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P. Surynek. Multi-Agent Path Finding with Generalized Conflicts: An Experimental Study. In Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), pages 118-142, 2019.
Abstract: This paper gives an overview of conflict reasoning in generalizations of multi-agent path finding (MAPF). MAPF and derived variants assume items placed in vertices of an undirected graph with at most one item per vertex. Items can be relocated across edges while various constraints depending on the concrete type of relocation problem must be satisfied. We recall a general problem formulation that encompasses known types of item relocation problems such as multi-agent path finding (MAPF), token swapping (TSWAP), token rotation (TROT), and token permutation (TPERM). We then focused on three existing optimal algorithms for MAPF: search-based CBS, and propositional satisfiability (SAT)-based MDD-SAT and SMT-CBS. These algorithms were modified to tackle various types of conflicts. The major contribution of this paper is a thorough experimental evaluation of CBS, MDD-SAT, and SMT-CBS on various types of relocation problems.