Query-driven Constraint Acquisition

Christian Bessiere, Remi Coletta, Barry O’Sullivan, Mathias Paulin

The modelling and reformulation of constraint networks are recognised as important problems. The task of automatically acquiring a constraint network formulation of a problem from a subset of its solutions and non-solutions has been presented in the literature. However, the choice of such a subset was assumed to be made independently of the acquisition process. We present an approach in which an interactive acquisition system actively selects a good set of examples. We show that the number of examples required to acquire a constraint network is significantly reduced using our approach.

Subjects: 15.2 Constraint Satisfaction

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Submitted: Oct 15, 2006


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