A Search Method for Reducing Local Cost in Distributed Constraint Optimization Problem

M. Noto, D. Hashimoto, and M. Matsuda (Japan)


distributed constraint optimization problem, asynchronous search, intelligent agent, local load


A distributed constraint optimization problem (DCOP) dis tributes the variables and constraints among intelligent agents to enable it to be treated as a constraint satisfaction problem. In this paper, we propose a search method based on the asynchronous distributed optimization (Adopt) algo rithm that has been proposed for DCOP. Adopt is a com plete method based on a depth-first-search, and operates asynchronously to find the optimal solution for the overall cost. We propose a distributed search method that builds on the merits of Adopt by considering the local load of each agent as opposed to overall optimization. The effect of the proposal was evaluated in simulations.

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