Query-Driven Constraint Acquisition
Abstract
The modelling and reformulation of constraint net- works are recognised as important problems. The task of automatically acquiring a constraint net- work 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 ac- quisition 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.
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