JOURNAL ARTICLE

Conflict-Based Search For Optimal Multi-Agent Path Finding

Guni SharonRoni SternAriel FelnerNathan Sturtevant

Year: 2021 Journal:   Proceedings of the AAAI Conference on Artificial Intelligence Vol: 26 (1)Pages: 563-569   Publisher: Association for the Advancement of Artificial Intelligence

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.

Keywords:
Speedup Path (computing) Computer science Tree (set theory) Search tree Mathematical optimization Position (finance) Search problem Order (exchange) Search algorithm Bidirectional search Beam search Algorithm Best-first search Mathematics Parallel computing

Metrics

80
Cited By
1.96
FWCI (Field Weighted Citation Impact)
20
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robotic Path Planning Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
AI-based Problem Solving and Planning
Physical Sciences →  Computer Science →  Artificial Intelligence

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