Abstract

F. Fioretto, H. Xu, S. Koenig and S. Kumar. Solving Multiagent Constraint Optimization Problems on the Constraint Composite Graph. In Proceedings of the AAMAS-14 International Joint Workshop on Optimisation in Multi-Agent Systems and Distributed Constraint Reasoning (OptMAS-DCR), 2018.

Abstract: The Distributed Constraint Optimization Problem (DCOP) offers a powerful approach for the description and resolution of cooperative multi-agent problems. In this model, a group of agents coordinates their actions to optimize a global objective function, taking into account their local preferences. In the majority of DCOP algorithms, agents operate on three main graphical representations of the problem: (a) the constraint graph, (b) the pseudo-tree, or (c) the factor graph. In this paper, we introduce the Constraint Composite Graph (CCG) for DCOPs, an alternative graphical representation 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-MaxSum, which is applied to CCGs. We also demonstrate the efficiency and effectiveness of CCG-Max-Sum on DCOP benchmarks based on several network topologies.

Download the paper in pdf.

Many publishers do not want authors to make their papers available electronically after the papers have been published. Please use the electronic versions provided here only if hardcopies are not yet available. If you have comments on any of these papers, please send me an email! Also, please send me your papers if we have common interests.


This page was automatically created by a bibliography maintenance system that was developed as part of an undergraduate research project, advised by Sven Koenig.