ID | 19655 |
Eprint ID | 19655
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フルテキストURL | |
著者 |
Moriwake Keita
Hiroshima University
Katagiri Hideki
Hiroshima University
Nishizaki Ichiro
Hiroshima University
Hayashida Tomohiro
Hiroshima University
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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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発行日 | 2009-11-12
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出版物タイトル |
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
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巻 | 2009巻
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号 | 1号
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出版者 | IEEE SMC Hiroshima Chapter
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開始ページ | 132
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終了ページ | 136
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ISSN | 1883-3977
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NCID | BB00577064
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資料タイプ |
会議発表論文
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言語 |
英語
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著作権者 | IEEE SMC Hiroshima Chapter
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イベント | 5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
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イベント地 | 東広島市
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イベント地の別言語 | Higashi-Hiroshima City
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論文のバージョン | publisher
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査読 |
有り
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Eprints Journal Name | IWCIA
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