AbdelAli Ed-Dbali

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In this paper, we present an abstract framework for learning a finite domain constraint solver mod-eled by a set of operators enforcing a consistency. The behavior of the consistency to be learned is taken as the set of examples on which the learning process is applied. The best possible expression of this operator in a given language is then searched. We(More)
What makes a good consistency ? Depending on the constraint, it may be a good pruning power or a low computational cost. By " weakening " arc-consistency, we propose to define new automatically generated solvers which form a sequence of consistencies weaker than arc-consistency. The method presented in this paper exploits a form of regularity in the cloud(More)
In this paper, we present an abstract framework for learning a finite domain constraint solver modeled by a set of operators enforcing a consistency. The behavior of the consistency to be learned is taken as the set of examples on which the learning process is applied. The best possible expression of this operator in a given language is then searched. We(More)
In this paper, we introduce a formal framework to describe CSP approximations (usually called consistencies), showing the importance of the language (or data-structure) used to perform this consistency. We introduce the notion of R-consistency which takes into account the representation of the data and which generalizes many known consistencies. We then(More)
The purpose of this paper is to present some functionalities of the HyperPro System. HyperPro is a hypertext tool which allows to develop Constraint Logic Programming (CLP) together with their documentation. The text editing part is not new and is based on the free software Thot. A HyperPro program is a Thot document written in a report style. The tool is(More)