Symmetry Breaking for k-Robust Multi-Agent Path Finding
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.
Cite
@article{arxiv.2102.08689,
title = {Symmetry Breaking for k-Robust Multi-Agent Path Finding},
author = {Zhe Chen and Daniel Harabor and Jiaoyang Li and Peter J. Stuckey},
journal= {arXiv preprint arXiv:2102.08689},
year = {2021}
}
Comments
8 pages. Accepted by Thirty-Fifth AAAI Conference on Artificial Intelligence