Learning Classifier System with Self-adaptive Discovery Mechanism

被引：0

作者：

Troc, Maciej ^{[1
]}

Unold, Olgierd ^{[1
]}

机构：

[1] Wroclaw Univ Technol, Inst Comp Engn Control & Robot, PL-50370 Wroclaw, Poland

来源：

NATURE INSPIRED COOPERATIVE STRATEGIES FOR OPTIMIZATION (NICSO 2007) | 2008年 / 129卷

关键词：

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：

Learning Classifier System which replaces the genetic algorithm with (lie evolving cooperative population of discoverers is a focus of current research. This paper presents a modified version of XCS classifier system with self-adaptive discovery module. The new model was confirmed experimentally in a multiplexer environment. The results prove that XCS with the self-adaptive method for determining mutation rate had a better performance than the classic architecture with fixed mutation.

引用

页码：273 / 283

页数：11

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