Using instruction matrix based genetic programming to evolve programs

被引：0
|
作者：
Li, Gang [1 ]
Lee, Kin Hong [1 ]
Leung, Kwong Sak [1 ]
机构：
[1] Chinese Univ Hong Kong, Dept Comp Sci & Engn, Shatin, Hong Kong, Peoples R China
来源：
ADVANCES IN COMPUTATION AND INTELLIGENCE, PROCEEDINGS | 2007年 / 4683卷
关键词：
genetic programming; instruction matrix based genetic programming;
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 (GP), evolving tree nodes separately would be an ideal approach to reduce the huge solution space of CP. We use Instruction Matrix based Genetic Programming (IMGP) to evolve tree nodes separately while taking into account their interdependencies in the form of subtrees. IMGP uses an Instruction Matrix (IM) to maintain the statistical data of tree nodes and subtrees. IMGP extracts program trees from IM, and updates IM with the information of the extracted program trees. The experiments have verified that the results of IMGP are better than those the related GP algorithms in terms of the qualities of the solutions and the number of program evaluations.
引用
收藏
页码：631 / +
页数：3
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