An evolutionary function approximation approach to compute prediction in XCSF

被引：0
|
作者：
Hamzeh, A [1 ]
Rahmani, A [1 ]
机构：
[1] Iran Univ Sci & Technol, Dept Comp Engn, Tehran, Iran
来源：
MACHINE LEARNING: ECML 2005, PROCEEDINGS | 2005年 / 3720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：
XCSF is a new extension to XCS that is developed to extend XCS's reward calculation capability via computing. This new feature is called computable prediction. The first version of XCSF tries to find the most appropriate equation to compute each classifier's reward using a weight update mechanism. In this paper, we try to propose a new evolutionary mechanism to compute these equations using genetic algorithms.
引用
收藏
页码：584 / 592
页数：9
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