A parallel computer-Go player, using HDP method

Xindi Cai, D.C. Wunsch
IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222)  
The game Go has simple rules to learn but requires complex strategies to play well, and, the conventional tree search algorithm for computer games is not suited for Go program. Thus, the game Go is an ideal problem domain for machine learning algorithms. This paper examines the performance of a 19x19 computer Go player, using heuristic dynamic programming (HDP) and parallel Alpha-Beta search. The neural network based Go player learns good Go evaluation functions and wins about 30% of the games
more » ... t 30% of the games in a test series on 19x1 9 board.
doi:10.1109/ijcnn.2001.938737 fatcat:ncwiuedrabfp3c243rfzyt5yii