Search Results for author: Chengjie WU

Found 4 papers, 1 papers with code

SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition

no code implementations17 Nov 2021 Hangyu Mao, Chao Wang, Xiaotian Hao, Yihuan Mao, Yiming Lu, Chengjie WU, Jianye Hao, Dong Li, Pingzhong Tang

The MineRL competition is designed for the development of reinforcement learning and imitation learning algorithms that can efficiently leverage human demonstrations to drastically reduce the number of environment interactions needed to solve the complex \emph{ObtainDiamond} task with sparse rewards.

Imitation Learning reinforcement-learning

Safe Opponent-Exploitation Subgame Refinement

no code implementations29 Sep 2021 Mingyang Liu, Chengjie WU, Qihan Liu, Yansen Jing, Jun Yang, Pingzhong Tang, Chongjie Zhang

Search algorithms have been playing a vital role in the success of superhuman AI in both perfect information and imperfect information games.

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