Adding heuristics to conflict-based search for multi-agent path finding

Ariel Felner, Jiaoyang Li, Eli Boyarski, Hang Ma, Liron Cohen, T. K.Satish Kumar, Sven Koenig

Research output: Contribution to journalConference articlepeer-review

118 Scopus citations

Abstract

Conflict-Based Search (CBS) and its enhancements are among the strongest algorithms for the multi-agent path-finding problem. However, existing variants of CBS do not use any heuristics that estimate future work. In this paper, we introduce different admissible heuristics for CBS by aggregating cardinal conflicts among agents. In our experiments, CBS with these heuristics outperforms previous state-of-the-art CBS variants by up to a factor of five.

Original languageEnglish
Pages (from-to)83-87
Number of pages5
JournalProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume2018-June
StatePublished - 2018
Externally publishedYes
Event28th International Conference on Automated Planning and Scheduling, ICAPS 2018 - Delft, Netherlands
Duration: 24 Jun 201829 Jun 2018

Bibliographical note

Publisher Copyright:
Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Funding

The research at Ben-Gurion University was supported by the Israel Ministry of Science and the Czech Ministry of Education and by Israel Science Foundation grant 844/17. The research at the University of Southern California was supported by National Science Foundation grants 1724392, 1409987 and 1319966. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the sponsoring organizations, agencies or the U.S. government.

FundersFunder number
Israel Ministry of Science
National Science Foundation1409987, 1724392, 1319966
University of Southern California
Ministerstvo Školství, Mládeže a Tělovýchovy
Israel Science Foundation844/17
Ben-Gurion University of the Negev

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