This work focuses on solving DCOPs in communication constrained scenarios.
GDL is a well-known algorithm to optimally solve DCOP problems, that
requires the exchange of exponentially large messages. Function filtering
is a technique that alleviates this high communication requirement while
maintaining optimality. Specifically, function filtering involves
calculating approximations of the exact cost functions exchanged by GDL.
In this work, we explore different ways to compute such approximations,
providing a novel method that empirically achieves significant
communication savings.