Know Thine Enemy: A Champion RoboCup Coach Agent. - Gregory Kuhlmann; William B. Knox; Peter Stone 001 (AAAI, 2006)

Person recognition on a Segway Robot: A video of UT Austin Villa Robocup@Home 2007 finals demonstration. - W. Bradley Knox; Juhyun Lee; Peter Stone 001 (ICRA, 2008)

Domestic Interaction on a Segway Base. - W. Bradley Knox; Juhyun Lee; Peter Stone 001 (RoboCup, 2008)

Design Principles for Creating Human-Shapable Agents. - W. Bradley Knox; Ian R. Fasel; Peter Stone 001 (AAAI Spring Symposium: Agents that Learn from Human Teachers, 2009)

Interactively shaping agents via human reinforcement: the TAMER framework. - W. Bradley Knox; Peter Stone 001 (K-CAP, 2009)

Combining manual feedback with subsequent MDP reward signals for reinforcement learning. - W. Bradley Knox; Peter Stone 001 (AAMAS, 2010)

Training a Tetris agent via interactive shaping: a demonstration of the TAMER framework. - W. Bradley Knox; Peter Stone 001 (AAMAS, 2010)

Reinforcement Learning with Human Feedback in Mountain Car. - W. Bradley Knox; Adam Bradley Setapen; Peter Stone 001 (AAAI Spring Symposium: Help Me Help You: Bridging the Gaps in Human-Agent Collaboration, 2011)

Computational, Neuroscientific, and Lifespan Perspectives on the Exploration-Exploitation Dilemma. - A. Ross Otto; W. Bradley Knox; Bradley C. Love; Samuel Gershman; Yael Niv; Darrell A. Worthy; W. Todd Maddox; Jared M. Hotaling; Jerome R. Busemeyer; Richard M. Shiffrin (CogSci, 2011)

Reinforcement learning from simultaneous human and MDP reward. - W. Bradley Knox; Peter Stone 001 (AAMAS, 2012)

Reinforcement learning from human reward: Discounting in episodic tasks. - W. Bradley Knox; Peter Stone 001 (RO-MAN, 2012)

How Humans Teach Agents - A New Experimental Perspective. - W. Bradley Knox; Brian D. Glass; Bradley C. Love; W. Todd Maddox; Peter Stone 001 (Int. J. Soc. Robotics, 2012)

Using informative behavior to increase engagement in the tamer framework. - Guangliang Li; Hayley Hung; Shimon Whiteson; W. Bradley Knox (AAMAS, 2013)

IUI workshop on interactive machine learning. - Saleema Amershi; Maya Cakmak; W. Bradley Knox; Todd Kulesza; Tessa Lau (IUI Companion, 2013)

Learning non-myopically from human-generated reward. - W. Bradley Knox; Peter Stone 001 (IUI, 2013)

Teaching agents with human feedback: a demonstration of the TAMER framework. - W. Bradley Knox; Peter Stone 001; Cynthia Breazeal (IUI Companion, 2013)

Training a Robot via Human Feedback: A Case Study. - W. Bradley Knox; Peter Stone 001; Cynthia Breazeal (ICSR, 2013)

Leveraging social networks to motivate humans to train agents. - Guangliang Li; Hayley Hung; Shimon Whiteson; W. Bradley Knox (AAMAS, 2014)

Learning from human reward benefits from socio-competitive feedback. - Guangliang Li; Hayley Hung; Shimon Whiteson; W. Bradley Knox (ICDL-EPIROB, 2014)

Power to the People: The Role of Humans in Interactive Machine Learning. - Saleema Amershi; Maya Cakmak; W. Bradley Knox; Todd Kulesza (AI Mag., 2014)

Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance. - W. Bradley Knox; Peter Stone 001 (Artif. Intell., 2015)

Learning from the Wizard: Programming Social Interaction through Teleoperated Demonstrations (Extended Abstract). - W. Bradley Knox; Samuel Spaulding; Cynthia Breazeal (AAMAS, 2016)

Using informative behavior to increase engagement while learning from human reward. - Guangliang Li; Shimon Whiteson; W. Bradley Knox; Hayley Hung (Auton. Agents Multi Agent Syst., 2016)

