An accelerated Genetic Algorithm

被引：19

作者：

Podlena, JR ^{[1
]}

Hendtlass, T ^{[1
]}

机构：

[1] Swinburne Univ Technol, Sch Biophys Sci & Elect Engn, Ctr Intelligent Syst, Hawthorne, Vic 3122, Australia

来源：

APPLIED INTELLIGENCE | 1998年 / 8卷 / 02期

关键词：

genetic algorithm; neural networks; Baldwin effect; optimisation; history;

D O I：

10.1023/A:1008227606285

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The standard Genetic Algorithm, originally inspired by natural evolution, has displayed its effectiveness in solving a wide variety of complex problems. This paper describes the use of the natural phenomenon known as the Baldwin effect (or cross-generational learning) as an enhancement to the standard Genetic Algorithm. This is implemented by using an artificial neural network to store aspects of the population's history. It also describes a method by which the negative side effects of a large elite sub-population can be counter-balanced by using an ageing coefficient in the fitness calculation.

引用

页码：103 / 111

页数：9

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