C. Bessi#re and J.C. R#gin. Arc consistency for general constraint networks: preliminary results. In Proceedings IJCAI'97, pages 398404, Nagoya, Japan, 1997.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....variables and an outer loop that keeps this process going while new values are deleted. The worst case complexity of achieving SAC is O(en 2 d 4 ) where e is the number of constraints, n the number of variables, and d the domain size. For non binary constraints, if we assume that GAC schema [BR97] is used to enforce GAC then the worst case complexity of achieving SGAC is O(en 2 d 2k ) where k is the arity of the constraints. For the specialized case of all di erent constraints, taking advantage of Regin s algorithm means that SGAC can be achieved with O(cn 4 d 4 ) worst case ....

C. Bessiere and J.C. Regin. Arc consistency for general constraint networks: Preliminary results. In Proceedings IJCAI-97, pages 398-404, 1997.

....Consistency on Conjunctions of Constraints Christian Bessi#re 1 and Jean Charles R#gin 2 Abstract. Constraint networks are used more and more to solve combinatorial problems in real life applications. As pointed out in [BR97], this success requires dealing with nonbinary constraints, which are widely needed in real world constraint solvers. Since arc consistency is a fundamental piece of reasoning that seems to be of great help during search for solutions, it is important to have eOEcient arc consistency algorithms ....

....with nonbinary constraints, which are widely needed in real world constraint solvers. Since arc consistency is a fundamental piece of reasoning that seems to be of great help during search for solutions, it is important to have eOEcient arc consistency algorithms for non binary constraints. In [BR97], a rst step has been done, resulting in a general schema for arc consistency on any kind of constraints, and in instantiations of the schema to handle the more general non binary constraints, i.e. those given as a predicate or as a set of allowed forbidden combinations of values. In this paper, ....

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C. Bessi#re and J.C. R#gin. Arc consistency for general constraint networks: preliminary results. In Proceedings IJCAI'97, pages 398404, Nagoya, Japan, 1997. ECAI98 Workshop on Non Binary Constraints 58

....it to specific cases, following the Strategy pattern [Gamma et al. 1994] To facilitate reuse, we use the Template Method pattern: the algorithm is decomposed into several methods representing various steps of the resolution. 2. 2Constraints Classes The central concept is constraint filtering [Bessi re and R gin 1997], which is used during the resolution to reduce the problem. Constraint filtering depends on the nature of the constraint considered but is domain independent. This leads to organizing constraints into a hierarchy of classes, each class defining its own filtering procedure. This offers the ....

C. Bessière and J.-Ch. Régin, "Arc-Consistency for General Constraint Networks: Preliminary Results" proceedings of IJCAI, Nagoya, Japan, pp. 398-404, Aug. 1997.

....problems, for which the binary conversion is sometimes often impracticable. This observation, stressed by van Beek in its CP 96 invocation, has started having its eoeect since papers especially devoted to non binary constraints or to their binary conversion begin to appear in this end of decade [4, 1, 22, 2]. Dealing with non binary constraints for real world problems raises questions that do not appear as crucial on binary constraints. Applying ltering techniques during search is central in the eOEciency of constraint satisfaction algorithms. But applying ltering on non binary constraints is much ....

C. Bessi#re and J.C. R#gin. Arc consistency for general constraint networks: preliminary results. In Proceedings IJCAI'97, pages 398404, Nagoya, Japan, 1997.

....the propagations nFC3 (resp. nFC5) performs in order to reach an arc consistent state on C n c;f (resp. C n p;f ) whereas nFC2 (resp. nFC4) performs ione passj arc consistency on them. Thus, if we suppose that arc consistency is achieved by an optimal algorithm, such as GAC4 [7] or GAC schema [2], the upper bound in the number of constraint checks performed by nFC3 (resp. nFC5) at a given node is the same as nFC2 (resp. nFC4) bound. With an AC3 like algorithm [6] nFC3 and nFC5 have a greater upper bound. 4.3 FC and nFC1 The hidden variable representation is a general method for ....

C. Bessi#re and J.C. R#gin. Arc consistency for general constraint networks: preliminary results. In Proceedings IJCAI'97, pages 398404, Nagoya, Japan, 1997.

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C. Bessi#re and J.C. R#gin. Arc consistency for general constraint networks: preliminary results. In Proceedings IJCAI'97, pages 398404, Nagoya, Japan, 1997.

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C. Bessiere and J.-C. Regin. Arc consistency for general constraint networks: Preliminary results. In Proc. of IJCAI-97, pp. 398-404.

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Bessiere, C., Regin, J.C.: Arc consistency for general constraint networks: preliminary results. In: Proceedings IJCAI'97, Nagoya, Japan (1997) 398-404

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C. Bessiere and J.C. Regin. Arc consistency for general constraint networks: Preliminary results. In Proceedings IJCAI-97, pages 398{ 404, 1997.

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C. Bessiere and J-C Regin. Arc consistency for general constraint networks: Preliminary results. In Proceedings of IJCAI'97, pages 398-404, 1997.

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C. Bessiere and J-C Regin. Arc consistency for general constraint networks: Preliminary results. In Proceedings of IJCAI'97, pages 398-404, 1997.

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C. Bessiere and J.C. Regin. Arc consistency for general constraint networks: Preliminary results. In Proc. of IJCAI'97, pages 398-404. Morgan Kaufmann, 1997.

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