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Learning Agents
Webpage:
http://www.cs.utexas.edu/users/pstone/
Director:
Peter Stone
The learning agents research group is led by Prof. Peter Stone. Our aim is to understand how we can best create complete intelligent agents. We consider both adaptation and interaction to be essential capabilites of such agents. Thus, our research focuses mainly on machine learning, multiagent systems, and robotics. Application domains include robot soccer, autonomous bidding agents, traffic management, and autonomic computing.
People
Samuel Barrett
Ph.D. Student
sbarrett@cs.utexas.edu
Craig Corcoran
Ph.D. Student
ccor@cs.utexas.edu
Katie Genter
Ph.D. Student
katie@cs.utexas.edu
Matthew Hausknecht
Ph.D. Student
mhauskn@cs.utexas.edu
Piyush Khandelwal
Ph.D. Student
piyushk@cs.utexas.edu
Patrick MacAlpine
Ph.D. Student
patmac@cs.utexas.edu
Peter Stone
Professor
pstone@cs.utexas.edu
Daniel Urieli
Ph.D. Student
urieli@cs.utexas.edu
Show Alumni
Alumni
[Expand to show all 20]
[Minimize]
Noa Agmon
Alumni
agmon@cs.biu.ac.il
Tsz-Chiu Au
Alumni
chiu@cs.utexas.edu
Patrick Beeson
Alumni
pbeeson@traclabs.com
Doran Chakraborty
Alumni
chakrado@cs.utexas.edu
Kurt Dresner
Alumni
kurt@dresner.name
Ian Fasel
Alumni
ianfasel@cs.utexas.edu
Todd Hester
Ph.D. Student (Alumni)
todd@cs.utexas.edu
Nicholas Jong
Alumni
nickjong@me.com
Tobias Jung
Alumni
tjung@ulg.ac.be
Shivaram Kalyanakrishnan
Alumni
shivaram@cs.utexas.edu
W. Bradley Knox
Ph.D. Student (Alumni)
bradknox@mit.edu
Gregory Kuhlmann
Alumni
kuhlmann@cs.utexas.edu
Juhyun Lee
Alumni
impjdi@gmail.com
David Pardoe
Alumni
dpardoe@cs.utexas.edu
Michael Quinlan
Alumni
mquinlan@cs.utexas.edu
Adam Setapen
Masters Student (Alumni)
asetapen@cs.utexas.edu
Mohan Sridharan
Alumni
mhnsrdhrn@gmail.com
Daniel Stronger
Alumni
dan.stronger@gmail.com
Matthew Taylor
Alumni
taylorm@eecs.wsu.edu
Shimon Whiteson
Alumni
s.a.whiteson@uva.nl
Publications
[Expand to show all 273]
[Minimize]
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 from Human-Generated Reward
2012
W. Bradley Knox
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
TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains.
2012
Todd Hester
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
Video: RoboCup Robot Soccer History 1997 – 2011
2012
Manuela Veloso and 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
Adaptive Trading Agent Strategies Using Market Experience
2011
David Merrill Pardoe
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
Structured Exploration for Reinforcement Learning
2010
Nicholas Kenneth Jong
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
Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study
2009
W. Bradley Knox and Ole Mengshoel
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
The UT Austin Villa Robot Soccer team
2003 - Present
TacTex, an autonomous bidding agent for the Trading Agent Competition
2003 - Present
AIM: Autonomous Intersection Management
2003 - Present
Autonomic computing
2003 - Present
Areas of Interest
[Expand to show all 30]
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Ad Hoc Teamwork
Agent Modeling in Multiagent Systems
Auctions
Autonomic Computing
Autonomous Driving
Autonomous Traffic Management
Game Theory
General Game Playing
Humanoid Robots
Layered Learning
Machine Learning
Markov Decision Processes
Mechanism Design for Trading Agents
Multi-Robot Systems
Multiagent Systems
Neuroevolution
Planning
Predictive State Representations
Quadruped Robots
Real Robot Soccer
Reinforcement Learning
RoboCup
Robot Soccer
Robot Vision
Robotics
Simulated Robot Soccer
Social Agents
Supply Chain Management for Trading Agents
Trading Agents
Transfer Learning
Demos
TEXPLORE: Real-Time Sample Efficient Reinforcement Learning
Todd Hester
2012
Teaching an Agent Manually via Evaluative Reinforcement (TAMER)
W. Bradley Knox and Peter Stone
2009
SPL Robocup Soccer
2008
Simulated RoboCup Soccer
2004
Autonomous Intersection Management (AIM)
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
TacTex SCM Starter Agent
The purpose of this agent is to serve as a starting point for new participants in the TAC SCM competition. The agent is ...
2006
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...