Author:
Felner Ariel,Stern Roni,Shimony Solomon,Boyarski Eli,Goldenberg Meir,Sharon Guni,Sturtevant Nathan,Wagner Glenn,Surynek Pavel
Abstract
Multi-agent pathfinding (MAPF) is an area of expanding research interest. At the core of this research area, numerous diverse search-based techniques were developed in the past 6 years for optimally solving MAPF under the sum-of-costs objective function. In this paper we survey these techniques, while placing them into the wider context of the MAPF field of research. Finally, we provide analytical and experimental comparisons that show that no algorithm dominates all others in all circumstances. We conclude by listing important future research directions.
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Cited by
26 articles.
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