The Experts below are selected from a list of 15753 Experts worldwide ranked by ideXlab platform
Nikolai Kosmatov - One of the best experts on this subject based on the ideXlab platform.
-
SAC - A Constraint Solver for sequences and its applications
Proceedings of the 2006 ACM symposium on Applied computing - SAC '06, 2006Co-Authors: Nikolai KosmatovAbstract:Constraint programming techniques are successfully used in various areas of software engineering for industry, commerce, transport, finance etc. Constraint Solvers for different data types are applied in validation and verification of programs containing data elements of these types. A general Constraint Solver for sequences is necessary to take into account this data type in the existing validation and verification tools. In this work, we present an original Constraint Solver for sequences implemented in CHR and based on T. Fruhwirth's Solver for lists with the propagation of two Constraints: generalized concatenation and size. The applications of the Solver (with the validation and verification tool BZTT) to different software engineering problems are illustrated by the example of a waiting room model.
-
Constraint solving for sequences in software validation and verification
Lecture Notes in Computer Science, 2006Co-Authors: Nikolai KosmatovAbstract:Constraint programming techniques are successfully used in various areas of software engineering for industry, commerce, transport, finance etc. Constraint Solvers for different data types are applied in validation and verification of programs containing data elements of these types. A general Constraint Solver for sequences is necessary to take into account this data type in the existing validation and verification tools. In this work, we present an original Constraint Solver for sequences implemented in CHR and based on T. Fruhwirth's Solver for lists with the propagation of two Constraints: generalized concatenation and size. Experimental results show its better efficiency compared to the intuitive propagation algorithm based on subsequences. The applications of the Solver (with the validation and verification tool BZTT) to different software engineering problems are illustrated by the example of a waiting room model.
-
INAP - Constraint solving for sequences in software validation and verification
Lecture Notes in Computer Science, 2006Co-Authors: Nikolai KosmatovAbstract:Constraint programming techniques are successfully used in various areas of software engineering for industry, commerce, transport, finance etc. Constraint Solvers for different data types are applied in validation and verification of programs containing data elements of these types. A general Constraint Solver for sequences is necessary to take into account this data type in the existing validation and verification tools. In this work, we present an original Constraint Solver for sequences implemented in CHR and based on T. Fruhwirth's Solver for lists with the propagation of two Constraints: generalized concatenation and size. Experimental results show its better efficiency compared to the intuitive propagation algorithm based on subsequences. The applications of the Solver (with the validation and verification tool BZTT) to different software engineering problems are illustrated by the example of a waiting room model.
Markus Triska - One of the best experts on this subject based on the ideXlab platform.
-
the boolean Constraint Solver of swi prolog system description
International Symposium on Functional and Logic Programming, 2016Co-Authors: Markus TriskaAbstract:We present a new Constraint Solver over Boolean variables, available as library(clpb) (documentation: http://eu.swi-prolog.org/man/clpb.html) in SWI-Prolog. Our Solver distinguishes itself from other available CLP(\(\mathcal {B}\)) Solvers by several unique features: First, it is written entirely in Prolog and is hence portable to different Prolog implementations. Second, it is the first freely available BDD-based CLP(\(\mathcal {B}\)) Solver. Third, we show that new interface predicates allow us to solve new types of problems with CLP(\(\mathcal {B}\)) Constraints. We also use our implementation experience to contrast features and state necessary requirements of attributed variable interfaces to optimally support CLP(\(\mathcal {B}\)) Constraints in different Prolog systems. Finally, we also present some performance results and comparisons with SICStus Prolog.
-
the finite domain Constraint Solver of swi prolog
International Symposium on Functional and Logic Programming, 2012Co-Authors: Markus TriskaAbstract:We present a new Constraint Solver over finite domains, freely available as library(clpfd) in SWI-Prolog. Our Solver has several unique features, which we describe in this paper: Reasoning over arbitrarily large integers, always terminating propagation, and a domain-specific language that concisely expresses the full semantics of Constraint reification. The library is entirely written in Prolog and can be easily ported to other Prolog systems that support attributed variables. The Constraint Solver is fast enough for teaching and research purposes and is already being used in courses at several universities in France, Germany, Italy, Austria and other countries.
-
A generalised finite domain Constraint Solver for SWI-Prolog
CTIT technical reports series, 2008Co-Authors: Markus Triska, Ulrich Neumerkel, Jan WielemakerAbstract:In this paper we describe a new Constraint Solver over finite domains that has recently been included in the SWI-Prolog distribution 1. Our Solver generalises finite domain Constraint solving towards unbounded domains, and thus enables a uniform approach to integer arithmetic and Constraints. We ensure termination of all predicates, which facilitates termination proofs of Constraint logic programs. The Solver is written in Prolog and can be quite easily ported to other systems.
