S. Ali, S. Koenig and M. Tambe. Preprocessing Techniques for Accelerating the DCOP Algorithm ADOPT. In International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 1041-1048, 2005.

Abstract: Methods for solving Distributed Constraint Optimization Problems (DCOP) have emerged as key techniques for distributed reasoning. Yet, their application faces significant hurdles in many multiagent domains due to their inefficiency. Preprocessing techniques have successfully been used to speed up algorithms for centralized constraint satisfaction problems. This paper introduces a framework of different preprocessing techniques that are based on dynamic programming and speed up ADOPT, an asynchronous complete and optimal DCOP algorithm. We investigate when preprocessing is useful and which factors influence the resulting speedups in two DCOP domains, namely graph coloring and distributed sensor networks. Our experimental results demonstrate that our preprocessing techniques are fast and can speed up ADOPT by an order of magnitude.

Download the paper in pdf.

Download the paper in gzipped postscript (large download time).

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.