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Dapeng Li (
李大鹏
)
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[1] From Explicit Communication to Tacit Cooperation:A Novel Paradigm for Cooperative MARL
International Conference on Autonomous Agents and Multi-Agent Systems(AAMAS), in Auckland, New Zealand, 2024. (Extended Abstract)
Dapeng Li, Zhiwei Xu, Bin Zhang, and Guoliang Fan
[Arxiv]
[2] Adaptive Parameter Sharing for Multi-Agent Reinforcement Learning
IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP), in Seoul, Korea, 2024.
Dapeng Li, Na Lou, Bin Zhang, Zhiwei Xu, and Guoliang Fan
[Arxiv]
[3] SEA: A Spatially Explicit Architecture for Multi-Agent Reinforcement Learning
International Joint Conference on Neural Networks(IJCNN),in Queensland, Australia, 2023.
Dapeng Li, Zhiwei Xu, Bin Zhang, and Guoliang Fan,
[4] Consensus Learning for Cooperative Multi-Agent Reinforcement Learning
Thirty-Seventh AAAI Conference on Artificial Intelligence(AAAI),in Washington, DC, USA, 2023.
(Oral)
Zhiwei Xu, Bin Zhang, Dapeng Li, Zeren Zhang, Guangchong Zhou, and Guoliang Fan,
[Arxiv][Code]
[5] HAVEN: Hierarchical Cooperative Multi-Agent Reinforcement Learning with Dual Coordination Mechanism
Thirty-Seventh AAAI Conference on Artificial Intelligence(AAAI),in Washington, DC, USA, 2023.
(Oral)
Zhiwei Xu, Yunpeng Bai, Bin Zhang, Dapeng Li, and Guoliang Fan,
[Arxiv][Code]
[6] Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning
Thirty-sixth Conference on Neural Information Processing Systems(NeurIPS),
in New Orleans, USA, 2022.
Zhiwei Xu, Dapeng Li, Bin Zhang, Yuan Zhan, Yunpeng Bai, and Guoliang Fan,
(Spotlight)
[Arxiv]
[7] MMD-MIX: Value Function Factorisation with Maximum Mean Discrepancy for Cooperative Multi-Agent Reinforcement Learning
International Joint Conference on Neural Networks(IJCNN),
in Shenzhen, China, 2021.
Zhiwei Xu, Dapeng Li , Yunpeng Bai, and Guoliang Fan*,
(Poster)
[Arxiv]
[8] SIDE: State Inference for Partially Observable Cooperative Multi-Agent Reinforcement Learning
International Conference on Autonomous Agents and Multi-Agent Systems(AAMAS),
in Auckland, New Zealand, 2022.
Zhiwei Xu, Yunpeng Bai,Dapeng Li, Bin Zhang, and Guoliang Fan*,
(Oral)
[Arxiv][Code]
Pre-prints:
[1] Style Miner: Find Significant and Stable Explanatory Factors in Time Series with Constrained Reinforcement Learning
Dapeng Li, Feiyang Pan, Jia He, Zhiwei Xu, Dandan Tu, and Guoliang Fan.
[Arxiv]