KOPT : Distributed DCOP Algorithm for Arbitrary k- optima with Monotonically Increasing Utility

Citation:

Hideaki Katagishi and Jonathan P. Pearce. 2007. “KOPT : Distributed DCOP Algorithm for Arbitrary k- optima with Monotonically Increasing Utility .” In Ninth Distributed Constraint Reasoning workshop (DCR).

Abstract:

A distributed constraint optimization problem (DCOP) is a formalism that captures the rewards and costs of local interactions within a team of agents. Because complete algorithms to solve DCOPs are unsuitable for some dynamic or anytime domains, researchers have explored incomplete DCOP algorithms that result in locally optimal solutions. One type of categorization of such algorithms, and the solutions they produce, is k-optimality; a k-optimal solution is one that cannot be improved by any deviation by k or fewer agents. There are no k-optimal algorithms (k>3) so far. In addition, the quality of solution existing algorithm can produce is fixed. We need different algorithms for different optimality. This paper introduces the first DCOP algorithm which can produce arbitrary k-optimal solutions.
See also: 2007