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Acquiring Constraint Networks using a SAT-based Version Space Algorithm

Christian Bessière 1 Frédéric Koriche 1 Remi Coletta 1 Barry O'Sullivan 2 
1 COCONUT - Agents, Apprentissage, Contraintes
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Constraint programming is a commonly used technology for solving complex combinatorial problems. However, users of this technology need significant expertise in order to model their problems appropriately. We propose a basis for address- ing this problem: a new SAT-based version space algorithm for acquiring constraint networks from examples of solutions and non-solutions of a target problem. An important advan- tage of the algorithm is the ease with which domain-specific knowledge can be exploited.
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Submitted on : Thursday, March 8, 2007 - 11:48:22 AM
Last modification on : Friday, August 5, 2022 - 3:02:57 PM
Long-term archiving on: : Tuesday, April 6, 2010 - 10:09:10 PM


  • HAL Id : lirmm-00135484, version 1



Christian Bessière, Frédéric Koriche, Remi Coletta, Barry O'Sullivan. Acquiring Constraint Networks using a SAT-based Version Space Algorithm. AAAI Conference on Artificial Intelligence, Jul 2006, Boston, MA, United States. pp.1565-1568. ⟨lirmm-00135484⟩



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