W Bradley Knox

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Peter StoneProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
Cynthia BreazealProfessor Media Arts and Sciences, MIT Media LabVerified email at media.mit.edu
Maya CakmakUniversity of WashingtonVerified email at cs.washington.edu
Todd KuleszaUser Experience Researcher, GoogleVerified email at google.com
Saleema AmershiMicrosoft ResearchVerified email at microsoft.com
Bradley C. LoveProfessor of Cognitive and Decision Sciences, University College LondonVerified email at ucl.ac.uk
Alessandro AllieviImperial College LondonVerified email at imperial.ac.uk
Scott NiekumAssociate Professor, University of Massachusetts AmherstVerified email at cs.umass.edu
Hayley HungAssociate Professor, Delft University of TechnologyVerified email at tudelft.nl
Shimon WhitesonProfessor of Computer Science, University of Oxford / Senior Staff Research Scientist, WaymoVerified email at cs.ox.ac.uk
Guangliang LiAssociate Professor, College of Electrical Engineering, Ocean University of China, Qingdao, ChinaVerified email at ouc.edu.cn
Ross OttoDepartment of Psychology, McGill UniversityVerified email at mcgill.ca
Serena BoothMITVerified email at mit.edu
Jin Joo Lee, PhDAmazon Lab126Verified email at amazon.com
Felix SchmittBosch Center for Artificial IntelligenceVerified email at de.bosch.com
W. Todd MaddoxWayne Holtzman Chair and Professor of Psychology, University of TexasVerified email at utexas.edu
Jolie Baumann WormwoodUniversity of New HampshireVerified email at unh.edu
David DeStenoNortheastern UniversityVerified email at northeastern.edu
Brian GlassPostdoctoral Researcher of Psychology and Computer Science, University College London, University ofVerified email at qmul.ac.uk
Stephane Hatgis-KessellStanford UniversityVerified email at stanford.edu

W Bradley Knox

Research Associate Professor at UT Austin

Verified email at cs.utexas.edu - Homepage

Reward functions Alignment RLHF Reinforcement Learning Human-Robot Interaction


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Power to the people: The role of humans in interactive machine learning S Amershi, M Cakmak, WB Knox, T Kulesza AI Magazine 35 (4), 105-120, 2014	1261	2014
Interactively shaping agents via human reinforcement: The TAMER framework WB Knox, P Stone Proceedings of the 5th International Conference on Knowledge Capture (K-CAP …, 2009	639	2009
Reinforcement learning from simultaneous human and MDP reward WB Knox, P Stone Proceedings of the 11th International Conference on Autonomous Agents and …, 2012	290*	2012
Combining manual feedback with subsequent MDP reward signals for reinforcement learning WB Knox, P Stone Proceedings of the 9th International Conference on Autonomous Agents and …, 2010	280	2010
Tamer: Training an agent manually via evaluative reinforcement WB Knox, P Stone 2008 7th IEEE international conference on development and learning, 292-297, 2008	227	2008
Training a robot via human feedback: A case study WB Knox, P Stone, C Breazeal International Conference on Social Robotics (ICSR), 460-470, 2013	182	2013
Computationally modeling interpersonal trust JJ Lee, B Knox, J Baumann, C Breazeal, D DeSteno Frontiers in psychology 4, 56004, 2013	130	2013
Reward (Mis)design for Autonomous Driving WB Knox, A Allievi, H Banzhaf, F Schmitt, P Stone arXiv preprint arXiv:2104.13906, 2021	112	2021
The nature of belief-directed exploratory choice in human decision-making WB Knox, AR Otto, P Stone, B Love Frontiers in Psychology 2, 2012	101	2012
How humans teach agents: A new experimental perspective WB Knox, BD Glass, BC Love, WT Maddox, P Stone International Journal of Social Robotics 4 (4), 409-421, 2012	96	2012
Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance WB Knox, P Stone Artificial Intelligence 225, 24-50, 2015	78	2015
Reinforcement Learning from Human Reward: Discounting in Episodic Tasks WB Knox, P Stone 21st IEEE International Symposium on Robot and Human Interactive …, 2012	76	2012
The EMPATHIC Framework for Task Learning from Implicit Human Feedback Y Cui, Q Zhang, A Allievi, P Stone, S Niekum, WB Knox Conference on Robot Learning (CoRL), 2020	70	2020
The perils of trial-and-error reward design: misdesign through overfitting and invalid task specifications S Booth, WB Knox, J Shah, S Niekum, P Stone, A Allievi Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 5920-5929, 2023	63	2023
Learning from Human-Generated Reward WB Knox University of Texas at Austin, 2012	61	2012
Contrastive prefence learning: Learning from human feedback without rl J Hejna, R Rafailov, H Sikchi, C Finn, S Niekum, WB Knox, D Sadigh arXiv preprint arXiv:2310.13639, 2023	49	2023
Learning non-myopically from human-generated reward WB Knox, P Stone Proceedings of the 2013 international conference on Intelligent user …, 2013	48	2013
Know thine enemy: A champion RoboCup coach agent G Kuhlmann, WB Knox, P Stone Proceedings of the National Conference on Artificial Intelligence 21 (2), 1463, 2006	47	2006
Using informative behavior to increase engagement in the tamer framework G Li, H Hung, S Whiteson, WB Knox Proceedings of the 2013 international conference on autonomous agents and …, 2013	43	2013
Design Principles for Creating Human-Shapable Agents. WB Knox, IR Fasel, P Stone AAAI Spring Symposium: Agents that Learn from Human Teachers, 79-86, 2009	35	2009

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