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Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges

Authors

Ariel Felner,Roni Stern,Solomon Shimony,Eli Boyarski,Meir Goldenberg,Guni Sharon,Nathan Sturtevant,Glenn Wagner,Pavel Surynek

Ben-Gurion University of the Negev,Ben-Gurion University of the Negev,Ben-Gurion University of the Negev,Bar-Ilan University,The Jerusalem College of Technology,The University of Texas at Austin,The University of Denver,Carnegie Mellon University,National Institute of Advanced Industrial Science and Technology


Proceedings:

Proceedings of the International Symposium on Combinatorial Search, 10

Volume

Issue:

Vol. 10 No. 1 (2017): Tenth Annual Symposium on Combinatorial Search

Track:

Long Papers

Downloads:

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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.

DOI:

10.1609/socs.v8i1.18423


SOCS

Vol. 10 No. 1 (2017): Tenth Annual Symposium on Combinatorial Search