A search method for reducing local cost in distributed constraint optimization problem

Authors:
Masato Noto;Daiki Hashimoto;Mitsutoshi Matsuda
Affiliations:
Kanagawa University, Yokohama, Japan;Kanagawa University, Yokohama, Japan;Kanagawa University, Yokohama, Japan
Venue:
ACST'07 Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology
Year:
2007

Citing 6
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Artificial Intelligence - Special issue: Distributed constraint satisfaction

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Abstract

A distributed constraint optimization problem (DCOP) distributes 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) algorithm that has been proposed for DCOP. Adopt is a complete 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.