A learning classifier system based on genetic network programming

Xianneng Li, Kotaro Hirasawa

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

Recent advances in Learning Classifier Systems (LCSs) have shown their sequential decision-making ability with a generalization property. In this paper, a novel LCS named eXtended rule-based Genetic Network Programming (XrGNP) is proposed. Different from most of the current LCSs, the rules are represented and discovered through a graph-based evolutionary algorithm GNP, which consequently has the distinct expression ability to model and evolve the decision-making rules. XrGNP is described in details in which its unique features are explicitly mapped. Experiments on benchmark and real-world multi-step problems demonstrate the effectiveness of XrGNP.

本文言語English
ホスト出版物のタイトルProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
ページ1323-1328
ページ数6
DOI
出版ステータスPublished - 2013
イベント2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 - Manchester, United Kingdom
継続期間: 2013 10 132013 10 16

Other

Other2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
国/地域United Kingdom
CityManchester
Period13/10/1313/10/16

ASJC Scopus subject areas

  • 人間とコンピュータの相互作用

フィンガープリント

「A learning classifier system based on genetic network programming」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル