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
收藏
页码：273 / 283
页数：11
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