{"created":"2025-01-18T23:03:45.420951+00:00","updated":"2025-01-22T14:43:04.193480+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00035411","sets":["1164:2836:2900:2906"]},"path":["2906"],"owner":"1","recid":"35411","title":["分散協調型強化学習によるリフレクティブエージェントの性能評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"1997-01-30"},"_buckets":{"deposit":"2036e35a-c975-493a-b363-1a57076e3d52"},"_deposit":{"id":"35411","pid":{"type":"depid","value":"35411","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"分散協調型強化学習によるリフレクティブエージェントの性能評価","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"分散協調型強化学習によるリフレクティブエージェントの性能評価"},{"subitem_title":"Ability Evaluation of Reflective Agent Based on the Distributed and Cooperative Reinforcement Learning","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"1997-01-30","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"金沢工業大学情報工学科"},{"subitem_text_value":"金沢工業大学情報工学科"},{"subitem_text_value":"金沢工業大学情報工学科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kanazawa Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Kanazawa Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Kanazawa Institute of Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/35411/files/IPSJ-DPS96080022.pdf"},"date":[{"dateType":"Available","dateValue":"1999-01-30"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DPS96080022.pdf","filesize":[{"value":"610.9 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"34"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"90b9cff3-945b-4560-8ba4-d7bb8b552f33","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 1997 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"阿部, 倫之"},{"creatorName":"中沢, 実"},{"creatorName":"服部, 進実"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Noriyuki, Abe","creatorNameLang":"en"},{"creatorName":"Minoru, Nakazawa","creatorNameLang":"en"},{"creatorName":"Shimmi, Hattori","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10116224","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Telescriptなどのモーバイルエージェントシステムは，ユーザの要求記述に基づいて広域ネットワーク上を移動しながら必要な行為を連続適用していくメカニズムを持っている．このエージェントの動作シナリオは，事前に全て記述する必要があるため，動的な環境変化を予測した記述をするのは困難である．本稿では，非決定的な動作シナリオをコンセプトと強度付きプロダクションルールで記述し，分散ルール強化学習メカニズムと分散ルール協調メカニズムによって動作シナリオを改変していくリフレクティブマルチエージェントシステムMAS/Rを提案している．また，CLOSを用いて評価システムを実装し，MAS/Rの適用能力を評価した．その結果，リフレクション（強化学習）を繰り返すことよって不適切なルールが淘汰され，環境変動に適応するように動作シナリオが改変されることを確認した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Mobile agent system like Telescript in distributed computing environment has the mechanism in which required actions are applied one after another according to users described scenario, moving agents on wide area network. However, it seems to be difficult to respond to open and dynamic network environment, because action scenario of agent behavior has to include all description of it prior to execution of agents. In this paper, reflective multi-agent system MAS/R which can autonomously change scenario of behavior by mechanism of distributed rule reinforcement learning and cooperation, describing behavior scenario of agent by concepts and production rules with strength, is proposed. This system connected to multi-server load simulator has been implemented and evaluated. As the result of it, behavior sccnario of agents has been confirmed to be autonomously changed to adopt to dynamic environment, selecting appropriate rules by repeating reflection.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"132","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告マルチメディア通信と分散処理（DPS）"}],"bibliographicPageStart":"127","bibliographicIssueDates":{"bibliographicIssueDate":"1997-01-30","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"13(1996-DPS-080)","bibliographicVolumeNumber":"1997"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":35411,"links":{}}