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Bei Peng
Bei Peng
Lecturer (Assistant Professor), University of Liverpool
Bestätigte E-Mail-Adresse bei liverpool.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
S Narvekar, B Peng, M Leonetti, J Sinapov, ME Taylor, P Stone
Journal of Machine Learning Research (JMLR 2020) 21, 1-50, 2020
6102020
Weighted QMIX: Expanding Monotonic Value Function Factorisation
T Rashid, G Farquhar, B Peng, S Whiteson
Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020), 2020
395*2020
Interactive learning from policy-dependent human feedback
J MacGlashan, MK Ho, R Loftin, B Peng, G Wang, DL Roberts, ME Taylor, ...
34th International Conference on Machine Learning (ICML 2017), 2285-2294, 2017
3662017
FACMAC: Factored Multi-Agent Centralised Policy Gradients
B Peng, T Rashid, CAS de Witt, PA Kamienny, PHS Torr, W Böhmer, ...
35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021
2562021
RODE: Learning Roles to Decompose Multi-Agent Tasks
T Wang, T Gupta, A Mahajan, B Peng, S Whiteson, C Zhang
International Conference on Learning Representations (ICLR 2021), 2020
2342020
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 (JAAMAS 2016) 30 (1), 30-59, 2016
1332016
Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control
CS de Witt, B Peng (equal contribution), PA Kamienny, P Torr, W Böhmer, ...
arXiv preprint arXiv:2003.06709, 2020
972020
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
S Iqbal, CAS de Witt, B Peng, W Böhmer, S Whiteson, F Sha
38th International Conference on Machine Learning (ICML 2021), 2021
90*2021
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 (AAAI 2014), 2014
822014
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
Autonomous Agents and Multiagent Systems (AAMAS 2016), 2016
602016
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
T Gupta, A Mahajan, B Peng, W Böhmer, S Whiteson
38th International Conference on Machine Learning (ICML 2021), 2021
552021
Optimistic Exploration even with a Pessimistic Initialisation
T Rashid, B Peng, W Böhmer, S Whiteson
International Conference on Learning Representations (ICLR 2020), 2020
532020
Regularized Softmax Deep Multi-Agent Q-Learning
L Pan, T Rashid, B Peng, L Huang, S Whiteson
35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021
40*2021
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
362014
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
242014
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
202018
An empirical study of non-expert curriculum design for machine learners
B Peng, J MacGlashan, R Loftin, ML Littman, DL Roberts, ME Taylor
Proceedings of the IJCAI Interactive Machine Learning Workshop, 2016
142016
Convergent Actor Critic by Humans
J MacGlashan, ML Littman, DL Roberts, R Loftin, B Peng, ME Taylor
International Conference on Intelligent Robots and Systems (IROS 2016), 2016
142016
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
112015
Accelerating laboratory automation through robot skill learning for sample scraping
G Pizzuto, H Wang, H Fakhruldeen, B Peng, KS Luck, AI Cooper
2024 IEEE 20th International Conference on Automation Science and …, 2024
72024
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