A Comparison of Logic Programming Approaches for Representation and Solving of Constraint Satisfaction Problems

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dc.creatorPelov, Nikolay
dc.creatorDe Mot, Emmanuel
dc.creatorBruynooghe, Maurice
dc.date2000-03-08
dc.date.accessioned2026-07-07T03:15:59Z
dc.date.available2026-07-07T03:15:59Z
dc.descriptionMany logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there are definite programs and constraint logic programs that compute a solution as an answer substitution to a query containing the variables of the constraint satisfaction problem. On the other hand there are approaches based on stable model semantics, abduction, and first-order logic model generation that compute solutions as models of some theory. This paper compares these different approaches from point of view of knowledge representation (how declarative are the programs) and from point of view of performance (how good are they at solving typical problems).
dc.description9 pages, 3 figures submitted to NMR 2000, April 9-11, Breckenridge, Colorado
dc.identifierhttps://arxiv.org/abs/cs/0003026
dc.identifierhttp://arxiv.org/abs/cs/0003026
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30186
dc.subjectLogic in Computer Science
dc.subjectI.2.3: Logic programming, Nonmonotonic reasoning; I.2.4; F.4.1: Logic and constraint programming; Experiments
dc.titleA Comparison of Logic Programming Approaches for Representation and Solving of Constraint Satisfaction Problems
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