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


  • Jiaoyang Li University of Southern California
  • Daniel Harabor Monash University
  • Peter J. Stuckey The University of Melbourne
  • Hang Ma University of Southern California
  • Sven Koenig University of Southern California



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.




How to Cite

Li, J., Harabor, D., Stuckey, P. J., Ma, H., & Koenig, S. (2019). Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 6087-6095.



AAAI Technical Track: Multiagent Systems