A framework for autonomous search in the Eclipse solver

Broderick Crawford, Ricardo Soto, Mauricio Montecinos, Carlos Castro, Eric Monfroy

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

20 Scopus citations

Abstract

Autonomous Search (AS) is a special feature allowing systems to improve their performance by self-adaptation. This approach has been recently adapted to Constraint Programming (CP) reporting promising results. However, as the research lies in a preliminary stage there is a lack of implementation frameworks and architectures. This hinders the research progress, which in particular, requires a considerable work in terms of experimentation. In this paper, we propose a new framework for implementing AS in CP. It allows a dynamic self-adaptation of the classic CP solving process and an easy update of its components, allowing developers to define their own AS-CP approaches. We believe this will help researchers to perform new AS experiments, and as a consequence to improve the current preliminary results.

Original languageEnglish
Title of host publicationModern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Proceedings
Pages79-84
Number of pages6
EditionPART 1
DOIs
StatePublished - 2011
Event24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011 - Syracuse, NY, United States
Duration: 28 Jun 20111 Jul 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6703 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011
Country/TerritoryUnited States
CitySyracuse, NY
Period28/06/111/07/11

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