Arc-Consistency Filtering Algorithms for Logical Combinations of Constraints

Lhomme, Olivier

doi:10.1007/978-3-540-24664-0_15

Cited by 30 publications

(16 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Now equipped with efficient filtering algorithms for regular and context-free grammar constraints, in the spirit of [3,12] we focus on certain questions that arise when a problem is modeled by logic combinations of these constraints. An important aspect when investigating logical combinations of grammar constraints is under what operations the given class of languages is closed.…”

Section: Logic Combinations Of Grammar Constraintsmentioning

confidence: 99%

Grammar constraints

Kadioglu

Sellmann

2009

Constraints

View full text Add to dashboard Cite

With the introduction of the Regular Membership Constraint, a new line of research has opened where constraints are based on formal languages. This paper is taking the next step, namely to investigate constraints based on grammars higher up in the Chomsky hierarchy. We devise a time-and space-efficient incremental arc-consistency algorithm for context-free grammars, investigate when logic combinations of grammar constraints are tractable, show how to exploit non-constant size grammars and reorderings of languages, and study where the boundaries run between regular, context-free, and context-sensitive grammar filtering.

show abstract

Section: Logic Combinations Of Grammar Constraintsmentioning

confidence: 99%

Grammar constraints

Kadioglu

Sellmann

2009

Constraints

View full text Add to dashboard Cite

show abstract

“…Indeed, the generic concepts that capture those consistencies are (relational) (i, j)-consistencies (see section 2.2). Therefore, they rather rely on the notion of allowed and valid instantiations, and it is required to be able to iterate over and export these, as it is performed to handle logical connectives in [16]. Moreover, algorithms that seek optimal worst-case time complexities memorize which instantiations have already been considered.…”

Section: A Generic Schemementioning

confidence: 99%

Integrating Strong Local Consistencies into Constraint Solvers

Vion

Petit²,

Jussien³

2011

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. This article presents a generic scheme for adding strong local consistencies to the set of features of constraint solvers, which is notably applicable to event-based constraint solvers. We encapsulate a subset of constraints into a global constraint. This approach allows a solver to use different levels of consistency for different subsets of constraints in the same model. Moreover, we show how strong consistencies can be applied with different kinds of constraints, including user-defined constraints. We experiment our technique with a coarse-grained algorithm for Max-RPC, called Max-RPC rm , and a variant of it, L-Max-RPC rm . Experiments confirm the interest of strong consistencies for Constraint Programming tools.

show abstract

“…A domain-consistency algorithm, based on AC7, was proposed in [7] for the conjunction of constraints. Lhomme [8] describes a domain-consistency algorithm for any combination of constraints. It focuses primarily on constraints given in extension.…”

Section: Related Work the Idea Of Using Forbidden Values Is Not New Imentioning

confidence: 99%

Domain Consistency with Forbidden Values

Deville

Hentenryck

2010

Principles and Practice of Constraint Programming – CP 2010

View full text Add to dashboard Cite

Abstract. This paper presents a novel domain-consistency algorithm which does not maintain supports dynamically during propagation, but rather maintain forbidden values. It introduces the optimal NAC4 (negative AC4) algorithm based on this idea. It further shows that maintaining forbidden values dynamically allows the generic algorithm AC5 to achieve domain consistency in time O(ed) for classes of constraints in which the number of supports is O(d 2 ) but the number of forbidden values is O(d). The paper also shows how forbidden values and supports can be used jointly to achieve domain consistency on logical combinations of constraints and to compute validity as well as entailment of constraints. Experimental results show the benefits of the joint exploitation of supports and forbidden values.

show abstract

Arc-Consistency Filtering Algorithms for Logical Combinations of Constraints

Cited by 30 publications

References 5 publications

Grammar constraints

Grammar constraints

Integrating Strong Local Consistencies into Constraint Solvers

Domain Consistency with Forbidden Values

Contact Info

Product

Resources

About