The multi-agent pathfinding (MAPF) problem takes as input a set of agents with different starts and goals, and assigns a path that does not cause conflicts among the agents. There is a powerful exact algorithm called Meta-Agent Conflict Based Search (MA-CBS) for minimizing the sum of the costs for each agent to reach the goal, which is known to be NP-hard. The behavior of MA-CBS varies depending on a condition called the merge policy, but it is known that it requires a huge amount of execution time for some MAPF instances under the conventional static merge policy. In this paper, we propose a new merge policy that dynamically changes the properties of the algorithm, and show by computer experiments that the algorithm that implements the proposed merge policy runs efficiently on more various instances than the conventional one.
"},{"@language":"ja","@value":"マルチエージェント経路探索 (Multi-agent Pathfinding, MAPF) 問題は，それぞれ相異なるスタートとゴールが定められたエージェントの集合を入力とし，エージェント同士の衝突が発生しない経路の割当を解とする問題である．NP困難であることが知られている，各エージェントがゴールに到達するまでに要する時間の総和の最小化について，Meta-Agent Conflict Based Search (MA-CBS) と呼ばれる有力な厳密アルゴリズムが存在する．MA-CBS の動作は，マージポリシーと呼ばれる条件に応じて変化するが，従来用いられてきた静的なマージポリシーのもとでは，一部のMAPFインスタンスにおいて膨大な実行時間を要することが知られている．そこで本論文では，アルゴリズムの性質を動的に変化させる新たなマージポリシーを提案する．また，提案したマージポリシーを実装したアルゴリズムが，従来と比較して多様なインスタンスで効率的に動作することを計算機実験で示す．
"}],"abstractLicenseFlag":"disallow"}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1410855656024589312","@type":"Researcher","foaf:name":[{"@language":"en","@value":"SHIBATA Koshi"},{"@language":"ja","@value":"柴田 航志"}],"jpcoar:affiliationName":[{"@language":"ja","@value":"九州大学"},{"@language":"en","@value":"Kyushu University"}]},{"@id":"https://cir.nii.ac.jp/crid/1410855656024589315","@type":"Researcher","foaf:name":[{"@language":"en","@value":"KIMURA Kei"},{"@language":"ja","@value":"木村 慧"}],"jpcoar:affiliationName":[{"@language":"ja","@value":"九州大学"},{"@language":"en","@value":"Kyushu University"}]},{"@id":"https://cir.nii.ac.jp/crid/1410855656024589313","@type":"Researcher","foaf:name":[{"@language":"en","@value":"TODO Taiki"},{"@language":"ja","@value":"東藤 大樹"}],"jpcoar:affiliationName":[{"@language":"ja","@value":"九州大学"},{"@language":"en","@value":"Kyushu University"}]},{"@id":"https://cir.nii.ac.jp/crid/1410855656024589314","@type":"Researcher","foaf:name":[{"@language":"en","@value":"YOKOO Makoto"},{"@language":"ja","@value":"横尾 真"}],"jpcoar:affiliationName":[{"@language":"ja","@value":"九州大学"},{"@language":"en","@value":"Kyushu University"}]}],"publication":{"publicationIdentifier":[{"@type":"EISSN","@value":"27587347"}],"prism:publicationName":[{"@language":"en","@value":"Proceedings of the Annual Conference of JSAI"},{"@language":"ja","@value":"人工知能学会全国大会論文集"},{"@language":"en","@value":"Proc. of JSAI"},{"@language":"ja","@value":"JSAI大会論文集"}],"dc:publisher":[{"@language":"en","@value":"The Japanese Society for Artificial Intelligence"},{"@language":"ja","@value":"一般社団法人 人工知能学会"}],"prism:publicationDate":"2022","prism:volume":"JSAI2022","prism:number":"0","prism:startingPage":"1N1GS503","prism:endingPage":"1N1GS503"},"jpcoar:conferenceName":"2022年度人工知能学会全国大会（第36回）","jpcoar:conferencePlace":"京都国際会館＋オンライン","availableAt":"2022","foaf:topic":[{"@id":"https://cir.nii.ac.jp/all?q=%E3%83%9E%E3%83%AB%E3%83%81%E3%82%A8%E3%83%BC%E3%82%B8%E3%82%A7%E3%83%B3%E3%83%88%E3%82%B7%E3%82%B9%E3%83%86%E3%83%A0","dc:title":"マルチエージェントシステム"},{"@id":"https://cir.nii.ac.jp/all?q=%E3%83%9E%E3%83%AB%E3%83%81%E3%82%A8%E3%83%BC%E3%82%B8%E3%82%A7%E3%83%B3%E3%83%88%E7%B5%8C%E8%B7%AF%E6%8E%A2%E7%B4%A2","dc:title":"マルチエージェント経路探索"},{"@id":"https://cir.nii.ac.jp/all?q=multi-agent%20system","dc:title":"multi-agent system"},{"@id":"https://cir.nii.ac.jp/all?q=multi-agent%20pathfinding","dc:title":"multi-agent pathfinding"}],"dataSourceIdentifier":[{"@type":"JALC","@value":"oai:japanlinkcenter.org:2009724198"}]}