JiangJun: Mastering Xiangqi by Tackling Non-Transitivity in Two-Player Zero-Sum Games

no code implementations • 9 Aug 2023 • Yang Li, Kun Xiong, Yingping Zhang, Jiangcheng Zhu, Stephen Mcaleer, Wei Pan, Jun Wang, Zonghong Dai, Yaodong Yang

This paper presents an empirical exploration of non-transitivity in perfect-information games, specifically focusing on Xiangqi, a traditional Chinese board game comparable in game-tree complexity to chess and shogi.

An Empirical Study on Google Research Football Multi-agent Scenarios

1 code implementation • 16 May 2023 • Yan Song, He Jiang, Zheng Tian, Haifeng Zhang, Yingping Zhang, Jiangcheng Zhu, Zonghong Dai, Weinan Zhang, Jun Wang

Few multi-agent reinforcement learning (MARL) research on Google Research Football (GRF) focus on the 11v11 multi-agent full-game scenario and to the best of our knowledge, no open benchmark on this scenario has been released to the public.

Benchmarking Multi-agent Reinforcement Learning +1