Analyzing Myopic Approaches for Multi-Agent Communication
Raphen Becker
Victor Lesser
Shlomo Zilberstein
Abstract
Choosing when to communicate is a fundamental problem
in multi-agent systems. This problem becomes particularly
hard when communication is constrained and each
agent has different partial information about the overall situation.
Although computing the exact value of communication
is intractable, it has been estimated using a standard
myopic assumption. However, this assumption--that communication
is only possible at the present time--introduces
error that can lead to poor agent behavior. We examine
specific situations in which the myopic approach performs
poorly and demonstrate an alternate approach that relaxes
the assumption to improve the performance. The results
provide an effective method for value-driven communication
policies in multi-agent systems.
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