1 code implementation • 27 Nov 2020 • Lei Han, Jiechao Xiong, Peng Sun, Xinghai Sun, Meng Fang, Qingwei Guo, Qiaobo Chen, Tengfei Shi, Hongsheng Yu, Xipeng Wu, Zhengyou Zhang
We show that with orders of less computation scale, a faithful reimplementation of AlphaStar's methods can not succeed and the proposed techniques are necessary to ensure TStarBot-X's competitive performance.
1 code implementation • 25 Nov 2020 • Peng Sun, Jiechao Xiong, Lei Han, Xinghai Sun, Shuxing Li, Jiawei Xu, Meng Fang, Zhengyou Zhang
This poses non-trivial difficulties for researchers or engineers and prevents the application of MARL to a broader range of real-world problems.
2 code implementations • 20 Jul 2019 • Qing Wang, Jiechao Xiong, Lei Han, Meng Fang, Xinghai Sun, Zhuobin Zheng, Peng Sun, Zhengyou Zhang
We introduce Arena, a toolkit for multi-agent reinforcement learning (MARL) research.
3 code implementations • 19 Sep 2018 • Peng Sun, Xinghai Sun, Lei Han, Jiechao Xiong, Qing Wang, Bo Li, Yang Zheng, Ji Liu, Yongsheng Liu, Han Liu, Tong Zhang
Both TStarBot1 and TStarBot2 are able to defeat the built-in AI agents from level 1 to level 10 in a full game (1v1 Zerg-vs-Zerg game on the AbyssalReef map), noting that level 8, level 9, and level 10 are cheating agents with unfair advantages such as full vision on the whole map and resource harvest boosting.