Uncertain Knowledge Representation and Communicative Behavior in Coordinated Defense

This paper reports on results we obtained on communication among artiicial and human agents interacting in a simulated air defense domain. In our research, we postulate that the artiicial agents use a decision-theoretic method to select optimal communicative acts, given the characteristics of the particular situation. Thus, the agents we implemented compute the expected utilities of various alternative communicative acts, and execute the best one. The agents use a probabilistic frame-based knowledge formalism to represent the uncertain information they have about the domain and about the other agents present. We build on our earlier work that uses the Recursive Modeling Method (RMM) for coordination, and apply RMM to rational communication in an anti-air defense domain. In this domain, distributed units coordinate and communicate to defend a speciied territory from a number of attacking missiles. We measure the beneets of rational communication by showing the improvement in the quality of interactions the communication results in. We show how the beneet of rational communication measured after the interactions is related to the expected utilities of best messages computed before the interaction takes place. Further, we compare our results to improvement due to communication achieved by human subjects under the same circumstances.