Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/3980
Title: Extensible Automated Constraint Modelling
Authors: Akgun, O.
Miguel, I.
Jefferson, C.
Frisch, A.M.
Hnich, B.
Publisher: AAAI Press
Abstract: In constraint solving, a critical bottleneck is the formulation of an effective constraint model of a given problem. The CONJURE system described in this paper, a substantial step forward over prototype versions of CONJURE previously reported, makes a valuable contribution to the automation of constraint modelling by automatically producing constraint models from their specifications in the abstract constraint specification language ESSENCE. A set of rules is used to refine an abstract specification into a concrete constraint model. We demonstrate that this set of rules is readily extensible to increase the space of possible constraint models CONJURE can produce. Our empirical results confirm that CONJURE can reproduce successfully the kernels of the constraint models of 32 benchmark problems found in the literature. Copyright © 2011, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Description: Association for the Advancement of Artificial Intelligence
ISBN: 9781577355083
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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