Probabilistic optimal solution assessment for DCOPs

Abstract

Distributed Constraint Optimization Problems (DCOPs) are widely used in Multi-Agent Systems for coordination and scheduling. The present paper proposes a heuristic algorithm that uses probabilistic assessment of the optimal solution in order to quickly find a solution that is not far from the optimal one. The heuristic assessment uses two passes by the agents to produce a high-quality solution. Extensive performance evaluation demonstrates that the solution of the proposed probabilistic assessment algorithm is indeed very close to the optimum, on smaller problems where this could be measured. In larger set-ups, the quality of the solution is demonstrated relatively to standard incomplete search algorithms.