Andreas Kuehlmann - One of the best experts on this subject based on the ideXlab platform.
-
a fast pseudo boolean Constraint Solver
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2005Co-Authors: Donald Chai, Andreas KuehlmannAbstract:Linear pseudo-Boolean (LPB) Constraints denote inequalities between arithmetic sums of weighted Boolean functions and provide a significant extension of the modeling power of purely propositional Constraints. They can be used to compactly describe many discrete electronic design automation problems with Constraints on linearly combined, weighted Boolean variables, yet also offer efficient search strategies for proving or disproving whether a satisfying solution exists. Furthermore, corresponding decision procedures can easily be extended for minimizing or maximizing an LPB objective function, thus providing a core optimization method for many problems in logic and physical synthesis. In this paper, we review how recent advances in satisfiability search can be extended for pseudo-Boolean Constraints and describe a new LPB Solver that is based on generalized Constraint propagation and conflict-based learning. We present a comparison with other, state-of-the-art LPB Solvers which demonstrates the overall efficiency of our method.
-
a fast pseudo boolean Constraint Solver
Design Automation Conference, 2003Co-Authors: Donald Chai, Andreas KuehlmannAbstract:Linear Pseudo-Boolean (LPB) Constraints denote inequalities between arithmetic sums of weighted Boolean functions and provide a significant extension of the modeling power of purely propositional Constraints. They can be used to compactly describe many discrete EDA problems with Constraints in linearly combined, parameterized weights, yet also offer efficient search strategies for proving or disproving whether a satisfying solution exists. Furthermore, corresponding decision procedures can easily be extended for minimizing or maximizing an LPB objective function, thus providing a core optimization method for many problems in logic and physical synthesis. In this paper, we review how recent advances in satisfiability (SAT) search can be extended for pseudo-Boolean Constraints and describe a new LPB Solver that is based on generalized Constraint propagation and conflict-based learning.
Eric Monfroy - One of the best experts on this subject based on the ideXlab platform.
-
modular Constraint Solver cooperation via abstract interpretation
arXiv: Artificial Intelligence, 2020Co-Authors: Pierre Talbot, Eric Monfroy, Charlotte TruchetAbstract:Cooperation among Constraint Solvers is difficult because different solving paradigms have different theoretical foundations. Recent works have shown that abstract interpretation can provide a unifying theory for various Constraint Solvers. In particular, it relies on abstract domains which capture Constraint languages as ordered structures. The key insight of this paper is viewing cooperation schemes as abstract domains combinations. We propose a modular framework in which Solvers and cooperation schemes can be seamlessly added and combined. This differs from existing approaches such as SMT where the cooperation scheme is usually fixed (e.g., Nelson-Oppen). We contribute to two new cooperation schemes: (i) interval propagators completion that allows abstract domains to exchange bound Constraints, and (ii) delayed product which exchanges over-approximations of Constraints between two abstract domains. Moreover, the delayed product is based on delayed goal of logic programming, and it shows that abstract domains can also capture control aspects of Constraint solving. Finally, to achieve modularity, we propose the shared product to combine abstract domains and cooperation schemes. Our approach has been fully implemented, and we provide various examples on the flexible job shop scheduling problem. Under consideration for acceptance in TPLP.
-
A reactive and hybrid Constraint Solver
Journal of Experimental & Theoretical Artificial Intelligence, 2013Co-Authors: Eric Monfroy, Carlos Castro, Broderick Crawford, Ricardo Soto, Fernando Paredes, Christian FigueroaAbstract:In Castro et al. [Castro, C., Monfroy, E., Figueroa, C., and Meneses, R. (2005), ‘An Approach for Dynamic Split Strategies in Constraint Solving’, in Proceedings of MICAI 2005 (Vol. 3789), LNAI, Berlin: Springer, pp. 162–174] a framework for adaptive enumeration strategies and meta-backtracks for a propagation-based Constraint Solver has been studied. Here, we extend this framework in order to trigger some functions of a Solver, or of a hybrid Solver to respond to some observations of the solving process. We can also simply design adaptive hybridisation strategies by just changing some rules of the update component of our framework. We experiment with this framework on a hybrid Branch and Bound + propagation Solver in which propagation can be triggered w.r.t. some observations of the solving process. The results show that some phases of propagation are not only beneficial to the Branch and Bound algorithm, but also that propagation is too costly to be executed at each node of the search tree. The hybridis...
-
basic components for Constraint Solver cooperations
ACM Symposium on Applied Computing, 2003Co-Authors: Eric Monfroy, Carlos CastroAbstract:We propose a predefined set of basic components for designing and implementing Constraint Solver cooperations and Solver cooperation languages. Combining these components into patterns enables one to manage computation, control, and coordination needed for Solver cooperations. Our framework has been implemented with the CHR language. We then used it to implement some cooperation primitives, and some Constraint propagation with cooperative components.
