Genetic learning of fuzzy reactive controllers

被引：27

作者：

Matellan, V ^{[1
]}

Fernandez, C ^{[1
]}

Molina, JM ^{[1
]}

机构：

[1] Univ Carlos III Madrid, Dept Informat, Madrid, Spain

来源：

ROBOTICS AND AUTONOMOUS SYSTEMS | 1998年 / 25卷 / 1-2期

关键词：

autonomous robots; fuzzy; genetic algorithms; learning;

D O I：

10.1016/S0921-8890(98)00035-9

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper concerns the learning of basic behaviors in an autonomous robot. It presents a method to adapt basic reactive behaviors using a genetic algorithm. Behaviors are implemented as fuzzy controllers and the genetic algorithm is used to evolve their rules. These rules will be formulated in a fuzzy way using prefixed linguistic labels. In order to test the rules obtained in each generation of the genetic evolution process, a real robot has been used. Numerical results from the evolution rate of the different experiments, as well as an example of the fuzzy rules obtained, are presented and discussed. (C) 1998 Elsevier Science B.V. All rights reserved.

引用

页码：33 / 41

页数：9