Acquiring Constraint Networks Using a SAT-based Version Space Algorithm

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.

Authors

• Christian Bessiere
• Frederic Koriche Barry O’Sullivan

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