Results 1 - 10 of 31

QuickXPlain: Conflict Detection for Arbitrary Constraint Propagation Algorithms

by Ulrich Junker, F- Valbonne , 2001
"... Existing conflict detection methods for CSP's such as [de Kleer, 1989; Ginsberg, 1993] cannot make use of powerful propagation which makes them unusable for complex real-world problems. On the other hand, powerful constraint propagation methods lack the ability to extract dependencies or confli ..."
Abstract - Cited by 84 (0 self) - Add to MetaCart
Existing conflict detection methods for CSP's such as [de Kleer, 1989; Ginsberg, 1993] cannot make use of powerful propagation which makes them unusable for complex real-world problems. On the other hand, powerful constraint propagation methods lack the ability to extract dependencies or conflicts, which makes them unusable for many advanced AI reasoning methods that require conflicts, as well as for interactive applications that require explanations. In this paper, we present a non-intrusive conflict detection algorithm called QUICKXPLAIN that tackles those problems. It can be applied to any propagation or inference algorithm as powerful as it may be. Our algorithm improves the efficiency of direct non-intrusive conflict detectors by recursively partitioning the problem into subproblems of half the size and by immediately skipping those subproblems that do not contain an element of the conflict. QUICKXPLAIN is used as explanation component of an advanced industrial constraint-based configuration tool.

The CIFF Proof Procedure for Abductive Logic Programming with Constraints

by U. Endriss, P. Mancarella, F. Sadri, G. Terreni, F. Toni - In Proceedings JELIA04 , 2004
"... We introduce a new proof procedure for abductive logic programming and present two soundness results. Our procedure extends that of Fung and Kowalski by integrating abductive reasoning with constraint solving and by relaxing the restrictions on allowed inputs for which the procedure can operate ..."
Abstract - Cited by 43 (20 self) - Add to MetaCart
We introduce a new proof procedure for abductive logic programming and present two soundness results. Our procedure extends that of Fung and Kowalski by integrating abductive reasoning with constraint solving and by relaxing the restrictions on allowed inputs for which the procedure can operate correctly. An implementation of our proof procedure is available and has been applied successfully in the context of multiagent systems.
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Comparing Two Implementations of a Complete and Backtrack-Free Interactive Configurator

by Sathiamoorthy Subbarayan, Rune M. Jensen, Tarik Hadzic, Henrik R. Andersen, Henrik Hulgaard, Jesper Møller - In: CP’04 CSPIA Workshop , 2004
"... A product configurator should be complete and backtrack free in the sense that the user can choose freely between any valid configuration and will be prevented from making choices that no valid configuration satisfies. In this paper, we experimentally evaluate a symbolic and search-based impleme ..."
Abstract - Cited by 22 (11 self) - Add to MetaCart
A product configurator should be complete and backtrack free in the sense that the user can choose freely between any valid configuration and will be prevented from making choices that no valid configuration satisfies. In this paper, we experimentally evaluate a symbolic and search-based implementation of an interactive product configuration algorithm with these properties. Our results show that the symbolic approach often has several orders of magnitude faster response time than the search-based approach due to the precompilation of a symbolic representation of the solution space. Moreover, the di#erence between the average and worst response time for the symbolic approach is typically within a factor of two, whereas it for the search-based approach may be more than two orders of magnitude.
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FaCiLe: a Functional Constraint Library

by Pascal Brisset, Nicolas Barnier , 2001
"... FaCiLe is an open source constraint programming library over integer nite domain written in OCaml, a functional language of the ML family. It oers all usual constraint system facilities to create and handle nite domain variables, arithmetic constraints (possibly nonlinear) , built-in global cons ..."
Abstract - Cited by 18 (11 self) - Add to MetaCart
FaCiLe is an open source constraint programming library over integer nite domain written in OCaml, a functional language of the ML family. It oers all usual constraint system facilities to create and handle nite domain variables, arithmetic constraints (possibly nonlinear) , built-in global constraints and search goals. FaCiLe allows as well to build easily user-dened constraints and goals from scratch or by combining simple primitives, making pervasive use of higher-order functionals to provide a simple and exible user interface. As FaCiLe is an OCaml library and not yet another language, the user benets from polymorphic type inference and strong typing discipline, high level of abstraction, generic modules and object system, as well as native code compilation eciency, garbage collection and replay debugger. All these features allow to prototype and experiment quickly: modelling, data processing and interface are implemented in the same powerful language with a high level of safety.

