Research On Discrimination Pruning In Game Tree Search Of Computer Chinese Chess

In this thesis, the author proposes a new game tree pruning algorithm to solve the problem about the computer Chinese chess, which uses the masters'experience on the endgame position judgment. The relevant experiments show the good efficiency on the game tree search.Researchers had proposed the endgame database to solve the computer Chinese chess problem in the end period of the game. However, since the endgame database is always very huge, it needs much time to match the current position and it maybe failed. Therefore, the result is not satisfying. The ordinary search engines select the best move based on the position values of leaf nodes of game tree, without considering the endgame patterns. But there is a difference between the engines and the masters. When playing the chess, masters will stop the consideration on the position after one move if the current thinking position matches an endgame pattern, which has been remembered in the masters'brains, but the search engines will not. Inspired by this process, the author designs a new algorithm to select the best move. In the algorithm,many patterns have been added into the new search engine to prune the game tree.