{"id":224871,"updated":"2025-01-19T12:59:30.567914+00:00","links":{},"created":"2025-01-19T01:24:25.894454+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00224871","sets":["1164:4402:11197:11205"]},"path":["11205"],"owner":"44499","recid":"224871","title":["マルチエージェント多目的強化学習における各エージェントが重視する報酬の違いによる自律的機能分化 "],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-26"},"_buckets":{"deposit":"c072f3b3-218d-4eb9-919f-8c28d6985124"},"_deposit":{"id":"224871","pid":{"type":"depid","value":"224871","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"マルチエージェント多目的強化学習における各エージェントが重視する報酬の違いによる自律的機能分化 ","author_link":["594014","594013"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"マルチエージェント多目的強化学習における各エージェントが重視する報酬の違いによる自律的機能分化 "}]},"item_type_id":"4","publish_date":"2023-02-26","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東洋大学"},{"subitem_text_value":"東洋大学"}]},"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/224871/files/IPSJ-ICS23209008.pdf","label":"IPSJ-ICS23209008.pdf"},"date":[{"dateType":"Available","dateValue":"2025-02-26"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ICS23209008.pdf","filesize":[{"value":"1.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"25"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"acb6ffa7-b963-45ae-a4fe-32de636d09bf","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"田中, 優暉"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山田, 和明"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11135936","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_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-885X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"強化学習には，報酬は設計者の知識や経験に依存してしまい，報酬を適切に設計することは困難であるという課題がある．そこで，報酬に重み付けをしなくても適切な学習をすることに成功すれば，設計者の負担を軽減できると考えた．本研究では，狭路すれ違い問題において，報酬に重みを付けない場合の tMAC の学習性能について検証した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告知能システム（ICS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-26","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicVolumeNumber":"2023-ICS-209"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}