Design and implementation of Chinese Dark Chess programs

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

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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.

Original languageEnglish
Article number6826513
Pages (from-to)66-74
Number of pages9
JournalIEEE Transactions on Computational Intelligence and AI in Games
Volume7
Issue number1
DOIs
StatePublished - 1 Mar 2015

Keywords

  • Chance nodes
  • Chinese Dark Chess
  • Monte Carlo Tree Search
  • nondeterministic actions
  • stochastic games

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