-
SAC - Using coordination for cooperative Constraint solving
Proceedings of the 1998 ACM symposium on Applied Computing - SAC '98, 1998Co-Authors: Farhad Arbab, Eric MonfroyAbstract:textabstractIn this paper we argue for an alternative way of designing cooperative Constraint Solver systems using a control-oriented coordination language. The idea is to take advantage of the coordination features of MANIFOLD for improving the Constraint Solver collaboration language of BALI. We demonstrate the validity of our ideas by presenting the advantages of such a realization and its (practical as well as conceptual) improvements of Constraint solving. We are convinced that cooperative Constraint solving is intrinsically linked to coordination, and that coordination languages, and MANIFOLD in particular, open new horizons for systems like BALI.
-
Coordination of heterogeneous distributed cooperative Constraint solving
ACM SIGAPP Applied Computing Review, 1998Co-Authors: Farhad Arbab, Eric MonfroyAbstract:In this paper we argue for an alternative way of designing cooperative Constraint Solver systems using a control-oriented coordination language. The idea is to take advantage of the coordination features of MANIFOLD for improving the Constraint Solver collaboration language of BALI . We demonstrate the validity of our ideas by presenting the advantages of such a realization and its (practical as well as conceptual) improvements of Constraint solving. We are convinced that cooperative Constraint solving is intrinsically linked to coordination, and that coordination languages, and MANIFOLD in particular, open new horizons for systems like BALI .
Farhad Arbab - One of the best experts on this subject based on the ideXlab platform.
-
a component based parallel Constraint Solver
International Conference on Coordination Models and Languages, 2004Co-Authors: Peter Zoeteweij, Farhad ArbabAbstract:As a case study that illustrates our view on coordination and component-based software engineering, we present the design and implementation of a parallel Constraint Solver. The parallel Solver coordinates autonomous instances of a sequential Constraint Solver, which is used as a software component. The component Solvers achieve load balancing of tree search through a time-out mechanism. Experiments show that the purely exogenous mode of coordination employed here yields a viable parallel Solver that effectively reduces turn-around time for Constraint solving on a broad range of hardware platforms.
-
COORDINATION - A component-Based Parallel Constraint Solver
Lecture Notes in Computer Science, 2004Co-Authors: Peter Zoeteweij, Farhad ArbabAbstract:As a case study that illustrates our view on coordination and component-based software engineering, we present the design and implementation of a parallel Constraint Solver. The parallel Solver coordinates autonomous instances of a sequential Constraint Solver, which is used as a software component. The component Solvers achieve load balancing of tree search through a time-out mechanism. Experiments show that the purely exogenous mode of coordination employed here yields a viable parallel Solver that effectively reduces turn-around time for Constraint solving on a broad range of hardware platforms.
-
SAC - Using coordination for cooperative Constraint solving
Proceedings of the 1998 ACM symposium on Applied Computing - SAC '98, 1998Co-Authors: Farhad Arbab, Eric MonfroyAbstract:textabstractIn this paper we argue for an alternative way of designing cooperative Constraint Solver systems using a control-oriented coordination language. The idea is to take advantage of the coordination features of MANIFOLD for improving the Constraint Solver collaboration language of BALI. We demonstrate the validity of our ideas by presenting the advantages of such a realization and its (practical as well as conceptual) improvements of Constraint solving. We are convinced that cooperative Constraint solving is intrinsically linked to coordination, and that coordination languages, and MANIFOLD in particular, open new horizons for systems like BALI.
-
Coordination of heterogeneous distributed cooperative Constraint solving
ACM SIGAPP Applied Computing Review, 1998Co-Authors: Farhad Arbab, Eric MonfroyAbstract:In this paper we argue for an alternative way of designing cooperative Constraint Solver systems using a control-oriented coordination language. The idea is to take advantage of the coordination features of MANIFOLD for improving the Constraint Solver collaboration language of BALI . We demonstrate the validity of our ideas by presenting the advantages of such a realization and its (practical as well as conceptual) improvements of Constraint solving. We are convinced that cooperative Constraint solving is intrinsically linked to coordination, and that coordination languages, and MANIFOLD in particular, open new horizons for systems like BALI .
-
Coordination of heterogeneous distributed cooperative Constraint solving
1998Co-Authors: Farhad Arbab, Eric MonfroyAbstract:textabstractIn this paper we argue for an alternative way of designing cooperative Constraint Solver systems using a control-oriented coordination language. The idea is to take advantage of the coordination features of Manifold for improving the Constraint Solver collaboration language of Bali. We demonstrate the validity of our ideas by presenting the advantages of such a realization and its (practical as well as conceptual) improvements of Constraint solving. We are convinced that cooperative Constraint solving is intrinsically linked to coordination, and that coordination languages, and Manifold in particular, open new horizons for systems like Bali.