Abstract
The main idea of conflict-based search (CBS), a popular, state-of-the-art algorithm for multi-agent pathfinding is to resolve conflicts between agents by systematically adding constraints to agents. Recently, CBS has been adapted for new domains and variants, including non-unit costs and continuous time settings. These adaptations require new types of constraints. This paper introduces a new automatic constraint generation technique called bipartite reduction (BR). BR converts the constraint generation step of CBS to a surrogate bipartite graph problem. The properties of BR guarantee completeness and optimality for CBS. Also, BR’s properties may be relaxed to obtain suboptimal solutions. Empirical results show that BR yields significant speedups in 2k connected grids over the previous state-of-the-art for both optimal and suboptimal search.
Original language | English |
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Title of host publication | AAAI 2020 - 34th AAAI Conference on Artificial Intelligence |
Publisher | AAAI press |
Pages | 7277-7284 |
Number of pages | 8 |
ISBN (Electronic) | 9781577358350 |
DOIs | |
State | Published - 2020 |
Externally published | Yes |
Event | 34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States Duration: 7 Feb 2020 → 12 Feb 2020 |
Publication series
Name | AAAI 2020 - 34th AAAI Conference on Artificial Intelligence |
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Conference
Conference | 34th AAAI Conference on Artificial Intelligence, AAAI 2020 |
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Country/Territory | United States |
City | New York |
Period | 7/02/20 → 12/02/20 |
Bibliographical note
Publisher Copyright:Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Funding
We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC) and support from BSF grant #2017692, NSF grant #1815660 and Lockheed Martin Corp.
Funders | Funder number |
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Lockheed Martin Corp | |
National Science Foundation | 1815660 |
Bonfils-Stanton Foundation | 2017692 |
Natural Sciences and Engineering Research Council of Canada |