W. Bradley Knox
Brad, an NSF Graduate Research Fellow, researches how to design agents that can be taught interactively by human reward—somewhat like animal training. The TAMER framework is the result of his efforts. After giving a lot of demos of a trainable Tetris agent, he kept getting called "The Tetris Guy." After defending, Brad joined Cynthia Breazeal's group at the MIT Media Lab as a postdoc, working on the personalization side of an educational robots project. In his free time, Brad runs in "barefoot" sandals, eats tasty trailer food, and tries out his robot training techniques on his dog.
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Reward (Mis)design for autonomous driving W. Bradley Knox and Alessandro Allievi and Holger Banzhaf and Felix Schmitt and Peter Stone Artificial Intelligence, 316, January 2023. 2023

The EMPATHIC Framework for Task Learning from Implicit Human Feedback Yuchen Cui and Qiping Zhang and Alessandro Allievi and Peter Stone and Scott Niekum and W. Bradley K... In Proceedings of the 4th Conference on Robot Learning (CoRL 2020), Cambridge MA, USA, Novemb... 2020

Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance W. Bradley Knox and Peter Stone Artificial Intelligence, 225, August 2015. 2015

Learning Non-Myopically from Human-Generated Reward 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 W. Bradley Knox and Peter Stone and Cynthia Breazeal In Social Robotics, October 2013. 2013

How Humans Teach Agents: A New Experimental Perspective W. Bradley Knox and Brian D. Glass and Bradley C. Love and W. Todd Maddox and Peter Stone International Journal of Social Robotics, 4:409-421, 2012. Springer Netherlands. 2012

Learning from feedback on actions past and intended W. Bradley Knox and Cynthia Breazeal and Peter Stone In In Proceedings of 7th ACM/IEEE International Conference on Human-Robot Interaction, Late-Break... 2012

Learning from Human-Generated Reward W. Bradley Knox %RefShort% 2012

Reinforcement Learning from Human Reward: Discounting in Episodic Tasks W. Bradley Knox and Peter Stone In In Proceedings of the 21st IEEE International Symposium on Robot and Human Interactive Communi... 2012

Reinforcement Learning with Human and MDP Reward W. Bradley Knox and Peter Stone In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (... 2012

The Nature of Belief-Directed Exploratory Choice in Human Decision-Making W. Bradley Knox and A. Ross Otto and Peter Stone and Bradley Love Frontiers in Psychology, 2, 2012. The paper can be accessed at: http://www.frontiersin.org/Jo... 2012

Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report W. Bradley Knox and Peter Stone In IJCAI 2011 Workshop on Agents Learning Interactively from Human Teachers (ALIHT), July 201... 2011

Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning W. Bradley Knox and Peter Stone In Proc. of 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2010), May 2010... 2010

Design Principles for Creating Human-Shapable Agents W. Bradley Knox and Ian Fasel and Peter Stone In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009. 2009

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study W. Bradley Knox and Ole Mengshoel In IJCAI 2009 Workshop on Self-* and Autonomous Systems, 2009. 2009

Interactively Shaping Agents via Human Reinforcement: The TAMER Framework W. Bradley Knox and Peter Stone In The Fifth International Conference on Knowledge Capture, September 2009. 2009

Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting Juhyun Lee and W. Bradley Knox and Peter Stone Journal of Physical Agents, 2(2):41-50, July 2008. Special Issue on Human Interaction with Do... 2008

Know Thine Enemy: A Champion RoboCup Coach Agent Gregory Kuhlmann and William B. Knox and Peter Stone In Proceedings of the Twenty-First National Conference on Artificial Intelligence, 1463-68, J... 2006