Applying Determinized MCTS in Chinese Military Chess
Monte Carlo Tree Search(MCTS)algorithm has been proved to be very successful in many perfect information games such as Go and Amazon.This leads to a trend to apply MCTS in games with imperfect information.One popular method is called Determinized MCTS and its efficiency has been shown in many games.In this paper,we plan to apply determinized MCTS to Chinese Military Chess,which is a very popular game in China.We discuss how to generate initial belief state for AI agent according to some rules and domain knowledge of the game,and present an algorithm to update it online.We then apply this framework into determinized MCTS and show its efficiency in experiments.
Chinese Military Chess Monte Carlo Determinized MCTS Belief State
Chenjun Xiao Tan Zhu Chao Lin Xinhe Xu Jiao Wang
Software College,Northeastern University,Shenyang,110819 School of Information Science and Engineering,Northeastern University,Shenyang,110819
国际会议
长沙
英文
3941-3946
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）