Acquiring constraint networks using a SAT-based version space algorithm

Authors:
Christian Bessiere;Remi Coletta;Frédéric Koriche;Barry O'Sullivan
Affiliations:
LIRMM, CNRS, University of Montpellier, Montpellier, France;LIRMM, CNRS, University of Montpellier, Montpellier, France;LIRMM, CNRS, University of Montpellier, Montpellier, France;Cork Constraint Computation Centre, University College Cork, Ireland
Venue:
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Year:
2006

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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 addressing 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 advantage of the algorithm is the ease with which domain-specific knowledge can be exploited.