Conflict-Based Search For Optimal Multi-Agent Path Finding

Guni Sharon; Roni Stern; Ariel Felner; Nathan Sturtevant

Conflict-Based Search For Optimal Multi-Agent Path Finding

Guni Sharon, Roni Stern, Ariel Felner, Nathan Sturtevant

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

6 Scopus citations

Abstract

In the multi agent path finding problem (MAPF) paths should be found for several agents, each with a different start and goal position such that agents do not collide. Previous optimal solvers applied global A*-based searches. We present a new search algorithm called Conflict Based Search (CBS). CBS is a two-level algorithm. At the high level, a search is performed on a tree based on conflicts between agents. At the low level, a search is performed only for a single agent at a time. In many cases this reformulation enables CBS to examine fewer states than A* while still maintaining optimality. We analyze CBS and show its benefits and drawbacks. Experimental results on various problems shows a speedup of up to a full order of magnitude over previous approaches.

Original language	English
Pages	563-569
Number of pages	7
State	Published - 2012
Externally published	Yes
Event	26th AAAI Conference on Artificial Intelligence, AAAI 2012 - Toronto, Canada Duration: 22 Jul 2012 → 26 Jul 2012

Conference

Conference	26th AAAI Conference on Artificial Intelligence, AAAI 2012
Country/Territory	Canada
City	Toronto
Period	22/07/12 → 26/07/12

Bibliographical note

Publisher Copyright:
Copyright © 2012, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Funding

This research was supported by the Israeli Sience Foundation (ISF) under grant #305/09 to Ariel Felner.

Funders	Funder number
Israel Science Foundation	305/09

Cite this

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abstract = "In the multi agent path finding problem (MAPF) paths should be found for several agents, each with a different start and goal position such that agents do not collide. Previous optimal solvers applied global A*-based searches. We present a new search algorithm called Conflict Based Search (CBS). CBS is a two-level algorithm. At the high level, a search is performed on a tree based on conflicts between agents. At the low level, a search is performed only for a single agent at a time. In many cases this reformulation enables CBS to examine fewer states than A* while still maintaining optimality. We analyze CBS and show its benefits and drawbacks. Experimental results on various problems shows a speedup of up to a full order of magnitude over previous approaches.",

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Conflict-Based Search For Optimal Multi-Agent Path Finding

Abstract

Conference

Bibliographical note

Funding

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