OpenHoldem: A Benchmark for Large-Scale Imperfect-Information Game Research

doi:10.1109/TNNLS.2023.3280186

	OpenHoldem: A Benchmark for Large-Scale Imperfect-Information Game Research
	Li, Kai1,2 ; Xu, Hang 1,2; Zhao, Enmin1,2 ; Wu, Zhe1,2 ; Xing, Junliang3
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN	2162-237X
	2023-06-14
页码	15
通讯作者	Xing, Junliang(jlxing@tsinghua.edu.cn)
摘要	Owing to the unremitting efforts from a few institutes, researchers have recently made significant progress in designing superhuman artificial intelligence (AI) in no-limit Texas hold'em (NLTH), the primary testbed for large-scale imperfect-information game research. However, it remains challenging for new researchers to study this problem since there are no standard benchmarks for comparing with existing methods, which hinders further developments in this research area. This work presents OpenHoldem, an integrated benchmark for large-scale imperfect-information game research using NLTH. OpenHoldem makes three main contributions to this research direction: 1) a standardized evaluation protocol for thoroughly evaluating different NLTH AIs; 2) four publicly available strong baselines for NLTH AI; and 3) an online testing platform with easy-to-use APIs for public NLTH AI evaluation. We will publicly release OpenHoldem and hope it facilitates further studies on the unsolved theoretical and computational issues in this area and cultivates crucial research problems like opponent modeling and human-computer interactive learning.
关键词	Artificial intelligence (AI) benchmark imperfect-information game Nash equilibrium no-limit Texas hold'em (NLTH)
DOI	10.1109/TNNLS.2023.3280186
关键词[WOS]	LEVEL ; GO ; POKER ; ALGORITHM ; SHOGI ; CHESS
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2022ZD0116401] ; Natural Science Foundation of China[62076238] ; Natural Science Foundation of China[62222606] ; Natural Science Foundation of China[61902402] ; China Computer Federation (CCF)-Tencent Open Fund ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA27000000]
项目资助者	National Key Research and Development Program of China ; Natural Science Foundation of China ; China Computer Federation (CCF)-Tencent Open Fund ; Strategic Priority Research Program of the Chinese Academy of Sciences
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:001012538800001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53571
专题	复杂系统认知与决策实验室_决策指挥与体系智能
通讯作者	Xing, Junliang
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Li, Kai,Xu, Hang,Zhao, Enmin,et al. OpenHoldem: A Benchmark for Large-Scale Imperfect-Information Game Research[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2023:15.
APA	Li, Kai,Xu, Hang,Zhao, Enmin,Wu, Zhe,&Xing, Junliang.(2023).OpenHoldem: A Benchmark for Large-Scale Imperfect-Information Game Research.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,15.
MLA	Li, Kai,et al."OpenHoldem: A Benchmark for Large-Scale Imperfect-Information Game Research".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023):15.