【作者】 郭峰；

【导师】 王熙照； 翟俊海；

【作者基本信息】 河北大学 ， 计算机应用技术， 2009， 硕士

【摘要】 本文作者针对中国象棋的计算机博弈存在一些问题,提出了一种利用象棋大师知识的新搜索剪枝算法,相关实验证明该方法在博弈树搜索中的有效性。对于残局阶段的计算机博弈,有学者提出了利用残局库,但这些残局库往往很大,匹配一个残局需要很长的时间,也未必能匹配上,效果也不好。而一般的搜索引擎在对博弈树进行剪枝的时候仅仅依据的是叶子结点评估值,没有考虑残局模式。这和人类大师有点不同。象棋大师们的大脑记住了很多残局的模式,当他们在下棋的过程中,发现当前思考局面能够匹配某个残局模式,就会停止进一步的思考。受到这个思考过程的启发,本文作者设计了一种新的剪枝算法。在搜索引擎中加入了一些经典残局判别规则,来对博弈树进行剪枝。更多还原

【Abstract】 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.更多还原