Abstract
Despite the significant progress in multi-agent communication decision, existing research does not address two important issues: 1) how to optimize timing and currency of communication when dealing with dynamically changing information, and 2) what kinds of communication decision interdependency exist in a team and how this interdependency impacts a single agent's communication decision. To provide a more comprehensive solution to the communication problem, we present a new model, DTPC (decision-theoretic proactive communication), which uses statistical analysis of information production and need of team members and a dynamic decision-theoretic determination of communication policies. We show experimentally how DTPC decreases communication load while improving performance of distributed teamwork.
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