A New Crossover Technique for Cartesian Genetic Programming Genetic Programming Track

被引：0
|
作者：
Clegg, Janet [1 ]
Walker, James Alfred [1 ]
Miller, Julian Francis [1 ]
机构：
[1] Univ York, Dept Elect, Intelligent Syst Grp, York YO10 5DD, N Yorkshire, England
来源：
GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2 | 2007年
关键词：
Cartesian Genetic Programming; optimization; crossover techniques;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped to create the offspring. Later Miller and Thomson introduced Cartesian Genetic Programming, which uses directed graphs as a representation to replace the tree structures originally introduced by Koza. Cartesian Genetic Programming has been shown to perform better than the traditional Genetic Programming; but it does not; use crossover to create offspring, it is implemented using mutation only. In this paper a new crossover method in Genetic Programming is introduced. The new technique is based on an adaptation of the Cartesian Genetic Programming representation and is tested oil two simple regression problems. It is shown that by implementing the new crossover technique, convergence is faster than that of using mutation only in the Cartesian Genetic Programming method.
引用
收藏
页码：1580 / 1587
页数：8
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