{"type":"ScholarlyArticle","title":"Multi-Agent Path Finding with Deadlines","authors":[{"name":"Hang Ma","slug":"hang-ma","given":"Hang","family":"Ma","affiliation":"University of Southern California"},{"name":"Glenn Wagner","slug":"glenn-wagner","given":"Glenn","family":"Wagner","affiliation":"CSIRO"},{"name":"Ariel Felner","slug":"ariel-felner","given":"Ariel","family":"Felner","affiliation":"Ben-Gurion University"},{"name":"Jiaoyang Li","slug":"jiaoyang-li","given":"Jiaoyang","family":"Li","affiliation":"University of Southern California"},{"name":"T. K. Satish Kumar","slug":"t-k-satish-kumar","given":"T. K. Satish","family":"Kumar","affiliation":"University of Southern California"},{"name":"Sven Koenig","slug":"sven-koenig","given":"Sven","family":"Koenig","affiliation":"University of Southern California"}],"abstract":"We formalize Multi-Agent Path Finding with Deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their given start vertices within the deadline, without colliding with each other. We first show that MAPF-DL is NP-hard to solve optimally. We then present two classes of optimal algorithms, one based on a reduction of MAPF-DL to a flow problem and a subsequent compact integer linear programming formulation of the resulting reduced abstracted multi-commodity flow network and the other one based on novel combinatorial search algorithms. Our empirical results demonstrate that these MAPF-DL solvers scale well and each one dominates the other ones in different scenarios.","doi":"10.24963/ijcai.2018/58","url":"https://ijcai.org/proceedings/2018/58","pdf":"https://ijcai.org/proceedings/2018/0058.pdf","markdown":"https://ijcai.org/proceedings/2018/58.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/58","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Agent-based and Multi-agent Systems","track":"Main track","number":58,"pages":{"first":417,"last":423},"keywords":["Agent-based and Multi-agent Systems: Multi-agent Planning","Heuristic Search and Game Playing: Combinatorial Search and Optimisation","Planning and Scheduling: Planning Algorithms","Planning and Scheduling: Search in Planning and Scheduling","Agent-based and Multi-agent Systems: Coordination and Cooperation","Planning and Scheduling: Planning and Scheduling"],"videos":[],"references":[{"position":1,"raw":"[Barer et al., 2014] M. 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