Learning Classifier System with Convergence and Generalization
Learning Classifier System with Convergence and Generalization
复制标题
具有收敛性和泛化性的学习分类器系统
DOI：
10.1007/11319122_11
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
O. Katai
中科院分区：
文献类型：
--
作者：
A. Wada;K. Takadama;K. Shimohara;O. Katai
摘要学习分类器系统（LCS）是一种基于规则的系统，其规则被命名为分类器。最初的LCS是由Holland [1，2]引入的，旨在成为研究条件-动作规则学习的框架。它包括规则条件下的泛化机制和使用遗传算法的规则发现机制[3]。后来，这个原始的LCS被修改为它的“标准形式”[4]，产生了许多变体[5-8]。
AbstractLearning Classifier Systems (LCSs) are rule-based systems whose rules are namedclassifiers. The original LCS was introduced by Holland [1, 2], and was intended to be a framework to study learning in condition-action rules. It included the distinctive features of ageneralizationmechanism in rule conditions and arule discoverymechanism using genetic algorithms (GAs) [3]. Later, this original LCS was revised to its “standard form”[4], which produced many variants [5–8].