Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering
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We introduce multi-goal multi agent path finding (MAPF^MG) which generalizes the standard discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigate agents in an undirected graph from their starting vertices to one individual goal vertex per agent, MAPF^MG assigns each agent multiple goal vertices and the task is to visit each of them at least once. Solving MAPF^MG not only requires finding collision free paths for individual agents but also determining the order of visiting agent's goal vertices so that common objectives like the sum-of-costs are optimized. We suggest two novel algorithms using different paradigms to address MAPF^MG: a heuristic search-based search algorithm called Hamiltonian-CBS (HCBS) and a compilation-based algorithm built using the SMT paradigm, called SMT-Hamiltonian-CBS (SMT-HCBS). Experimental comparison suggests limitations of compilation-based approach.
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