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A Polynomial-Time Algorithm for Non-Optimal Multi-Agent Pathfinding

Mokhtar Khorshid, Robert C. Holte, Nathan Sturtevant

2021Proceedings of the International Symposium on Combinatorial Search64 citationsDOIOpen Access PDF

Abstract

Multi-agent pathfinding, where multiple agents must travel to their goal locations without getting stuck, has been studied in both theoretical and practical contexts, with a variety of both optimal and sub-optimal algorithms proposed for solving problems. Recent work has shown that there is a linear-time check for whether a multi-agent pathfinding problem can be solved in a tree, however this was not used to actually produce solutions. In this paper we provide a constructive proof of how to solve multi-agent pathfinding problems in a tree that culminates in a novel approach that we call the tree-based agent swapping strategy (TASS). Experimental results showed that TASS can find solutions to the multi-agent pathfinding problem on a highly crowded tree with 1000 nodes and 996 agents in less than 8 seconds. These results are far more efficient and general than existing work, suggesting that TASS is a productive line of study for multi-agent pathfinding.

Topics & Concepts

PathfindingTree (set theory)Computer scienceTime complexityVariety (cybernetics)ConstructiveAlgorithmMathematical optimizationTheoretical computer scienceMathematicsArtificial intelligenceShortest path problemProcess (computing)CombinatoricsGraphProgramming languageRobotic Path Planning AlgorithmsAI-based Problem Solving and PlanningMulti-Agent Systems and Negotiation
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