Minimizing Fuel in Multi-Agent Pathfinding

The multi-agent pathfinding problem (MAPF) of finding conflict-free paths for multiple agents has attracted a large number of researchers in the past. The cost of the solution is commonly measured by the sum-of-costs (SOC) cost func tion or, less commonly, by Makespan. In this paper, we fo cus on the Fuel cost function, which is the number of phys ical steps the agents traverse. While Fuel was mentioned in many previous papers, our paper is the first to deepen into it. We introduce an A^*-based algorithm and a CBS-based algo rithm for Fuel. We study Fuel theoretically, showing that it is (perhaps non-intuitively) can be more complex than SOC. Finally, we experimentally compare both algorithms against each other and against their SOC counterparts, studying their advantages and disadvantages.