Conflict-Based Increasing Cost Search

Thayne T. Walker, Nathan R. Sturtevant, Ariel Felner, Han Zhang, Jiaoyang Li, T. K.Satish Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Two popular optimal search-based solvers for the multi-agent pathfinding (MAPF) problem, Conflict-Based Search (CBS) and Increasing Cost Tree Search (ICTS), have been extended separately for continuous time domains and symmetry breaking. However, an approach to symmetry breaking in continuous time domains remained elusive. In this work, we introduce a new algorithm, Conflict-Based Increasing Cost Search (CBICS), which is capable of symmetry breaking in continuous time domains by combining the strengths of CBS and ICTS. Our experiments show that CBICS often finds solutions faster than CBS and ICTS in both unit time and continuous time domains.

Original languageEnglish
Title of host publication31st International Conference on Automated Planning and Scheduling, ICAPS 2021
EditorsSusanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo
PublisherAssociation for the Advancement of Artificial Intelligence
Pages385-395
Number of pages11
ISBN (Electronic)9781713832317
StatePublished - 1 Jan 2021
Event31st International Conference on Automated Planning and Scheduling, ICAPS 2021 - Guangzhou, Virtual, China
Duration: 2 Aug 202113 Aug 2021

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume2021-August
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Country/TerritoryChina
CityGuangzhou, Virtual
Period2/08/2113/08/21

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