Constrain relaxation in distributed constraint satisfaction problems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

The distributed constraint satisfaction problem (DSCP) formulation has recently been identified as a general framework for formalizing various Distributed Artificial Intelligence problems. In this paper, we extend the DCSP formalization by introducing the notion of importance values of constraints. With these values, we define a solution criterion for DCSPs, that are over-constrained (where no solution satisfies all constraints completely). We show that agents can find an optimal solution with this criterion by using the asynchronous incremental relaxation algorithm, in which the agents iteratively apply the asynchronous backtracking algorithm to solve a DCSP, while incrementally relaxing less important constraints. In this algorithm, agents act asynchronously and concurrently, in contrast to traditional sequential backtracking techniques, while guaranteeing thee completeness of the algorithm and the optimality of the optimality. Furthermore, we show that, in this algorithm, agents can avoid redundant computation and achieve a five-fold speed-up in example problems by maintaining the dependencies between constraint violations (nogoods) and constraints.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Tools with Artificial Intelligence
Editors Anon
PublisherPubl by IEEE
Pages56-63
Number of pages8
ISBN (Print)0818642009
Publication statusPublished - 1993
Externally publishedYes
EventProceedings of the 5th International Conference on Tools with Artificial Intelligence TAI '93 - Boston, MA, USA
Duration: Nov 8 1993Nov 11 1993

Other

OtherProceedings of the 5th International Conference on Tools with Artificial Intelligence TAI '93
CityBoston, MA, USA
Period11/8/9311/11/93

All Science Journal Classification (ASJC) codes

  • Software

Fingerprint Dive into the research topics of 'Constrain relaxation in distributed constraint satisfaction problems'. Together they form a unique fingerprint.

Cite this