Efficient Methods for Pseudo-tree Based Distributed Best First Search

Abstract— Distributed constraint optimization problem is an area of research in multi agent system. In recent years, a distributed constraint optimization algorithm, which performs best-first search in bottom up manner according to pseudo tree, was proposed. In this paper, we propose several efficient methods for the distributed bottom up best-first search. Derivation of partial solution is introduced to decrease number of backtracking among agents, Synchronization control method is applied to decrease number of communication message cycles. Additionally, error bounds are applied to obtain quasi optimal solution within less number of message cycles. Results of experiments are shown for the efficiency evaluation of the proposed heuristics methods.