Todd Hester
Postdoctoral Alumni, Ph.D. Alumni
Todd's research focused on reinforcement learning and robotics, specifically looking at the exploration versus exploitation problem in reinforcement learning and working to apply it to large domains. Before coming to UT, Todd worked in the Motion Analysis Laboratory at Spaulding Rehabiliation Hospital, Motorola, Sun Microsystems, and the Air Force Research Laboratory. Outside of his research, Todd enjoys ultimate frisbee and foosball and is a dedicated New England Patriots fan.
Homepage:
http://www.cs.utexas.edu/~todd
Publications
     [Expand to show all 24][Minimize]
Intrinsically motivated model learning for developing curious robots 2015
Todd Hester and Peter Stone, Artificial Intelligence (2015). Elsevier.
Learning Exploration Strategies in Model-Based Reinforcement Learning 2013
Todd Hester, Manuel Lopes, and Peter Stone, In The Twelfth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2013.
The 2012 {UT Austin Villa} Code Release 2013
Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone, In {R}obo{C}up-2013: Robot Soccer World Cup {XVII} 2013.
The Open-Source TEXPLORE Code Release for Reinforcement Learning on Robots 2013
Todd Hester and Peter Stone, In RoboCup-2013: Robot Soccer World Cup {XVII}, Sven Behnke and Arnoud Visser and Rong Xiong and Manuela Veloso (Eds.) 2013. Springer Verlag.
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, In RoboCup-2012: Robot Soccer World Cup {XVI}, Xiaoping Chen and Peter Stone and Luis Enrique Sucar and Tijn Van der Zant (Eds.) 2013. Springer Verlag.
Intrinsically Motivated Model Learning for a Developing Curious Agent 2012
Todd Hester and Peter Stone, In Eleventh International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), June 2012.
Intrinsically Motivated Model Learning for a Developing Curious Agent 2012
Todd Hester and Peter Stone, In The Eleventh International Conference on Development and Learning (ICDL), Nov 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.
Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing 2012
Samuel Barrett, Katie Genter, Todd Hester, Piyush Khandelwal, Michael Quinlan, Peter Stone, and Mohan Sridharan, Technical Report, Department of Computer Science, The University of Texas at Austin. Tech Report UT-AI-TR-12-01.
RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control 2012
Todd Hester, Michael Quinlan, and Peter Stone, In {IEEE} International Conference on Robotics and Automation (ICRA), May 2012.
TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots 2012
Todd Hester and Peter Stone, Machine Learning (2012).
A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control 2011
Todd Hester, Michael Quinlan, and Peter Stone, No other information
Austin Villa 2010 Standard Platform Team Report 2011
Samuel Barrett, Katie Genter, Matthew Hausknecht, Todd Hester, Piyush Khandelwal, Juhyun Lee, Michael Quinlan, Aibo Tian, Peter Stone, and Mohan Sridharan, Technical Report, Department of Computer Science, The University of Texas at Austin. Tech Report UT-AI-TR-11-01.
Learning and Using Models 2011
Todd Hester and Peter Stone, In Reinforcement Learning: State of the Art 2011.
Controlled Kicking under Uncertainty 2010
Samuel Barrett, Katie Genter, Todd Hester, Michael Quinlan, and Peter Stone, In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, Nashville, TN 2010.
Generalized Model Learning for Reinforcement Learning on a Humanoid Robot 2010
Todd Hester, Michael Quinlan, and Peter Stone, In International Conference on Robotics and Automation 2010.
Real Time Targeted Exploration in Large Domains 2010
Todd Hester and Peter Stone, In Proceedings of the Ninth International Conference on Development and Learning (ICDL 2010), 2010 (Eds.), August 2010.
An Empirical Comparison of Abstraction in Models of Markov Decision Processes 2009
Todd Hester and Peter Stone, In Proceedings of the ICML/UAI/COLT Workshop on Abstraction in Reinforcement Learning, June 2009.
Generalized Model Learning for Reinforcement Learning in Factored Domains 2009
Todd Hester and Peter Stone, In The Eighth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2009.
Three Humanoid Soccer Platforms: Comparison and Synthesis 2009
Shivaram Kalyanakrishnan, Todd Hester, Michael Quinlan, Yinon Bentor, and Peter Stone, In Proceedings of the RoboCup International Symposium 2009 2009. Springer Verlag.
TT-UT Austin Villa 2009: Naos across Texas 2009
Todd Hester, Michael Quinlan, Peter Stone, and Mohan Sridharan, Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory.
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.
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.
UT Austin Villa 2008: Standing on Two Legs 2008
Todd Hester, Michael Quinlan, and Peter Stone, Technical Report UT-AI-TR-08-8, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Projects
TEXPLORE: Real-Time Sample Efficient Reinforcement Learning 2009 - Present
The UT Austin Villa Robot Soccer team 2003 - Present
Areas of Interest
Real Robot Soccer Reinforcement Learning RoboCup Robot Soccer Robotics
Demos
TEXPLORE: Real-Time Sample Efficient Reinforcement LearningTodd Hester2012
SPL Robocup Soccer2008
Labs
Formerly affiliated with Learning Agents