Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding - Robotics Institute Carnegie Mellon University

Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding

Jiaoyang Li, Daniel Harabor, Peter J. Stuckey, Hang Ma, and Sven Koenig
Conference Paper, Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI '19), pp. 6087 - 6095, January, 2019

Abstract

We describe a new way of reasoning about symmetric collisions for Multi-Agent Path Finding (MAPF) on 4-neighbor grids. We also introduce a symmetry-breaking constraint to resolve these conflicts. This specialized technique allows us to identify and eliminate, in a single step, all permutations of two currently assigned but incompatible paths. Each such permutation has exactly the same cost as a current path, and each one results in a new collision between the same two agents. We show that the addition of symmetry-breaking techniques can lead to an exponential reduction in the size of the search space of CBS, a popular framework for MAPF, and report significant improvements in both runtime and success rate versus CBSH and EPEA* – two recent and state-of-the-art MAPF algorithms.

BibTeX

@conference{Li-2019-131434,
author = {Jiaoyang Li and Daniel Harabor and Peter J. Stuckey and Hang Ma and Sven Koenig},
title = {Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding},
booktitle = {Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI '19)},
year = {2019},
month = {January},
pages = {6087 - 6095},
}