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Learn all about Multi-Agent Path Finding (MAPF)

Publication

D. Atzmon, Y. Zax, E. Kivity, L. Avitan, J. Morag and A. Felner. Generalizing Multi-Agent Path Finding for Heterogeneous Agents. In Proceedings of the International Symposium on Combinatorial Search (SoCS), pages 101-105, 2020.


Abstract: Multi-Agent Path Finding (MAPF) is the problem of finding non-colliding paths for multiple agents. The classical problem assumes that all agents are homogeneous, with a fixed size and behavior. However, in reality agents are heterogeneous, with different sizes and behaviors. In this paper, we generalize MAPF to G-MAPF for the case of heterogeneous agents. We then show how two previous settings of large agents and k-robust agents are special cases of G-MAPF. Finally, we introduce G-CBS, a variant of the Conflict-Based Search (CBS) algorithm for G-MAPF, which does not cause significant extra overhead.


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(last updated in 2022)