OPL++: A Modeling Layer for Constraint Programming Libraries

by Laurent Michel, Pascal Van Hentenryck - INFORMS JOURNAL ON COMPUTING , 2001
"... Mathematical modeling and constraint programming languages have orthogonal strengths in stating combinatorial optimization problems. Modeling languages typically feature high-level set and algebraic notations, while constraint programming languages provide a rich constraint language and the abili ..."
Abstract - Cited by 10 (2 self) - Add to MetaCart
Mathematical modeling and constraint programming languages have orthogonal strengths in stating combinatorial optimization problems. Modeling languages typically feature high-level set and algebraic notations, while constraint programming languages provide a rich constraint language and the ability to specify search procedures. This paper shows that many of the functionalities typically found in modeling languages can be integrated elegantly in constraint programming libraries without dening a specic language or preprocessor. In particular, it presents the design of OPL++, a C++ modeling layer for constraint programming that combines the salient features of both approaches. Of particular interest is the one-to-one correspondance between high-level models and OPL++ statements and the negligible overhead induced by the extensions.

Evaluating ASP and commercial solvers on the CSPLib

by Marco Cadoli, Toni Mancini, Davide Micaletto, Fabio Patrizi - In Proceedings of the Seventeenth European Conference on Artificial Intelligence (ECAI 2006 , 2006
"... Abstract. This paper deals with three solvers for combinatorial problems: the commercial state-of-the-art solver Ilog OPL, and the research ASP systems DLV and SMODELS. The first goal of this research is to evaluate the relative performance of such systems, using a reproducible and extensible experi ..."
Abstract - Cited by 8 (3 self) - Add to MetaCart
Abstract. This paper deals with three solvers for combinatorial problems: the commercial state-of-the-art solver Ilog OPL, and the research ASP systems DLV and SMODELS. The first goal of this research is to evaluate the relative performance of such systems, using a reproducible and extensible experimental methodology. In particular, we consider a third-party problem library, i.e., the CSPLib, and uniform rules for modelling and selecting instances. The second goal is to analyze the effects of a popular reformulation technique, i.e., symmetry breaking, and the impact of other modelling aspects, like global constraints and auxiliary predicates. Results show that there is not a single solver winning on all problems, and that reformulation is almost always beneficial: symmetry-breaking may be a good choice, but its complexity has to be carefully chosen, by taking into account also the particular solver used. Global constraints often, but not always, help OPL, and the addition of auxiliary predicates is usually worth, especially when dealing with ASP solvers. Moreover, interesting synergies among the various modelling techniques exist. 1
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An Interval Constraint System for Lattice Domains

by Antonio J. Fernández, Patricia M. Hill - ACM Transactions on Programming Languages and Systems , 2004
"... We present a generic framework for defining and solving interval constraints on any set of domains (finite or infinite) that are lattices. The approach is based on the use of a single form of constraint similar to that of an indexical used by CLP for finite domains and on a particular generic defini ..."
Abstract - Cited by 6 (3 self) - Add to MetaCart
We present a generic framework for defining and solving interval constraints on any set of domains (finite or infinite) that are lattices. The approach is based on the use of a single form of constraint similar to that of an indexical used by CLP for finite domains and on a particular generic definition of an interval domain built from an arbitrary lattice. We provide the theoretical foundations for this framework and a schematic procedure for the operational semantics. Examples are provided that illustrate how new (compound) constraint solvers can be constructed from existing solvers using lattice combinators and how different solvers (possibly on distinct domains) can communicate and hence, cooperate in solving a problem. We describe the language clp(L), which is a prototype implementation of this framework and discuss ways in which this implementation may be improved.

