Search-based optimal solvers for the multi-agent pathfinding problem: Summary and challenges

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

Search-based optimal solvers for the multi-agent pathfinding problem: Summary and challenges

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

Department of Computer Science

Research output: Contribution to conference › Paper › peer-review

148 Scopus citations

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.

Original language	English
Pages	29-37
Number of pages	9
State	Published - 2017
Event	10th Annual Symposium on Combinatorial Search, SoCS 2017 - Pittsburgh, United States Duration: 16 Jun 2017 → 17 Jun 2017

Conference

Conference	10th Annual Symposium on Combinatorial Search, SoCS 2017
Country/Territory	United States
City	Pittsburgh
Period	16/06/17 → 17/06/17

Bibliographical note

Publisher Copyright:
Copyright c 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Funding

This research was supported by Israel Science Foundation (ISF) grant #417/13 and by a joint grant of the Israel and Czech Ministries of Science #8G15027.

Funders	Funder number
Israel and Czech Ministries of Science	8G15027
Israel Science Foundation	417/13

Cite this

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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.",

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AU - Shimony, Solomon Eyal

AU - Boyarski, Eli

AU - Goldenberg, Meir

AU - Sharon, Guni

AU - Sturtevant, Nathan

AU - Wagner, Glenn

AU - Surynek, Pavel

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Search-based optimal solvers for the multi-agent pathfinding problem: Summary and challenges

Abstract

Conference

Bibliographical note

Funding

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Cite this