Crossover-Based Tree Distance in Genetic Programming
Crossover-Based Tree Distance in Genetic Programming
复制标题
遗传编程中基于交叉的树距离
DOI：
10.1109/tevc.2008.915993
复制
发表时间：
2008
影响因子：
14.3
通讯作者：
L. Vanneschi
中科院分区：
文献类型：
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作者：
Steven M. Gustafson;L. Vanneschi
在进化算法中，解之间的距离度量通常对指导和理解搜索过程的许多方面都很有用。一个好的距离度量应该反映搜索的能力：如果发现两个解在距离或相似性上接近，那么它们在搜索算法的意义上也应该接近，即，用于遍历搜索空间的变分算子应当容易地将它们中的一个变换成另一个。本文探讨了遗传编程语法树这样的距离。距离的措施进行了讨论，定义和实证研究。然后，在分析（在种群进化过程中分析适应度-距离相关性）以及指导搜索（在适应度共享算法中使用我们的度量改进结果）和多样性（与标准度量相比，获得了新的见解）的背景下验证这些度量的价值。
In evolutionary algorithms, distance metrics between solutions are often useful for many aspects of guiding and understanding the search process. A good distance measure should reflect the capability of the search: if two solutions are found to be close in distance, or similarity, they should also be close in the search algorithm sense, i.e., the variation operator used to traverse the search space should easily transform one of them into the other. This paper explores such a distance for genetic programming syntax trees. Distance measures are discussed, defined and empirically investigated. The value of such measures is then validated in the context of analysis (fitness-distance correlation is analyzed during population evolution) as well as guiding search (results are improved using our measure in a fitness sharing algorithm) and diversity (new insights are obtained as compared with standard measures).
DOI：
--
发表时间：
1992
期刊：
--
影响因子：
--
作者：
J. Koza
通讯作者：
J. Koza