Asynchronous forward-bounding for distributed constraints optimization

Amir Gershman, Amnon Meisels, Roie Zivan

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

25 Scopus citations

Abstract

A new search algorithm for solving distributed constraint optimization problems (DisCOPs) is presented. Agents assign variables sequentially and propagate their assignments asynchronously. The asynchronous forward-bounding algorithm (AFB) is a distributed optimization search algorithm that keeps one consistent partial assignment at all times. Forward bounding propagates the bounds on the cost of solutions by sending copies of the partial assignment to all unassigned agents concurrently. The algorithm is described in detail and its correctness proven. Experimental evaluation of AFB on random Max-DisCSPs reveals a phase transition as the tightness of the problem increases. This effect is analogous to the phase transition of Max-CSP when local consistency maintenance is applied [3]. AFB outperforms Synchronous Branch & Bound (SBB) as well as the asynchronous state-of-the-art ADOPT algorithm, for the harder problem instances. Both asynchronous algorithms outperform SBB by a large factor.

Original languageEnglish
Title of host publicationECAI 2006
Subtitle of host publication17th European Conference on Artificial Intelligence August 29 - September 1, 2006, Riva del Garda, Italy
EditorsGerhard Brewka, Silvia Coradeschi, Anna Perini, Paolo Traverso
PublisherIOS Press BV
Pages103-107
Number of pages5
ISBN (Print)9781586036423
StatePublished - 1 Jan 2006

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume141
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Asynchronous forward-bounding for distributed constraints optimization'. Together they form a unique fingerprint.

Cite this