Using autonomous search for generating good enumeration strategy blends in constraint programming

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

33 Scopus citations

Abstract

In Constraint Programming, enumeration strategies play an important role, they can significantly impact the performance of the solving process. However, choosing the right strategy is not simple as its behavior is commonly unpredictable. Autonomous search aims at tackling this concern, it proposes to replace bad performing strategies by more promising ones during the resolution. This process yields a combination of enumeration strategies that worked during the search phase. In this paper, we focus on the study of this combination by carefully tracking the resolution. Our preliminary goal is to find good enumeration strategy blends for a given Constraint Satisfaction Problem.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - 12th International Conference, ICCSA 2012, Proceedings
Pages607-617
Number of pages11
EditionPART 3
DOIs
StatePublished - 23 Jul 2012
Event12th International Conference on Computational Science and Its Applications, ICCSA 2012 - Salvador de Bahia, Brazil
Duration: 18 Jun 201221 Jun 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume7335 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Computational Science and Its Applications, ICCSA 2012
Country/TerritoryBrazil
CitySalvador de Bahia
Period18/06/1221/06/12

Keywords

  • Artificial Intelligence
  • Autonomous Search
  • Constraint Programming

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