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ORCIDW. Bradley Knox
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- affiliation: University of Texas at Austin, USA
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Journal Articles
- 2024
[j7]W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Gabriele Allievi:
Models of human preference for learning reward functions. Trans. Mach. Learn. Res. 2024 (2024)- 2023
- [j6]W. Bradley Knox
, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for autonomous driving. Artif. Intell. 316: 103829 (2023) - 2018
- [j5]Guangliang Li, Shimon Whiteson, W. Bradley Knox, Hayley Hung:
Social interaction for efficient agent learning from human reward. Auton. Agents Multi Agent Syst. 32(1): 1-25 (2018) - 2016
- [j4]Guangliang Li, Shimon Whiteson, W. Bradley Knox, Hayley Hung:
Using informative behavior to increase engagement while learning from human reward. Auton. Agents Multi Agent Syst. 30(5): 826-848 (2016) - 2015
- [j3]W. Bradley Knox, Peter Stone:
Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance. Artif. Intell. 225: 24-50 (2015) - 2014
- [j2]Saleema Amershi, Maya Cakmak, W. Bradley Knox, Todd Kulesza:
Power to the People: The Role of Humans in Interactive Machine Learning. AI Mag. 35(4): 105-120 (2014) - 2012
- [j1]W. Bradley Knox, Brian D. Glass, Bradley C. Love, W. Todd Maddox, Peter Stone:
How Humans Teach Agents - A New Experimental Perspective. Int. J. Soc. Robotics 4(4): 409-421 (2012)
Conference and Workshop Papers
- 2024
- [c26]W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking It for Reward. AAAI 2024: 10066-10073 - [c25]W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for Autonomous Driving (Abstract Reprint). AAAI 2024: 22702 - [c24]Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh:
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning. ICLR 2024 - 2023
- [c23]Serena Booth, W. Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, Alessandro Allievi:
The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications. AAAI 2023: 5920-5929 - 2022
- [c22]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:
Toward Believable Acting for Autonomous Animated Characters. MIG 2022: 1:1-1:15 - 2021
- [c21]Yuchen Cui, Qiping Zhang, Sahil Jain, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox:
Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback. AAAI 2021: 16017-16019 - 2020
- [c20]Yuchen Cui, Qiping Zhang, W. Bradley Knox, Alessandro Allievi, Peter Stone, Scott Niekum:
The EMPATHIC Framework for Task Learning from Implicit Human Feedback. CoRL 2020: 604-626 - 2016
- [c19]W. Bradley Knox, Samuel Spaulding, Cynthia Breazeal:
Learning from the Wizard: Programming Social Interaction through Teleoperated Demonstrations (Extended Abstract). AAMAS 2016: 1309-1310 - 2014
- [c18]Guangliang Li, Hayley Hung, Shimon Whiteson, W. Bradley Knox:
Leveraging social networks to motivate humans to train agents. AAMAS 2014: 1571-1572 - [c17]Guangliang Li, Hayley Hung, Shimon Whiteson, W. Bradley Knox:
Learning from human reward benefits from socio-competitive feedback. ICDL-EPIROB 2014: 93-100 - 2013
- [c16]Guangliang Li, Hayley Hung, Shimon Whiteson, W. Bradley Knox:
Using informative behavior to increase engagement in the tamer framework. AAMAS 2013: 909-916 - [c15]W. Bradley Knox, Peter Stone, Cynthia Breazeal:
Teaching agents with human feedback: a demonstration of the TAMER framework. IUI Companion 2013: 65-66 - [c14]Saleema Amershi, Maya Cakmak, W. Bradley Knox, Todd Kulesza, Tessa Lau:
IUI workshop on interactive machine learning. IUI Companion 2013: 121-124 - [c13]W. Bradley Knox, Peter Stone:
Learning non-myopically from human-generated reward. IUI 2013: 191-202 - [c12]W. Bradley Knox, Peter Stone, Cynthia Breazeal:
Training a Robot via Human Feedback: A Case Study. ICSR 2013: 460-470 - 2012
- [c11]W. Bradley Knox, Peter Stone:
Reinforcement learning from simultaneous human and MDP reward. AAMAS 2012: 475-482 - [c10]W. Bradley Knox, Peter Stone:
Reinforcement learning from human reward: Discounting in episodic tasks. RO-MAN 2012: 878-885 - 2011
- [c9]W. Bradley Knox, Adam Bradley Setapen, Peter Stone:
Reinforcement Learning with Human Feedback in Mountain Car. AAAI Spring Symposium: Help Me Help You: Bridging the Gaps in Human-Agent Collaboration 2011 - [c8]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:
Computational, Neuroscientific, and Lifespan Perspectives on the Exploration-Exploitation Dilemma. CogSci 2011 - 2010
- [c7]W. Bradley Knox, Peter Stone:
Combining manual feedback with subsequent MDP reward signals for reinforcement learning. AAMAS 2010: 5-12 - [c6]W. Bradley Knox, Peter Stone:
Training a Tetris agent via interactive shaping: a demonstration of the TAMER framework. AAMAS 2010: 1767-1768 - 2009
- [c5]W. Bradley Knox, Ian R. Fasel, Peter Stone:
Design Principles for Creating Human-Shapable Agents. AAAI Spring Symposium: Agents that Learn from Human Teachers 2009: 79-86 - [c4]W. Bradley Knox, Peter Stone:
Interactively shaping agents via human reinforcement: the TAMER framework. K-CAP 2009: 9-16 - 2008
- [c3]W. Bradley Knox, Juhyun Lee, Peter Stone:
Person recognition on a Segway Robot: A video of UT Austin Villa Robocup@Home 2007 finals demonstration. ICRA 2008: 1785-1786 - [c2]W. Bradley Knox, Juhyun Lee, Peter Stone:
Domestic Interaction on a Segway Base. RoboCup 2008: 519-531 - 2006
- [c1]Gregory Kuhlmann, William B. Knox, Peter Stone:
Know Thine Enemy: A Champion RoboCup Coach Agent. AAAI 2006: 1463-1468
Informal and Other Publications
- 2024
- [i6]Rafael Rafailov, Yaswanth Chittepu, Ryan Park, Harshit Sikchi, Joey Hejna, W. Bradley Knox, Chelsea Finn, Scott Niekum:
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. CoRR abs/2406.02900 (2024) - 2023
- [i5]W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking it for Reward. CoRR abs/2310.02456 (2023) - [i4]Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh:
Contrastive Preference Learning: Learning from Human Feedback without RL. CoRR abs/2310.13639 (2023) - 2022
- [i3]W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Allievi:
Models of human preference for learning reward functions. CoRR abs/2206.02231 (2022) - 2021
- [i2]W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, Peter Stone:
Reward (Mis)design for Autonomous Driving. CoRR abs/2104.13906 (2021) - 2020
- [i1]Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox:
The EMPATHIC Framework for Task Learning from Implicit Human Feedback. CoRR abs/2009.13649 (2020)
Coauthor Index
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