no code implementations • 25 Oct 2022 • Ziluo Ding, Wanpeng Zhang, Junpeng Yue, Xiangjun Wang, Tiejun Huang, Zongqing Lu
We investigate the use of natural language to drive the generalization of policies in multi-agent settings.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 14 Oct 2022 • Xi Chen, Tianyu Shi, Qingpeng Zhao, Yuchen Sun, Yunfei Gao, Xiangjun Wang
It provides realistic 3D environments of variable complexity, various tasks, and multiple modes of interaction, where agents can learn to perceive 3D environments, navigate and plan, compete and cooperate in a human-like manner.
no code implementations • 17 Sep 2022 • Kefan Su, Siyuan Zhou, Jiechuan Jiang, Chuang Gan, Xiangjun Wang, Zongqing Lu
Decentralized learning has shown great promise for cooperative multi-agent reinforcement learning (MARL).
no code implementations • 24 Dec 2020 • Xiangjun Wang, Junxiao Song, Penghui Qi, Peng Peng, Zhenkun Tang, Wei zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao GAO, Haitao Long, Quan Yuan
In this paper, we will share the key insights and optimizations on efficient imitation learning and reinforcement learning for StarCraft II full game.