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Yujing Hu
Yujing Hu
NetEase Fuxi AI Lab
在 corp.netease.com 的电子邮件经过验证
标题
引用次数
引用次数
年份
Multi-agent game abstraction via graph attention neural network
Y Liu, W Wang, Y Hu, J Hao, X Chen, Y Gao
Proceedings of the AAAI conference on artificial intelligence 34 (05), 7211-7218, 2020
2642020
Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application
Y Hu, Q Da, A Zeng, Y Yu, Y Xu
Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018
2132018
Learning to utilize shaping rewards: A new approach of reward shaping
Y Hu, W Wang, H Jia, Y Wang, Y Chen, J Hao, F Wu, C Fan
Advances in Neural Information Processing Systems 33, 15931-15941, 2020
1842020
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
1202020
Episodic multi-agent reinforcement learning with curiosity-driven exploration
L Zheng, J Chen, J Wang, J He, Y Hu, Y Chen, C Fan, Y Gao, C Zhang
Advances in Neural Information Processing Systems 34, 3757-3769, 2021
832021
Multiagent reinforcement learning with unshared value functions
Y Hu, Y Gao, B An
IEEE transactions on cybernetics 45 (4), 647-662, 2014
702014
Q-value path decomposition for deep multiagent reinforcement learning
Y Yang, J Hao, G Chen, H Tang, Y Chen, Y Hu, C Fan, Z Wei
International Conference on Machine Learning, 10706-10715, 2020
632020
Towards unifying behavioral and response diversity for open-ended learning in zero-sum games
X Liu, H Jia, Y Wen, Y Hu, Y Chen, C Fan, Z Hu, Y Yang
Advances in Neural Information Processing Systems 34, 941-952, 2021
502021
Accelerating multiagent reinforcement learning by equilibrium transfer
Y Hu, Y Gao, B An
IEEE transactions on cybernetics 45 (7), 1289-1302, 2014
502014
Value Function Transfer for Deep Multi-Agent Reinforcement Learning Based on N-Step Returns.
Y Liu, Y Hu, Y Gao, Y Chen, C Fan
IJCAI, 457-463, 2019
442019
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, ...
arXiv preprint arXiv:2002.08037, 2020
382020
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
arXiv preprint arXiv:1907.11461, 2019
372019
Individual reward assisted multi-agent reinforcement learning
L Wang, Y Zhang, Y Hu, W Wang, C Zhang, Y Gao, J Hao, T Lv, C Fan
International Conference on Machine Learning, 23417-23432, 2022
352022
Learning in Multi-agent Systems with Sparse Interactions by Knowledge Transfer and Game Abstraction.
Y Hu, Y Gao, B An
AAMAS, 753-761, 2015
312015
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
272021
Fever basketball: A complex, flexible, and asynchronized sports game environment for multi-agent reinforcement learning
H Jia, Y Hu, Y Chen, C Ren, T Lv, C Fan, C Zhang
arXiv preprint arXiv:2012.03204, 2020
222020
Unifying behavioral and response diversity for open-ended learning in zero-sum games
X Liu, H Jia, Y Wen, Y Yang, Y Hu, Y Chen, C Fan, Z Hu
arXiv preprint arXiv:2106.04958, 2021
202021
Aligndiff: Aligning diverse human preferences via behavior-customisable diffusion model
Z Dong, Y Yuan, J Hao, F Ni, Y Mu, Y Zheng, Y Hu, T Lv, C Fan, Z Hu
arXiv preprint arXiv:2310.02054, 2023
182023
Euclid: Towards efficient unsupervised reinforcement learning with multi-choice dynamics model
Y Yuan, J Hao, F Ni, Y Mu, Y Zheng, Y Hu, J Liu, Y Chen, C Fan
arXiv preprint arXiv:2210.00498, 2022
132022
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
132020
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