J. Li, D. Harabor, P. Stuckey, H. Ma and S. Koenig. Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pages (in print), 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.

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