{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232677","sets":["1164:4402:11550:11551"]},"path":["11551"],"owner":"44499","recid":"232677","title":["分散強化学習によるLifelong MAPF解決手法における近隣エージェントとの情報共有の改善"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-22"},"_buckets":{"deposit":"92f01661-6e90-4407-9e99-7a808dc10d43"},"_deposit":{"id":"232677","pid":{"type":"depid","value":"232677","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"分散強化学習によるLifelong MAPF解決手法における近隣エージェントとの情報共有の改善","author_link":["630482","630483"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"分散強化学習によるLifelong MAPF解決手法における近隣エージェントとの情報共有の改善"}]},"item_type_id":"4","publish_date":"2024-02-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"早稲田大学基幹理工学部情報理工学科"},{"subitem_text_value":"早稲田大学基幹理工学部情報理工学科"}]},"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/232677/files/IPSJ-ICS24212004.pdf","label":"IPSJ-ICS24212004.pdf"},"date":[{"dateType":"Available","dateValue":"2026-02-22"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ICS24212004.pdf","filesize":[{"value":"1.6 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":"87184a55-a0f8-41c7-a751-c16e98348d59","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"藤澤, 陽祐"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"菅原, 俊治"}],"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":"本稿では，Lifelong Multi-Agent Path Finding（Lifelong MAPF）問題を解決する分散深層強化学習（distributed deep reinforcement learning, DDRL）を利用した PRIMAL2 におけるエージェント間の情報共有を拡張し，単位時間あたりの目標地点への到達効率を向上させる手法を提案する．Lifelong MAPF 問題とは，複数エージェントが継続的に割り当てられる目標地点を目指して，障害物や他のエージェントとの衝突を回避しつつ経路探索と移動を繰り返す問題である．この問題は様々な状況に適用可能で，例えば，空港の運用や自動倉庫，遭難救助などが挙げられる．そのため Lifelong MAPF 問題の既存手法は数多く存在するが，なかでも DDRL を利用した手法はエージェント数が増加しても実用的な計算時間で経路計画が可能な点で有効である．本研究では既存の DDRL を利用した Lifelong MAPF 解決手法である PRIMAL2 を拡張し，近隣エージェントとの情報共有を拡大し，そのエージェントの周辺の環境や他のエージェントの情報を得ることを提案する．実験結果から，単純に既存手法で視野を広げたものと比較して，目標地点への到達効率を改善できることを確認し，その理由について議論する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告知能システム（ICS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-02-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"2024-ICS-212"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":232677,"updated":"2025-01-19T10:21:25.104097+00:00","links":{},"created":"2025-01-19T01:33:40.906413+00:00"}