Search Results for author: Xinghai Sun

Found 4 papers, 4 papers with code

TStarBot-X: An Open-Sourced and Comprehensive Study for Efficient League Training in StarCraft II Full Game

1 code implementation27 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.

Imitation Learning Starcraft +1

TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning

1 code implementation25 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.

Dota 2 Multi-agent Reinforcement Learning +3

TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game

3 code implementations19 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.

Decision Making Starcraft +1

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