COMPARING GENETIC OPERATORS WITH GAUSSIAN MUTATIONS IN SIMULATED EVOLUTIONARY PROCESSES USING LINEAR-SYSTEMS

被引：129

作者：

FOGEL, DB ^{[1
]}

ATMAR, JW ^{[1
]}

机构：

[1] AICS RES INC,UNIVERSITY PK,NM 88003

来源：

BIOLOGICAL CYBERNETICS | 1990年 / 63卷 / 02期

关键词：

D O I：

10.1007/BF00203032

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Evolutionary optimization has been proposed as a method to generate machine learning through automated discovery. Specific genetic operations (e.g. crossover and inversion) have been proposed to mutate the structure that encodes expressed behavior. The efficiency of these operations is evaluated in a series of experiments aimed at solving linear systems of equations. The results indicate that these genetic operators do not compare favorably with more simple random mutation. © 1990 Springer-Verlag.

引用

页码：111 / 114

页数：4

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