| Exploration in deep reinforcement learning: a comprehensive survey T Yang, H Tang, C Bai, J Liu, J Hao, Z Meng, P Liu, Z Wang IEEE Transactions on Neural Networks and Learning Systems, 1-21, 2021 | 155* | 2021 |
| From few to more: Large-scale dynamic multiagent curriculum learning W Wang *, T Yang*, Y Liu*, J Hao, X Hao, Y Hu, Y Chen, C Fan, Y Gao Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7293-7300, 2020 | 102 | 2020 |
| A deep bayesian policy reuse approach against non-stationary agents Y Zheng, Z Meng, J Hao, Z Zhang, T Yang, C Fan Advances in neural information processing systems 31, 2018 | 82 | 2018 |
| A survey on interpretable reinforcement learning C Glanois, P Weng, M Zimmer, D Li, T Yang, J Hao, W Liu Machine Learning, 1-44, 2024 | 57 | 2024 |
| Towards efficient detection and optimal response against sophisticated opponents T Yang, Z Meng, J Hao, C Zhang, Y Zheng, Z Zheng Proceedings of the 28th International Joint Conference on Artificial …, 2018 | 42 | 2018 |
| Efficient deep reinforcement learning via adaptive policy transfer T Yang, J Hao, Z Meng, Z Zhang, Y Hu, Y Cheng, C Fan, W Wang, W Liu, ... Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 31 | 2020 |
| Action semantics network: Considering the effects of actions in multiagent systems W Wang*, T Yang*, Y Liu, J Hao, X Hao, Y Hu, Y Chen, C Fan, Y Gao Proceedings of the 8th International Conference on Learning Representations, 2019 | 31 | 2019 |
| An efficient transfer learning framework for multiagent reinforcement learning T Yang, W Wang, H Tang, J Hao, Z Meng, H Mao, D Li, W Liu, Y Chen, ... Advances in neural information processing systems 34, 17037-17048, 2021 | 29* | 2021 |
| PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration P Li, H Tang, T Yang, X Hao, T Sang, Y Zheng, J Hao, ME Taylor, Z Wang International Conference on Machine Learning 162, 12979-12997, 2022 | 23 | 2022 |
| Learning action-transferable policy with action embedding Y Chen, Y Chen, Z Hu, T Yang, C Fan, Y Yu, J Hao arXiv preprint arXiv:1909.02291, 2019 | 18 | 2019 |
| Efficient policy detecting and reusing for non-stationarity in markov games Y Zheng, J Hao, Z Zhang, Z Meng, T Yang, Y Li, C Fan Autonomous Agents and Multi-Agent Systems 35, 1-29, 2021 | 16 | 2021 |
| Accelerating Norm Emergence Through Hierarchical Heuristic Learning. T Yang, Z Meng, J Hao, S Sen, C Yu Proceedings of 22nd European Conference on Artificial Intelligence (ECAI …, 2016 | 16 | 2016 |
| Neighborhood cooperative multiagent reinforcement learning for adaptive traffic signal control in epidemic regions C Zhang, Y Tian, Z Zhang, W Xue, X Xie, T Yang, X Ge, R Chen IEEE Transactions on Intelligent Transportation Systems 23 (12), 25157-25168, 2022 | 15 | 2022 |
| Bayes-ToMoP: A Fast Detection and Best Response Algorithm Towards Sophisticated Opponents. T Yang, J Hao, Z Meng, Y Zheng, C Zhang, Z Zheng AAMAS, 2282-2284, 2019 | 15 | 2019 |
| GALOIS: Boosting Deep Reinforcement Learning via Generalizable Logic Synthesis Y Cao, Z Li, T Yang, H Zhang, Y Zheng, Y Li, J Hao, Y Liu Advances in Neural Information Processing Systems 35, 19930-19943, 2022 | 11 | 2022 |
| Efficient Deep Reinforcement Learning through Policy Transfer. T Yang, J Hao, Z Meng, Z Zhang, Y Hu, Y Chen, C Fan, W Wang, Z Wang, ... AAMAS, 2053-2055, 2020 | 11 | 2020 |
| Advertising impression resource allocation strategy with multi-level budget constraint dqn in real-time bidding C Zhang, K Zheng, Y Tian, W Xue, T Yang, D An, Y Pi, R Chen Neurocomputing 488, 647-656, 2022 | 7 | 2022 |
| Cross-domain Adaptive Transfer Reinforcement Learning Based on State-Action Correspondence H You, T Yang, Y Zheng, J Hao, ME Taylor The 38th Conference on Uncertainty in Artificial Intelligence, 2022 | 6 | 2022 |
| Portal: Automatic curricula generation for multiagent reinforcement learning J Wu, J Hao, T Yang, X Hao, Y Zheng, W Wang, ME Taylor Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 15934 …, 2024 | 3 | 2024 |
| Human-in-the-Loop Reinforcement Learning: A Survey and Position on Requirements, Challenges, and Opportunities CO Retzlaff, S Das, C Wayllace, P Mousavi, M Afshari, T Yang, A Saranti, ... Journal of Artificial Intelligence Research 79, 359-415, 2024 | 3 | 2024 |
Yingfeng Chen(陈赢峰)Fuxi AI Lab in Netease在 mail.ustc.edu.cn 的电子邮件经过验证
