Results 1  10
of
16
Beyond NP: ArcConsistency for Quantified Constraints
, 2002
"... The generalization of the satisfiability problem with arbitrary quantifiers is a challenging problem of both theoretical and practical relevance. Being PSPACEcomplete, it provides a canonical model for solving other PSPACE tasks which naturally arise in AI. ..."
Abstract

Cited by 46 (5 self)
 Add to MetaCart
The generalization of the satisfiability problem with arbitrary quantifiers is a challenging problem of both theoretical and practical relevance. Being PSPACEcomplete, it provides a canonical model for solving other PSPACE tasks which naturally arise in AI.
An Analysis of Slow Convergence in Interval Propagation
"... Abstract. When performing interval propagation on integer variables with a large range, slowconvergence phenomena are often observed: it becomes difficult to reach the fixpoint of the propagation. This problem is practically important, as it hinders the use of propagation techniques for problems wi ..."
Abstract

Cited by 7 (1 self)
 Add to MetaCart
(Show Context)
Abstract. When performing interval propagation on integer variables with a large range, slowconvergence phenomena are often observed: it becomes difficult to reach the fixpoint of the propagation. This problem is practically important, as it hinders the use of propagation techniques for problems with large numerical ranges, and notably problems arising in program verification. A number of attempts to cope with this issue have been investigated, yet all of the proposed techniques only guarantee a fast convergence on specific instances. An important question is therefore whether slow convergence is intrinsic to propagation methods, or whether an improved propagation algorithm may exist that would avoid this problem. This paper proposes the first analysis of the slow convergence problem under the light of complexity results. It answers the question, by a negative result: if we allow propagators that are general enough, computing the fixpoint of constraint propagation is shown to be intractable. Slow convergence is therefore unavoidable unless P=NP. The result holds for the propagators of a basic class of constraints. 1
Theory of Finite or Infinite Trees Revisited
 UNDER CONSIDERATION FOR PUBLICATION IN THEORY AND PRACTICE OF LOGIC PROGRAMMING
, 2007
"... We present in this paper a firstorder axiomatization of an extended theory T of finite or infinite trees, built on a signature containing an infinite set of function symbols and a relation finite(t) which enables to distinguish between finite or infinite trees. We show that T has at least one model ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
We present in this paper a firstorder axiomatization of an extended theory T of finite or infinite trees, built on a signature containing an infinite set of function symbols and a relation finite(t) which enables to distinguish between finite or infinite trees. We show that T has at least one model and prove its completeness by giving not only a decision procedure, but a full firstorder constraint solver which gives clear and explicit solutions for any firstorder constraint satisfaction problem in T. The solver is given in the form of 16 rewriting rules which transform any firstorder constraint ϕ into an equivalent disjunction φ of simple formulas such that φ is either the formula true or the formula false or a formula having at least one free variable, being equivalent neither to true nor to false and where the solutions of the free variables are expressed in a clear and explicit way. The correctness of our rules implies the completeness of T. We also describe an implementation of our algorithm in CHR (Constraint Handling Rules) and compare the performance with an implementation in C++ and that of a recent decision procedure for decomposable theories.
P.: Static Type Inference for the Q language using Constraint Logic Programming
 In: 28th International Conference on Logic Programming (ICLP 2012). Leibniz International Proceedings in Informatics (LIPIcs
, 2012
"... We describe an application of Prolog: a type inference tool for the Q functional language. Q is a terse vector processing language, a descendant of APL, which is getting more and more popular, especially in financial applications. Q is a dynamically typed language, much like Prolog. Extending Q with ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
We describe an application of Prolog: a type inference tool for the Q functional language. Q is a terse vector processing language, a descendant of APL, which is getting more and more popular, especially in financial applications. Q is a dynamically typed language, much like Prolog. Extending Q with static typing improves both the readability of programs and programmer productivity, as type errors are discovered by the tool at compile time, rather than through debugging the program execution. We map the task of type inference onto a constraint satisfaction problem and use constraint logic programming, in particular the Constraint Handling Rules extension of Prolog. We determine the possible type values for each program expression and detect inconsistencies. As most builtin function names of Q are overloaded, i.e. their meaning depends on the argument types, a quite complex system of constraints had to be implemented.
AgentOriented Language Engineering for Robust NLP
 In
"... The main goal of our work is to propose an agentoriented framework for developing robust NLP applications. This framework provides means to compose analysis modules in a cooperative style. The idea is to encapsulate existing analysis tools and resources within software agents coordinated at a ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
(Show Context)
The main goal of our work is to propose an agentoriented framework for developing robust NLP applications. This framework provides means to compose analysis modules in a cooperative style. The idea is to encapsulate existing analysis tools and resources within software agents coordinated at a higher level using metaknowledge. Agents can be activated concurrently and they should provide their linguistic competence depending on the application needs. The activation policy is determined by the context, by the domain knowledge and by performance constraints. At this level, coordination is computational logicbased in order to exploit known inference mechanisms for the decision support. This framework should be general enough to cope with other kinds of information sources, such as multimedia documents and with multimodal dialogue systems.
Toward a FirstOrder Extension of Prolog’s Unification using CHR  A CHR FirstOrder Constraint Solver Over Finite or Infinite Trees
, 2007
"... Prolog, which stands for PROgramming in LOGic, is the most widely used language in the logic programming paradigm. One of its main concepts is unification. It represents the mechanism of binding the contents of variables and can be seen as solving conjunctions of equations over finite or infinite tr ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
Prolog, which stands for PROgramming in LOGic, is the most widely used language in the logic programming paradigm. One of its main concepts is unification. It represents the mechanism of binding the contents of variables and can be seen as solving conjunctions of equations over finite or infinite trees. We present in this paper an idea of a firstorder extension of Prolog’s unification by giving a general algorithm for solving any firstorder constraint in the theory T of finite or infinite trees, extended by a relation which allows to distinguish between finite and infinite trees. The algorithm is given in the form of 16 rewriting rules which transform any firstorder formula ϕ into an equivalent disjunction φ of simple formulas in which the solutions of the free variables are expressed in a clear and explicit way. We end this paper describing a CHR implementation of our algorithm. CHR (Constraint Handling Rules) has originally been developed for writing constraint solvers, but the constraints here go much beyond implicitly quantified conjunctions of atomic constraints and are considered as arbitrary firstorder formulas built on the signature of T. We discuss how we implement nested local constraint stores and what programming patterns and language features we found useful in the CHR implementation of our algorithm.
A logical framework for designing robust distributed NLP applications
, 2001
"... The main goal of our work is to propose an agentoriented framework for developing robust NLP applications. The framework is a computational logicbased environment for developing document analysis applications. This ..."
Abstract
 Add to MetaCart
The main goal of our work is to propose an agentoriented framework for developing robust NLP applications. The framework is a computational logicbased environment for developing document analysis applications. This
SICStus Prolog User’s Manual Mats Carlsson et al.
, 2009
"... Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the ..."
Abstract
 Add to MetaCart
Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by SICS. i
Pros and Cons of Using CHR for Type Inference
"... Abstract. We report on using logic programming and in particular the Constraint Handling Rules extension of Prolog to provide static type analysis for the Q functional language. We discuss some of the merits and difficulties of CHR that we came across during implementation of a type inference tool. ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract. We report on using logic programming and in particular the Constraint Handling Rules extension of Prolog to provide static type analysis for the Q functional language. We discuss some of the merits and difficulties of CHR that we came across during implementation of a type inference tool.