Multi-agent pathfinding with continuous time

Anton Andreychuk, Konstantin Yakovlev, Dor Atzmon, Roni Sternr

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

59 Scopus citations


Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that every agent reaches its goal and the agents do not collide. Most prior work on MAPF was on grids, assumed agents' actions have uniform duration, and that time is discretized into timesteps. We propose a MAPF algorithm that does not rely on these assumptions, is complete, and provides provably optimal solutions. This algorithm is based on a novel adaptation of Safe interval path planning (SIPP), a continuous time single-agent planning algorithm, and a modified version of Conflict-based search (CBS), a state of the art multi-agent pathfinding algorithm. We analyze this algorithm, discuss its pros and cons, and evaluate it experimentally on several standard benchmarks.

Original languageEnglish
Title of host publicationProceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019
EditorsSarit Kraus
PublisherInternational Joint Conferences on Artificial Intelligence
Number of pages7
ISBN (Electronic)9780999241141
StatePublished - 2019
Externally publishedYes
Event28th International Joint Conference on Artificial Intelligence, IJCAI 2019 - Macao, China
Duration: 10 Aug 201916 Aug 2019

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823


Conference28th International Joint Conference on Artificial Intelligence, IJCAI 2019

Bibliographical note

Publisher Copyright:
© 2019 International Joint Conferences on Artificial Intelligence. All rights reserved.


This research is supported by ISF grants no. 210/17 to Roni Stern and by RSF grant no. 16-11-00048 to Konstantin Yakovlev and Anton Andreychuk.

FundersFunder number
Robert Schalkenbach Foundation16-11-00048
Israel Science Foundation210/17
Russian Science Foundation


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