Design and improvement of the pruning algorithm of the Chinese chess in the computer games

Abstract

Computer games have always been considered to be the most challenging task in the field of artificial intelligence specially the Chinese chess as an example. The core technology of the computer games is the search. This work is studied to research an improved pruning strategy in order to achieve a deeper level search of the game tree in a limited time. On the basis of the traditional alpha–beta search algorithm, the worthless nodes are discarded to be never searched by introducing the deep iterative, history table and other auxiliary methods of pruning. The number of nodes searched is effectively reduced to make the pruning earlier to shorten the search time. At the same time, its search depth is higher than the original search algorithm. The advanced and modified algorithm is proved to be practical and applicative by experimentations and tests of computer games system provided in this study.