An efficient algorithm for multiagent plan coordination

Abstract

The multiagent plan coordination problem arises whenever multiple agents plan to achieve their individual goals independently, but might mutually benefit by coordinating their plans to avoid working at cross purposes or duplicating effort. Although variations of this problem have been studied in the literature, there is as yet no agreement over a general characterization of the problem. In this paper, we describe a general framework that extends the partial-order, causal-link plan representation to the multiagent case, and that treats coordination as a form of iterative repair of plan flaws that cross agents. We show, analytically and empirically, that this algorithmic formulation can scale to the multiagent case better than can a straightforward application of the most advanced single-agent plan coordination technique, highlighting fundamental differences between single-agent and multiagent planning.