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A desirable goal for autonomous agents is to be able to coordinate on the flywith previously unknown teammates. Known as "ad hoc teamwork", enabling such acapability has been receiving increasing attention in the research community.One of the central challenges in ad hoc teamwork is quickly recognizing thecurrent plans of other agents and planning accordingly. In this paper, we focuson the scenario in which teammates can communicate with one another, but onlyat a cost. Thus, they must carefully balance plan recognition based onobservations vs. that based on communication. This paper proposes a new metricfor evaluating how similar are two policies that a teammate may be following -the Expected Divergence Point (EDP). We then present a novel planning algorithmfor ad hoc teamwork, determining which query to ask and planning accordingly.We demonstrate the effectiveness of this algorithm in a range of increasinglygeneral communication in ad hoc teamwork problems.

Expected Value of Communication for Planning in Ad Hoc Teamwork