基于数学形态学的围棋棋群聚类算法

计算机围棋可以模拟人类棋手的棋群聚类能力以提高搜索效率。本研究以数学形态学为工具，在形式化基础上采用带有限制条件的膨胀运算进行棋群的初步聚类，结合其它一些启发式搜索方法完成棋群的最终聚类，并结合实战对局评价了此算法的性能，指出了此算法的应用价值。

Cluster Algorithm of Go Groups Based on Mathematical Morphology

The computer go can simulate human player's go group clustering ability to improve its searching efficiency. This study,taking mathematical morphology as a tool,based on the formalization,adopts constrained dilating opera- tion to undergo preliminary clustering on go groups,and combines with some other heuristic searching methods to com- plete the final clustering on go groups.This paper,by linking with actual combat,also evaluates the algorithm's capa- bility,and at the same time points out its application value.