このエントリーをはてなブックマークに追加
ID 25646
本文ファイル
著者
Nishimura, Tokue
Handa, Hisashi
NDC
技術・工学
抄録(英)
Cognitive Agents must be able to decide their actions based on their recognized states. In general, learning mechanisms are equipped for such agents in order to realize intellgent behaviors. In this paper, we propose a new Estimation of Distribution Algorithms (EDAs) which can acquire effective rules for cognitive agents. Basic calculation procedure of the EDAs is that 1) select better individuals, 2) estimate probabilistic models, and 3) sample new individuals. In the proposed method, instead of the use of individuals, input-output records in episodes are directory used for estimating the probabilistic model by Conditional Random Fields. Therefore, estimated probabilistic model can be regarded as policy so that new input-output records are generated by the interaction between the policy and environments. Computer simulations on Probabilistic Transition Problems show the effectiveness of the proposed method.
掲載誌名
Fourth International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2008
開始ページ
185
終了ページ
190
出版年月日
2008-12
出版者
IEEE SMC Hiroshima Chapter
ISSN
1883-3977
言語
英語
NII資源タイプ
会議発表論文
広大資料タイプ
会議発表論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
publisher
権利情報
(c) Copyright by IEEE SMC Hiroshima Chapter.
部局名
工学研究科