaving of Planning and Execution 1996
Peter Stone and Manuela Veloso
FLECS: Planning with a Flexible Commitment Strategy 1995
Manuela Veloso and Peter Stone
Using Testing to Iteratively Improve Training 1995
Peter Stone and Manuela Veloso
Learning to Solve Complex Planning Problems: Finding Useful Auxiliary Problems 1994
Peter Stone and Manuela Veloso
The need for different domain-independent heuristics 1994
Peter Stone and Manuela Veloso and Jim Blythe
Projects
TEXPLORE: Real-Time Sample Efficient Reinforcement Learning 2009 - Present
Teaching an Agent Manually via Evaluative Reinforcement (TAMER) 2008 - Present
Autonomous Intersection Management (AIM) 2004 - Present
AIM: Autonomous Intersection Management 2003 - Present
Autonomic computing 2003 - Present
TacTex, an autonomous bidding agent for the Trading Agent Competition 2003 - Present
The UT Austin Villa Robot Soccer team 2003 - Present
Areas of Interest
Reinforcement Learning Robotics Planning Multiagent Systems Autonomic Computing Trading Agents Robot Soccer Transfer Learning Machine Learning Autonomous Traffic Management Game Theory General Game Playing Layered Learning Markov Decision Processes Predictive State Representations Multi-Robot Systems Agent Modeling in Multiagent Systems Social Agents Autonomous Driving Quadruped Robots Humanoid Robots Real Robot Soccer RoboCup Simulated Robot Soccer Robot Vision Auctions Mechanism Design for Trading Agents Supply Chain Management for Trading Agents
Software/Data
TacTex AA Binary The binary version of our 2009 TacTex AA agent, along with many other teams' agents, are available at the ... 2009
TacTex SCM Binaries Binary versions of all TacTex SCM (2005-2008) agents, along with many other teams' agents, are available at the ... 2008
Keepaway player framework source code, version 0.6 The Keepaway player framework is an implementation of all the low- and mid-level keepaway behaviors described in the pub...
Demos
TEXPLORE: Real-Time Sample Efficient Reinforcement LearningTodd Hester2012
Teaching an Agent Manually via Evaluative Reinforcement (TAMER)W. Bradley Knox and Peter Stone2009
SPL Robocup Soccer2008
Simulated RoboCup Soccer2004
Autonomous Intersection Management (AIM)
Labs
Learning Agents