Extensible Automated Constraint Modelling

Ozgur Akgun, Ian Miguel, Chris Jefferson, Alan M. Frisch, Brahim Hnich

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In constraint solving, a critical bottleneck is the formulationof 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.
Original languageEnglish
Title of host publicationProceedings of theTwenty-Fifth AAAI Conference on Artificial Intelligence
Place of PublicationSan Francisco
PublisherAAAI Press
Number of pages8
ISBN (Print)978-1-57735-507-6
Publication statusPublished - Aug 2011

Cite this