AbstractF. Fioretto, H. Xu, S. Koenig and S. Kumar. Solving Multiagent Constraint Optimization Problems on the Constraint Composite Graph. In Proceedings of the International Conference on Principles and Practice of Multi-Agent Systems (PRIMA), pages 106-122, 2018.
Abstract: We introduce the Constraint Composite Graph (CCG) for Distributed Constraint Optimization Problems (DCOPs), a popular paradigm used for the description and resolution of cooperative multi-agent problems. The CCG is a novel graphical representation of DCOPs on which agents can coordinate their assignments to solve the distributed problem suboptimally. By leveraging this representation, agents are able to reduce the size of the problem. We propose a novel variant of Max-Sum - a popular DCOP incomplete algorithm - called CCG-Max-Sum, which is applied to CCGs, and demonstrate its efficiency and effectiveness on DCOP benchmarks based on several network topologies.
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