ANALYZING MYOPIC APPROACHES FOR MULTI-AGENT COMMUNICATION

Choosing when to communicate is a fundamental problem in multi-agent systems. This problem becomes particularly challenging when communication is constrained and each agent has different partial information about the overall situation. We take a decision-theoretic approach to this problem that balances the benefits of communication against the costs. Although computing the exact value of communication is intractable, it can be estimated using a standard myopic assumption-that communication is only possible at the present time. We examine specific situations in which this assumption leads to poor performance and demonstrate an alternative approach that relaxes the assumption and improves performance. The results provide an effective method for value-driven communication policies in multi-agent systems.