Bei Peng
TitleCited byYear
Interactive learning from policy-dependent human feedback
J MacGlashan, MK Ho, R Loftin, B Peng, G Wang, DL Roberts, ME Taylor, ...
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
452017
A strategy-aware technique for learning behaviors from discrete human feedback
RT Loftin, J MacGlashan, B Peng, ME Taylor, ML Littman, J Huang, ...
Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
432014
Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning
R Loftin, B Peng, J MacGlashan, ML Littman, ME Taylor, J Huang, ...
Autonomous agents and multi-agent systems 30 (1), 30-59, 2016
422016
A need for speed: Adapting agent action speed to improve task learning from non-expert humans
B Peng, J MacGlashan, R Loftin, ML Littman, DL Roberts, ME Taylor
Proceedings of the 2016 International Conference on Autonomous Agents …, 2016
312016
Learning something from nothing: Leveraging implicit human feedback strategies
R Loftin, B Peng, J MacGlashan, ML Littman, ME Taylor, J Huang, ...
The 23rd IEEE International Symposium on Robot and Human Interactive …, 2014
152014
Training an agent to ground commands with reward and punishment
J MacGlashan, M Littman, R Loftin, B Peng, D Roberts, M Taylor
Workshops at the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
152014
An empirical study of non-expert curriculum design for machine learners
B Peng, J MacGlashan, R Loftin, ML Littman, DL Roberts, ME Taylor
In Proceedings of the IJCAI Interactive Machine Learning Workshop, 2016
102016
Towards integrating real-time crowd advice with reinforcement learning
GV de la Cruz, B Peng, WS Lasecki, ME Taylor
Proceedings of the 20th International Conference on Intelligent User …, 2015
62015
Convergent Actor Critic by Humans
J MacGlashan, ML Littman, DL Roberts, R Loftin, B Peng, ME Taylor
International Conference on Intelligent Robots and Systems, 2016
32016
Curriculum Design for Machine Learners in Sequential Decision Tasks
B Peng, J MacGlashan, R Loftin, ML Littman, DL Roberts, ME Taylor
IEEE Transactions on Emerging Topics in Computational Intelligence 2 (4 …, 2018
22018
Language and policy learning from human-delivered feedback
B Peng, R Loftin, J MacGlashan, ML Littman, ME Taylor, DL Roberts
Proc. Mach. Learn. Social Robot. Workshop, 2015
22015
Generating real-time crowd advice to improve reinforcement learning agents
GV de la Cruz, B Peng, WS Lasecki, ME Taylor
Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
22015
How do humans teach: On curriculum design for machine learners
B Peng
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent …, 2017
12017
Interactive Learning of Environment Dynamics for Sequential Tasks
R Loftin, B Peng, ME Taylor, ML Littman, DL Roberts
arXiv preprint arXiv:1907.08478, 2019
2019
Learning from Human Teachers: Supporting How People Want to Teach in Interactive Machine Learning
B Peng
Washington State University, 2018
2018
Towards Behavior-Aware Model Learning from Human-Generated Trajectories
RT Loftin, J MacGlashan, B Peng, ME Taylor, ML Littman, DL Roberts
2016 AAAI Fall Symposium Series, 2016
2016
On the Ability to Provide Demonstrations on a UAS: Observing 90 Untrained Participants Abusing a Flying Robot
M Scott, B Peng, M Chili, T Nigam, F Pascual, C Matuszek, ME Taylor
2015 AAAI Fall Symposium Series, 2015
2015
SPECIAL ISSUE ON HUMAN-MACHINE SYMBIOSIS
RE Patterson, RG Eggleston, M Demir, NJ McNeese, NJ Cooke, B Peng, ...
Open Problems for Online Bayesian Inference in Neural Networks
R Loftin, ME Taylor, ML Littman, J MacGlashan, B Peng, DL Roberts
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Articles 1–19