Using cellular automata as heuristic of computer Go

Author

Gong, Dao-Xiong ; Ruan, Xiao-gang

Author_Institution

Comput. Sci. Sch., Beijing Polytech. Univ., China

Volume

3

fYear

2002

fDate

2002

Firstpage

2353

Abstract

Based on the essential similarity of the cellular automata (CA) and the game of Go, this paper proposes a CA-based candidate move generator (GoCA) as well as the correlative knowledge represent method. A scheme for computer Go is also propounded. In which, GoCA perform the task of learning rules from expert game records, and then as a heuristic method, it combines with the minimax search to prune volume branches from the game tree. The experimental result shows the feasibility of anchoring our hope on it to improve the competitive ability of computer Go.

Keywords

cellular automata; computer games; correlation methods; heuristic programming; knowledge based systems; knowledge representation; minimax techniques; search problems; GoCA; candidate move generator; cellular automata; computer Go; correlative knowledge representation; expert game records; heuristic; minimax search; rule learning; volume branch pruning; Artificial intelligence; Chaos; Cognitive science; Computer displays; Computer science; High performance computing; Machine learning; Minimax techniques; Pattern recognition; Software engineering;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on

Print_ISBN

0-7803-7268-9

Type

conf

DOI

10.1109/WCICA.2002.1021511

Filename

1021511