Symmetry Breaking for k-Robust Multi-Agent Path Finding

• URL: http://arxiv.org/abs/2102.08689v1
• Date: Wed, 17 Feb 2021 11:09:33 GMT
• Title: Symmetry Breaking for k-Robust Multi-Agent Path Finding
• Authors: Zhe Chen, Daniel Harabor, Jiaoyang Li, Peter J. Stuckey
• Abstract summary: k-Robust Conflict-BasedSearch (k-CBS) is an algorithm that produces coordinated and collision-free plan that is robust for up to k delays. We introduce a variety of pairwise symmetry breaking constraints, specific to k-robust planning, that can efficiently find compatible and optimal paths for pairs of conflicting agents.
• Score: 30.645303869311366
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: During Multi-Agent Path Finding (MAPF) problems, agents can be delayed by unexpected events. To address such situations recent work describes k-Robust Conflict-BasedSearch (k-CBS): an algorithm that produces coordinated and collision-free plan that is robust for up to k delays. In this work we introducing a variety of pairwise symmetry breaking constraints, specific to k-robust planning, that can efficiently find compatible and optimal paths for pairs of conflicting agents. We give a thorough description of the new constraints and report large improvements to success rate ina range of domains including: (i) classic MAPF benchmarks;(ii) automated warehouse domains and; (iii) on maps from the 2019 Flatland Challenge, a recently introduced railway domain where k-robust planning can be fruitfully applied to schedule trains.

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