Design and Implementation of Chinese Dark Chess Programs

Author

Shi-Jim Yen ; Cheng-Wei Chou ; Jr-Chang Chen ; I-Chen Wu ; Kuo-Yuan Kao

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Nat. Dong Hwa Univ., Hualien, Taiwan

Volume

7

Issue

1

fYear

2015

fDate

Mar-15

Firstpage

66

Lastpage

74

Abstract

Chinese Dark Chess is an old and very popular game in the Chinese culture sphere. This game is a stochastic game with symmetric hidden information. This paper reviews alpha-beta search with chance nodes and proposes heuristics on Chinese Dark Chess programs. We propose an application of nondeterministic Monte Carlo Tree Search with random nodes for tackling partial observation. The proposed methods were implemented in the program Diablo, which won four Chinese Dark Chess tournaments in TAAI 2011/2012, TCGA 2011/2012 computer game tournaments. Diablo also played hundreds of games with different human players and programs based on alpha-beta search. These results show that the nondeterministic MCTS equipped with our heuristics is promising for Chinese Dark Chess.

Keywords

Monte Carlo methods; computer games; random processes; stochastic games; tree searching; Chinese culture sphere; Chinese dark chess program; alpha-beta search; computer game tournament; nondeterministic MCTS; nondeterministic Monte Carlo tree search; program Diablo; random nodes; stochastic game; symmetric hidden information; Backpropagation; Color; Educational institutions; Electronic mail; Games; Monte Carlo methods; Probability distribution; Chance nodes; Chinese Dark Chess; Monte Carlo Tree Search; nondeterministic actions; stochastic games;

fLanguage

English

Journal_Title

Computational Intelligence and AI in Games, IEEE Transactions on

Publisher

ieee

ISSN

1943-068X

Type

jour

DOI

10.1109/TCIAIG.2014.2329034

Filename

6826513