Decomposing Utility Functions in Bounded Max-sum for Distributed Constraint Optimization

Bounded Max-Sum is a message-passing algorithm for solving Distributed Constraint Optimization Problems (DCOP) able to compute solutions with a guaranteed approximation ratio. In this paper we show that the introduction of an intermediate step that decomposes functions may significantly improve its accuracy. This is especially relevant in critical applications (e.g. automatic surveillance, disaster response scenarios) where the accuracy of solutions is of vital importance.