Self-adaptation of Genetic Operators Through Genetic Programming Techniques

被引：10

作者：

Felipe Cruz-Salinas, Andres ^{[1
]}

Gomez Perdomo, Jonatan ^{[1
]}

机构：

[1] Univ Nacl Colombia, Artificial Life Res Grp Alife, Bogota, Colombia

来源：

PROCEEDINGS OF THE 2017 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'17) | 2017年

关键词：

Evolutionary algorithms; real optimization; self-adaptation; genetic programming; self-adapted operators; EVOLUTION STRATEGIES;

D O I：

10.1145/3071178.3071214

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Here we propose an evolutionary algorithm that self modifies its operators at the same time that candidate solutions are evolved. This tackles convergence and lack of diversity issues, leading to better solutions. Operators are represented as trees and are evolved using genetic programming (GP) techniques. The proposed approach is tested with real benchmark functions and an analysis of operator evolution is provided.

引用

页码：913 / 920

页数：8

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