Social interaction for efficient agent learning from human reward. - Guangliang Li; Shimon Whiteson; W. Bradley Knox; Hayley Hung (Auton. Agents Multi Agent Syst., 2018)

The EMPATHIC Framework for Task Learning from Implicit Human Feedback. - Yuchen Cui; Qiping Zhang; W. Bradley Knox; Alessandro Allievi; Peter Stone 001; Scott Niekum (CoRL, 2020)

Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback. - Yuchen Cui; Qiping Zhang; Sahil Jain; Alessandro Allievi; Peter Stone 001; Scott Niekum; W. Bradley Knox (AAAI, 2021)

Toward Believable Acting for Autonomous Animated Characters. - Cassidy J. Curtis; Sigurdur O. Adalgeirsson; Horia Stefan Ciurdar; Peter F. McDermott; J. D. Velásquez; W. Bradley Knox; Alonso Martinez; Dei Gaztelumendi; Norberto Adrián Goussies; Tianyu Liu; Palash Nandy (MIG, 2022)

The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications. - Serena Booth; W. Bradley Knox; Julie Shah; Scott Niekum; Peter Stone 001; Alessandro Allievi (AAAI, 2023)

Contrastive Preference Learning: Learning from Human Feedback without RL. - Joey Hejna; Rafael Rafailov; Harshit Sikchi; Chelsea Finn; Scott Niekum; W. Bradley Knox; Dorsa Sadigh (CoRR, 2023)

Reward (Mis)design for autonomous driving. - W. Bradley Knox; Alessandro Allievi; Holger Banzhaf; Felix Schmitt 001; Peter Stone 001 (Artif. Intell., 2023)

Reward (Mis)design for Autonomous Driving (Abstract Reprint). - W. Bradley Knox; Alessandro Allievi; Holger Banzhaf; Felix Schmitt 001; Peter Stone 001 (AAAI, 2024)

Learning Optimal Advantage from Preferences and Mistaking It for Reward. - W. Bradley Knox; Stephane Hatgis-Kessell; Sigurdur O. Adalgeirsson; Serena Booth; Anca D. Dragan; Peter Stone 001; Scott Niekum (AAAI, 2024)

Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning. - Joey Hejna; Rafael Rafailov; Harshit Sikchi; Chelsea Finn; Scott Niekum; W. Bradley Knox; Dorsa Sadigh (ICLR, 2024)

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. - Rafael Rafailov; Yaswanth Chittepu; Ryan Park; Harshit Sikchi; Joey Hejna; W. Bradley Knox; Chelsea Finn; Scott Niekum (NeurIPS, 2024)

Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions. - Michael J. Q. Zhang; W. Bradley Knox; Eunsol Choi (CoRR, 2024)

MobileSafetyBench: Evaluating Safety of Autonomous Agents in Mobile Device Control. - Juyong Lee; Dongyoon Hahm; June Suk Choi; W. Bradley Knox; Kimin Lee (CoRR, 2024)

Models of human preference for learning reward functions. - W. Bradley Knox; Stephane Hatgis-Kessell; Serena Booth; Scott Niekum; Peter Stone 001; Alessandro Gabriele Allievi (Trans. Mach. Learn. Res., 2024)

Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions. - Michael Jq Zhang; W. Bradley Knox; Eunsol Choi (ICLR, 2025)

Influencing Humans to Conform to Preference Models for RLHF. - Stephane Hatgis-Kessell; W. Bradley Knox; Serena Booth; Scott Niekum; Peter Stone 001 (CoRR, 2025)

Towards Improving Reward Design in RL: A Reward Alignment Metric for RL Practitioners. - Calarina Muslimani; Kerrick Johnstonbaugh; Suyog Chandramouli; Serena Booth; W. Bradley Knox; Matthew E. Taylor (CoRR, 2025)

A Descriptive and Normative Theory of Human Beliefs in RLHF. - Sylee Dandekar; Shripad Deshmukh; Frank Chiu; W. Bradley Knox; Scott Niekum (CoRR, 2025)