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The Multi-Agent Planning Problem

The purpose of this paper is to present a Multi-Agent planner for a team of autonomous agents. The approach is demonstrated by the Multi-Agent Planning Problem, which is a variant of the classical Multiple Traveling Salesmen Problem (MTSP): given a set of n goals/targets and a team of m agents, the optimal team strategy consists of findingm tours such that each target is visited only once and by only one agent, and the total cost of visiting all nodes is minimal. The proposed solution method is a Genetic Algorithm Inspired Steepest Descent (GAISD) method. To validate the approach, the method has been benchmarked against MTSPs and routing problems. Numerical experiments demonstrate the goodness of the approach.