We introduce in this paper a runtime-efficient tree hashing algorithm for the identification of isomorphic subtrees, with two important applications in genetic programming for symbolic regression: fast, online calculation of population diversity and algebraic simplification of symbolic expression trees. Based on this hashing approach, we propose a simple diversity-preservation mechanism with promising results on a collection of symbolic regression benchmark problems.

翻译：在本文中,我们引入了一种用于识别异形亚树种的运行时间效率高的树干散射算法,其中在基因规划中有两个重要应用,即快速、在线计算人口多样性和代数简化象征性表达树。 基于这种散射法,我们提出了一个简单的多样性保护机制,在收集象征性回归基准问题方面有望取得成果。