no code implementations • 8 Oct 2023 • Xihuai Wang, Shao Zhang, WenHao Zhang, Wentao Dong, Jingxiao Chen, Ying Wen, Weinan Zhang
Current evaluation methods for ZSC capability still need to improve in constructing diverse evaluation partners and comprehensively measuring the ZSC capability.
no code implementations • 13 Feb 2023 • Xihuai Wang, Zheng Tian, Ziyu Wan, Ying Wen, Jun Wang, Weinan Zhang
In this paper, we propose the \textbf{A}gent-by-\textbf{a}gent \textbf{P}olicy \textbf{O}ptimization (A2PO) algorithm to improve the sample efficiency and retain the guarantees of monotonic improvement for each agent during training.
no code implementations • 20 Mar 2022 • Xihuai Wang, Zhicheng Zhang, Weinan Zhang
Significant advances have recently been achieved in Multi-Agent Reinforcement Learning (MARL) which tackles sequential decision-making problems involving multiple participants.
1 code implementation • 7 May 2021 • Weinan Zhang, Xihuai Wang, Jian Shen, Ming Zhou
We specify the dynamics sample complexity and the opponent sample complexity in MARL, and conduct a theoretic analysis of return discrepancy upper bound.
Multi-agent Reinforcement Learning Reinforcement Learning (RL)