Expected Value of Communication for Planning in Ad Hoc Teamwork


  • William Macke University of Texas at Austin
  • Reuth Mirsky University of Texas at Austin
  • Peter Stone University of Texas at Austin and Sony AI




Teamwork, Activity and Plan Recognition, Adversarial Agents


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




How to Cite

Macke, W., Mirsky, R., & Stone, P. (2021). Expected Value of Communication for Planning in Ad Hoc Teamwork. Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11290-11298. https://doi.org/10.1609/aaai.v35i13.17346



AAAI Technical Track on Multiagent Systems