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We study here a natural situation when constraint programming can be entirely reduced to rule-based programming. To this end we explain first how one can compute on constraint satisfaction problems using rules represented by simple…

Artificial Intelligence · Computer Science 2007-05-23 Krzysztof R. Apt , Eric Monfroy

We describe the use of array expressions as constraints, which represents a consequent generalisation of the "element" constraint. Constraint propagation for array constraints is studied theoretically, and for a set of domain reduction…

Programming Languages · Computer Science 2007-05-23 Sebastian Brand

We study here the well-known propagation rules for Boolean constraints. First we propose a simple notion of completeness for sets of such rules and establish a completeness result. Then we show an equivalence in an appropriate sense between…

Artificial Intelligence · Computer Science 2007-05-23 Krzysztof R. Apt

We show that several constraint propagation algorithms (also called (local) consistency, consistency enforcing, Waltz, filtering or narrowing algorithms) are instances of algorithms that deal with chaotic iteration. To this end we propose a…

Artificial Intelligence · Computer Science 2007-05-23 Krzysztof R. Apt

Enforcing local consistencies is one of the main features of constraint reasoning. Which level of local consistency should be used when searching for solutions in a constraint network is a basic question. Arc consistency and partial forms…

Artificial Intelligence · Computer Science 2011-06-06 C. Bessiere , R. Debruyne

A widely adopted approach to solving constraint satisfaction problems combines systematic tree search with constraint propagation for pruning the search space. Constraint propagation is performed by propagators implementing a certain notion…

Artificial Intelligence · Computer Science 2007-05-23 Chiu Wo Choi , Warwick Harvey , Jimmy Ho-Man Lee , Peter J. Stuckey

We document a connection between constraint reasoning and probabilistic reasoning. We present an algorithm, called {em probabilistic arc consistency}, which is both a generalization of a well known algorithm for arc consistency used in…

Artificial Intelligence · Computer Science 2013-01-18 Michael C. Horsch , Bill Havens

In Constraint Programming, solving discrete minimization problems with hard and soft constraints can be done either using (i) soft global constraints, (ii) a reformulation into a linear program, or (iii) a reformulation into local cost…

Artificial Intelligence · Computer Science 2025-09-24 Pierre Montalbano , Simon de Givry , George Katsirelos

The notion of arc consistency plays a central role in constraint satisfaction. It is known that the notion of local consistency can be extended to constraint optimisation problems defined by soft constraint frameworks based on an idempotent…

Artificial Intelligence · Computer Science 2007-05-23 Martin Cooper , Thomas Schiex

A natural and established way to restrict the constraint satisfaction problem is to fix the relations that can be used to pose constraints; such a family of relations is called a constraint language. In this article, we study arc…

Artificial Intelligence · Computer Science 2011-04-27 Hubie Chen , Victor Dalmau , Berit Grußien

Constraint programming is a family of techniques for solving combinatorial problems, where the problem is modelled as a set of decision variables (typically with finite domains) and a set of constraints that express relations among the…

Artificial Intelligence · Computer Science 2016-05-31 James Caldwell , Ian P. Gent , Peter Nightingale

Bessiere et al. (AAAI'08) showed that several intractable global constraints can be efficiently propagated when certain natural problem parameters are small. In particular, the complete propagation of a global constraint is fixed-parameter…

Artificial Intelligence · Computer Science 2011-04-14 Serge Gaspers , Stefan Szeider

The past decade has witnessed substantial developments in string solving. Motivated by the complexity of string solving strategies adopted in existing string solvers, we investigate a simple and generic method for solving string…

Logic in Computer Science · Computer Science 2025-08-28 Matthew Hague , Artur Jeż , Anthony W. Lin , Oliver Markgraf , Philipp Rümmer

Two contrasting algorithmic paradigms for constraint satisfaction problems are successive local explorations of neighboring configurations versus producing new configurations using global information about the problem (e.g. approximating…

Quantum Physics · Physics 2022-12-09 S. Andrew Lanham

Numerical analysis has no satisfactory method for the more realistic optimization models. However, with constraint programming one can compute a cover for the solution set to arbitrarily close approximation. Because the use of constraint…

Numerical Analysis · Mathematics 2025-10-20 M. H. van Emden , B. Moa

Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem. We aim at determining the time complexity of arc consistency testing. The input structures $G$ and $H$…

Logic in Computer Science · Computer Science 2013-03-29 Christoph Berkholz , Oleg Verbitsky

Constraint propagation algorithms form an important part of most of the constraint programming systems. We provide here a simple, yet very general framework that allows us to explain several constraint propagation algorithms in a systematic…

Performance · Computer Science 2007-05-23 Krzysztof R. Apt

This paper describes a new approach on optimization of constraint satisfaction problems (CSPs) by means of substituting sub-CSPs with locally consistent regular membership constraints. The purpose of this approach is to reduce the number of…

Artificial Intelligence · Computer Science 2019-08-19 Sven Löffler , Ke Liu , Petra Hofstedt

In classical CLP(FD) systems, domains of variables are completely known at the beginning of the constraint propagation process. However, in systems interacting with an external environment, acquiring the whole domains of variables before…

Logic in Computer Science · Computer Science 2007-05-23 Marco Alberti , Marco Gavanelli , Evelina Lamma , Paola Mello , Michela Milano

In many combinatorial problems one may need to model the diversity or similarity of assignments in a solution. For example, one may wish to maximise or minimise the number of distinct values in a solution. To formulate problems of this…

Artificial Intelligence · Computer Science 2014-01-17 Emmanuel Hebrard , Dániel Marx , Barry O'Sullivan , Igor Razgon
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