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.
CITATION STYLE
Akgun, O., Miguel, I., Jefferson, C., Frisch, A. M., & Hnich, B. (2011). Extensible Automated Constraint Modelling. In Proceedings of the 25th AAAI Conference on Artificial Intelligence, AAAI 2011 (pp. 4–11). AAAI Press. https://doi.org/10.1609/aaai.v25i1.7820
Mendeley helps you to discover research relevant for your work.