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Conflict-Based Search For Optimal Multi-Agent Path Finding

Guni Sharon, Roni Stern, Ariel Felner, Nathan Sturtevant

2021Proceedings of the AAAI Conference on Artificial Intelligence85 citationsDOIOpen Access PDF

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.

Topics & Concepts

SpeedupPath (computing)Computer scienceTree (set theory)Search treeMathematical optimizationPosition (finance)Search problemOrder (exchange)Search algorithmBidirectional searchBeam searchAlgorithmBest-first searchMathematicsParallel computingEconomicsMathematical analysisFinanceProgramming languageRobotic Path Planning AlgorithmsMetaheuristic Optimization Algorithms ResearchAI-based Problem Solving and Planning