Akgun, Ozgur, Miguel, Ian, Jefferson, Chris et al. (2 more authors) (2011) Extensible Automated Constraint Modelling. In: Proceedings of theTwenty-Fifth AAAI Conference on Artificial Intelligence. AAAI Press , San Francisco , pp. 4-11.
Abstract
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.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Dates: |
|
Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 17 Oct 2013 15:21 |
Last Modified: | 16 Oct 2024 10:37 |
Status: | Published |
Publisher: | AAAI Press |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:76732 |
Download
Filename: PAPER3_FRISCH_ExtensibleAutomatedConstraint.pdf
Description: PAPER3_FRISCH_ ExtensibleAutomatedConstraint