| Item type |
デフォルトアイテムタイプ_（フル）(1) |
| 公開日 |
2023-03-18 |
| タイトル |
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|
タイトル |
An Evolutionary Multi-Objective Optimization-Based Constructive Method for Learning Classifier Systems Adjusting to Non-Markov Environments |
|
言語 |
en |
| 作成者 |
Moriwake, Keita
Katagiri, Hideki
Nishizaki, Ichiro
Hayashida, Tomohiro
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| アクセス権 |
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|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 権利情報 |
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|
権利情報 |
(c) Copyright by IEEE SMC Hiroshima Chapter. |
| 主題 |
|
|
主題Scheme |
NDC |
|
主題 |
500 |
| 内容記述 |
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|
内容記述 |
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. |
|
言語 |
en |
| 出版者 |
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|
出版者 |
IEEE SMC Hiroshima Chapter |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
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|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
|
資源タイプ |
conference paper |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 関連情報 |
|
|
|
識別子タイプ |
URI |
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|
関連識別子 |
http://www.hil.hiroshima-u.ac.jp/iwcia/2009/ |
| 収録物識別子 |
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|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
1883-3977 |
| 開始ページ |
|
|
開始ページ |
132 |
| 書誌情報 |
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
p. 132-136,
発行日 2009-11
|
| 旧ID |
28461 |
A1209.pdf (827.1 KB)