Facilitating dl-based hybrid reasoning with Inference Fusion. Knowledge-Based Systems. Journal reprint of ES’02

by Bo Hu, Inés Arana, Ernesto Compatangelo - Jour. of Knowledge-Based Systems , 2003
"... We present an extension to DL-based taxonomic reasoning by means of the proposed inference fusion, i.e. the dynamic combination of infer-ences from distributed heterogeneous reasoners. Our approach integrates results from a DL-based system with results from a constraint solver un-der the direction o ..."
Abstract - Cited by 4 (4 self) - Add to MetaCart
We present an extension to DL-based taxonomic reasoning by means of the proposed inference fusion, i.e. the dynamic combination of infer-ences from distributed heterogeneous reasoners. Our approach integrates results from a DL-based system with results from a constraint solver un-der the direction of a global reasoning coordinator. Inference fusion is performed by (i) processing heterogeneous input knowledge, producing suitable homogeneous input knowledge for each specialised reasoner; (ii) activating each reasoner when necessary, collecting its results and passing them to the other reasoner if appropriate; (iii) combining the results of the 1 two reasoners. We discuss the benefits of our approach and demonstrate our ideas by proposing a language (DL(D)/S) and a reasoning system (Concor) which uses knowledge bases written in DL(D)/S and supports hybrid reasoning. We illustrate our ideas with an example.
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A generic, collaborative framework for interval constraint solving

by Antonio J Fernández - In Departamento de Lenguajes y Ciencias de la Computacion., Univ. of Malaga, Malaga
"... Abstract. The paper abstracts the contents of a PhD dissertation entitled A Generic, Collaborative Framework for Interval Constraint Solving which has been recently defended. This thesis presents a generic framework for defining and solving interval constraints on any set of domains (finite or infi ..."
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Abstract. The paper abstracts the contents of a PhD dissertation entitled A Generic, Collaborative Framework for Interval Constraint Solving which has been recently defended. This thesis presents a generic framework for defining and solving interval constraints on any set of domains (finite or infinite) that are lattices. This framework combines a number of characteristics desirable in any constraint system such as transparency, on both constraints and computation domains (i.e., it follows a glass box approach where new constraints can be user defined and new, possibly compound, constraint domains can be constructed from existing domains using lattice combinators), cooperativity (so that different solvers, possibly on distinct domains, can communicate and hence, cooperate in solving a problem) and genericity (i.e., it can be applied on any computation domain with lattice structure). Keywords: Constraint, lattice, cooperation, propagation, indexical Abstract of PhD dissertation The basic idea in Constraint Logic Programming (CLP) Most constraint solvers, called black box solvers, have the control fixed by the system. This approach enables very efficient implementations and can provide practical tools for the common constraint applications. However, such black box solvers lack adaptability for use in solving non-standard problems. To overcome this lack of flexibility, some constraint systems provide glass box constraints Moreover, many problems are most naturally expressed using heterogeneous constraints over more than one domain and there exist constraints defined on multiple domains that require the collaboration of distinct domains by sending and receiving information to and from another different domain (e.g., w = x > y). As consequence, in existing CLP systems the formulation of real problems has to be artificially adapted to a single domain (i.e., one of the supported by the system). This thesis proposes a generic and cooperative schema for CLP(Interval(X )) where X is any computation domain with lattice structure. This schema, based on interval lattices, is a general framework for
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Representation and Reasoning with Non-Binary Constraints

by Kostas Stergiou , 2001
"... Many problems from the \real world" can be eciently expressed as constraint satisfaction problems (CSPs). Most of these can be naturally modelled using n-ary (or non-binary) constraints. Representing problems with n-ary constraints and reasoning with them is therefore very important in constrai ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
Many problems from the \real world" can be eciently expressed as constraint satisfaction problems (CSPs). Most of these can be naturally modelled using n-ary (or non-binary) constraints. Representing problems with n-ary constraints and reasoning with them is therefore very important in constraint satisfaction. However, issues regarding n-ary constraints have been neglected compared to binary constraints. The reasons were the simplicity of dealing with binary constraints compared to nary and the fact that any non-binary CSP can be encoded into an equivalent binary. This thesis makes an empirical and theoretical study on representation and solution methods for n-ary CSPs. The results we present demonstrate the importance of the choice of representation and reasoning techniques in n-ary problems.