An Evolutionary Multi-Objective Optimization-Based Constructive Method for Learning Classifier Systems Adjusting to Non-Markov Environments
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
132-136 頁
2009-11 発行
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この文献の参照には次のURLをご利用ください : https://ir.lib.hiroshima-u.ac.jp/00028461
| ファイル情報(添付) | |
| タイトル ( eng ) |
An Evolutionary Multi-Objective Optimization-Based Constructive Method for Learning Classifier Systems Adjusting to Non-Markov Environments
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| 作成者 |
Moriwake Keita
Nishizaki Ichiro
Hayashida Tomohiro
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| 収録物名 |
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
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| 開始ページ | 132 |
| 終了ページ | 136 |
| 抄録 |
Learning Classifier Systems (LCSs) are rule-based systems that automatically build their rule set so as to get optimal policies through evolutionary processes. This paper considers an evolutionary multi-objective optimization-based constructive method for LCSs that adjust to non-Markov environments. Our goal is to construct a XCSMH (eXtended Classifier System - Memory Hierarchic) that can obtain not only optimal policies but also highly generalized rule sets. Results of numerical experiments show that the proposed method is superior to an existing method with respect to the generality of the obtained rule sets.
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| NDC分類 |
技術・工学 [ 500 ]
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| 言語 |
英語
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| 資源タイプ | 会議発表論文 |
| 出版者 |
IEEE SMC Hiroshima Chapter
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| 発行日 | 2009-11 |
| 権利情報 |
(c) Copyright by IEEE SMC Hiroshima Chapter.
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| 出版タイプ | Version of Record（出版社版。早期公開を含む） |
| アクセス権 | オープンアクセス |
| 収録物識別子 |
[ISSN] 1883-3977
[URI] http://www.hil.hiroshima-u.ac.jp/iwcia/2009/
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