Siyuan Li

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Chongjie zhangWashington University in St. LouisVerified email at wustl.edu
Jianhao WangPhd of Computer Science, Tsinghua UniversityVerified email at mails.tsinghua.edu.cn
Guangxiang ZhuTsinghua UniversityVerified email at mails.tsinghua.edu.cn
Wenzhe LiPrinceton UniversityVerified email at princeton.edu
Rui WangAlumni, Stanford UniversityVerified email at cs.stanford.edu
Minxue TangDuke UniversityVerified email at duke.edu
Jin ZhangTsinghua UniversityVerified email at mails.tsinghua.edu.cn
Eric JiangUndergraduate Student, Tsinghua UniversityVerified email at mails.tsinghua.edu.cn
Jian LiTsinghua UniversityVerified email at mail.tsinghua.edu.cn
Lulu ZhengTsinghua UniverisityVerified email at mails.tsinghua.edu.cn
Fangda GuPhD Student, UC BerkeleyVerified email at berkeley.edu
Yang YuProfessor, Nanjing UniversityVerified email at nju.edu.cn
Qianchuan ZhaoCenter for Intelligent and Networked Systems, Dept. Automation, Tsinghua University, Beijing, ChinaVerified email at tsinghua.edu.cn
Yiqin YangAssistant Professor，Institue of Automation，Chinese Academy of SciencesVerified email at ia.ac.cn
Rushuai YangHong Kong University of Science and TechnologyVerified email at connect.ust.hk
Chenjia BaiShanghai AI LaboratoryVerified email at pjlab.org.cn
Bin ZhaoNorthwestern Polytechnical UniversityVerified email at mail.nwpu.edu.cn
Hongyi GuoNorthwestern UniversityVerified email at u.northwestern.edu
Bo AnNanyang Technological UniversityVerified email at ntu.edu.sg
Tianhong DaiLecturer in Computing Science, University of AberdeenVerified email at abdn.ac.uk

Siyuan Li

Harbin Institute of Technology

Verified email at hit.edu.cn - Homepage

Reinforcement Learning Robotics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Hierarchical reinforcement learning with advantage-based auxiliary rewards S Li, R Wang, M Tang, C Zhang Advances in Neural Information Processing Systems 32, 2019	82	2019
An optimal online method of selecting source policies for reinforcement learning S Li, C Zhang Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	54	2018
Offline reinforcement learning with reverse model-based imagination J Wang, W Li, H Jiang, G Zhu, S Li, C Zhang Advances in Neural Information Processing Systems 34, 29420-29432, 2021	52	2021
Learning subgoal representations with slow dynamics S Li, L Zheng, J Wang, C Zhang International Conference on Learning Representations, 2021	46	2021
Context-aware policy reuse S Li, F Gu, G Zhu, C Zhang arXiv preprint arXiv:1806.03793, 2018	38	2018
Active hierarchical exploration with stable subgoal representation learning S Li, J Zhang, J Wang, Y Yu, C Zhang arXiv preprint arXiv:2105.14750, 2021	24	2021
MetaTrader: An reinforcement learning approach integrating diverse policies for portfolio optimization H Niu, S Li, J Li Proceedings of the 31st ACM international conference on information …, 2022	22	2022
Flow to control: Offline reinforcement learning with lossless primitive discovery Y Yang, H Hu, W Li, S Li, J Yang, Q Zhao, C Zhang Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 10843 …, 2023	10	2023
Behavior contrastive learning for unsupervised skill discovery R Yang, C Bai, H Guo, S Li, B Zhao, Z Wang, P Liu, X Li International Conference on Machine Learning, 39183-39204, 2023	7	2023
Cup: Critic-guided policy reuse J Zhang, S Li, C Zhang Advances in Neural Information Processing Systems 35, 27537-27548, 2022	6	2022
Learning to Solve Tasks with Exploring Prior Behaviours R Zhu, S Li, T Dai, C Zhang, O Celiktutan 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023	1	2023
IOB: integrating optimization transfer and behavior transfer for multi-policy reuse S Li, H Li, J Zhang, Z Wang, P Liu, C Zhang Autonomous Agents and Multi-Agent Systems 38 (1), 3, 2024		2024
Robust Visual Imitation Learning with Inverse Dynamics Representations S Li, X Wang, R Zuo, K Sun, L Cui, J Ding, P Liu, Z Ma Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), 13609 …, 2024		2024
Classifying ambiguous identities in hidden-role Stochastic games with multi-agent reinforcement learning S Han, S Li, B An, W Zhao, P Liu Autonomous Agents and Multi-Agent Systems 37 (2), 35, 2023		2023
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making H Niu, S Li, J Zheng, Z Lin, J Li, J Guo, B An arXiv preprint arXiv:2308.08918, 2023		2023
IDRL: Identifying Identities in Multi-Agent Reinforcement Learning with Ambiguous Identities. S Han, P Liu, S Li CoRR, 2022		2022
Deep Reinforcement Learning with Hierarchical Structures. S Li IJCAI, 4899-4900, 2021		2021

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