Computer Chinese Chess

Abstract

This article describes the current state of computer Chinese chess (Xiang Qi). For two reasons, Chinese-chess programming is important in the field of Artificial Intelligence. First, Chinese chess is one of the most popular and oldest board games worldwide; currently the strength of a Chinesechess program can be compared to that of human players. Second, the complexity of Chinese chess is between that of chess and Go. We assume that after DEEP BLUE's victory over Kasparov in 1997, Chinese chess will be the next popular chess-like board game at which a program will defeat a human top player. In the article we introduce some techniques for developing Chinese-chess programs. In the Computer Olympiads of 2001 and 2002, the programs ELP and SHIGA were the top Chinese-chess programs. Although these two programs roughly have the same strength, they were developed following completely different techniques, as described in the article. The improvements of the best Chinese-chess programs over the last twenty years suggest that a human top player will be defeated before 2010. 1. Chinese chess is a two-player, zero-sum game with complete information. Chinese-chess expert knowledge started to be developed some 800 years ago. Nowadays, the world has many excellent human players. Yet, already now, the strength of the best Chinese-chess programs can be compared to that of human players notwithstanding the fact that the game is considered rather complex. Table 1 shows the state-space complexity and the game-tree complexity of chess, Chinese chess, Shogi, and Go. The state-space complexity of Western chess and Chinese chess was estimated by Allis (1994). The game-tree complexity of Chinese chess is based on a branching factor of 38 and an average game length of 95 plies (Hsu, 1990). The complexity of two other games has been estimated: by Bouzy and Cazenave (2001) for Go and by Iida, Sakuta, and Rollason (2002) for Shogi. The complexity of Chinese chess is between that of Western chess and Shogi. Game State-space complexity Game-tree complexity Chess 50 123 Chinese chess 48 150 Shogi 71 226 Go 160 400 Table 1: State-space complexity and game-tree complexity given by the power of 10.

Self-Optimizing Evaluation Function for Chinese-Chess

“…The evaluation of a position in Chinese chess has approximately six elements [3]: (1) the strength of the pieces in play, (2) the positions' value, (3) the control of the places, (4) the pieces' flexibility, (5) the threat between pieces and the protection of pieces from threat, and (6) the piece features or dynamic adjustment according to the situation. Details of those elements are discussed blow.…”

“…Chinese chess is one of the most popular board games worldwide, being played by approximately 1.5 billion people in china and wherever Chinese have settled. Chinese chess program has became the next challenge for many artificial intelligence masters, because the complexity of Chinese-chess is between that of chess and Shogi (the complexity of chess is 123 (Allis(1994), the complexity of Shogi was estimated Bylida, Sakuta and Rollason (2002)) and there is a long distance between Chinese chess program and masters of Chinese-chess [3].…”

Integration of Chinese Chess Endgame Knowledge Bases

“…In the middle game, people often use a nega-scout algorithm with a good evaluation function and a nice move ordering scheme to obtain a good solution [2]. There are also strategies in artificial intelligence that automatically generate middle game evaluation functions [3].…”

A Random Walk Model for Chinese Chess Game Playing

“…This method can be applied to one, two, or multiple domains. Although many people did the same area research (Yen et al, 2004;Ong, 2007), none of them use the random walk method. In this paper, we use the random walk method for computing similarities and dissimilarities to evaluate the semantic similarities between game situation and functional similarities of situation (Fouss, Pirotte and Saerens, 2007).…”