Rule-based programming experiences renaissance due to its applications in areas such as Business Rules, Semantic Web, Computational Biology, Verification and Security. Executable rules are used in declarative programm...
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ISBN:
(纸本)9781595933881
Rule-based programming experiences renaissance due to its applications in areas such as Business Rules, Semantic Web, Computational Biology, Verification and Security. Executable rules are used in declarative programming languages, in program transformation and analysis, and for reasoning in artificial intelligence *** Handling Rules (CHR) [6, 8, 11] is a concurrent committed-choice constraint logic programming language consisting of guarded rules that transform multi-sets of atomic formulas (constraints) into simpler ones until exhaustion. CHR was initially developed for solving constraints, but has matured into a general-purpose concurrent constraint language over the last decade, because it can embed many rule-based formalisms and describe algorithms in a declarative way. the clean semantics of CHR facilitates non-trivial program analysis and transformation
We study a generalization of the constraint satisfaction problem (CSP), the periodic constraint satisfaction problem. An input instance of the periodic CSP is a finite set of "generating" constraints over a ...
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We study a generalization of the constraint satisfaction problem (CSP), the periodic constraint satisfaction problem. An input instance of the periodic CSP is a finite set of "generating" constraints over a structured variable set that implicitly specifies a larger, possibly infinite set of constraints;the problem is to decide whether or not the larger set of constraints has a satisfying assignment. this model is natural for studying constraint networks consisting of constraints obeying a high degree of regularity or symmetry. Our main contribution is the identification of two broad polynomial-time tractable subclasses of the periodic CSP.
Previous studies have demonstrated that designing special purpose constraint propagators can significantly improve the efficiency of a constraintprogramming approach. In this paper we present an efficient algorithm f...
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Previous studies have demonstrated that designing special purpose constraint propagators can significantly improve the efficiency of a constraintprogramming approach. In this paper we present an efficient algorithm for bounds consistency propagation of the generalized cardinality constraint (gcc). Using a variety of benchmark and random problems, we show that on some problems our bounds consistency algorithm can dramatically outperform existing state-of-the-art commercial implementations of constraint propagators for the gcc. We also present a new algorithm for domain consistency propagation of the gcc which improves on the worst-case performance of the best previous algorithm for problems that occur often in applications.
COMET is an object-oriented language supporting a constraint-based architecture for local search through declarative and search components. this paper proposes three novel and lightweight control abstractions for the ...
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COMET is an object-oriented language supporting a constraint-based architecture for local search through declarative and search components. this paper proposes three novel and lightweight control abstractions for the search component, significantly enhancing the compositionality, modularity, and reuse of COMET programs. these abstractions, which includes events and checkpoints, rely on first-class closures as the enabling technology. they are especially useful for expressing, in a modular way, heuristic and meta-heuristics, unions of heterogeneous neighborhoods, and sequential composition of neighborhoods.
Modeling and programming tools for neighborhood search often support invariants, i.e., data structures specified declaratively and automatically maintained incrementally under changes. this paper considers invariants ...
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Modeling and programming tools for neighborhood search often support invariants, i.e., data structures specified declaratively and automatically maintained incrementally under changes. this paper considers invariants for longest paths in directed acyclic graphs, a fundamental abstraction for many applications. It presents bounded incremental algorithms for arc insertion and deletion which run in O ( ||delta|| + |delta| log |delta|) time and O ( ||delta||) time respectively, where |delta| and ||delta|| are measures of the change in the input and output. the paper also shows how to generalize the algorithm to various classes of multiple insertions/ deletions encountered in scheduling applications. Preliminary experimental results show that the algorithms behave well in practice.
this article follows a tutorial, given by the authors on dynamic constraint solving at CP 2003 (Ninthinternationalconference on principles and practice of constraintprogramming) in Kinsale, Ireland (Verfaillie, G.,...
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this article follows a tutorial, given by the authors on dynamic constraint solving at CP 2003 (Ninthinternationalconference on principles and practice of constraintprogramming) in Kinsale, Ireland (Verfaillie, G., & Jussien, N. (2003). It aims at offering an overview of the main approaches and techniques that have been proposed in the domain of constraint satisfaction to deal with uncertain and dynamic environments.
We study a generalization of the constraint satisfaction problem (CSP), the periodic constraint satisfaction problem. An input instance of the periodic CSP is a finite set of "generating" constraints over a ...
详细信息
We study a generalization of the constraint satisfaction problem (CSP), the periodic constraint satisfaction problem. An input instance of the periodic CSP is a finite set of "generating" constraints over a structured variable set that implicitly specifies a larger, possibly infinite set of constraints;the problem is to decide whether or not the larger set of constraints has a satisfying assignment. this model is natural for studying constraint networks consisting of constraints obeying a high degree of regularity or symmetry. Our main contribution is the identification of two broad polynomial-time tractable subclasses of the periodic CSP.
A constraint is a relation with an active behavior. For a given relation, we propose to learn a representation adapted to this active behavior. It yields two contributions. the first is a generic metatechnique for cla...
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ISBN:
(纸本)3540292438
A constraint is a relation with an active behavior. For a given relation, we propose to learn a representation adapted to this active behavior. It yields two contributions. the first is a generic metatechnique for classifier improvement showing performances comparable to boosting. the second lies in the ability of using the learned concept in constraint-based decision or optimization problems. It opens a new way of integrating Machine Learning in Decision Support Systems.
Modeling and programming tools for neighborhood search often support invariants, i.e., data structures specified declaratively and automatically maintained incrementally under changes. this paper considers invariants ...
详细信息
Modeling and programming tools for neighborhood search often support invariants, i.e., data structures specified declaratively and automatically maintained incrementally under changes. this paper considers invariants for longest paths in directed acyclic graphs, a fundamental abstraction for many applications. It presents bounded incremental algorithms for arc insertion and deletion which run in O ( ||delta|| + |delta| log |delta|) time and O ( ||delta||) time respectively, where |delta| and ||delta|| are measures of the change in the input and output. the paper also shows how to generalize the algorithm to various classes of multiple insertions/ deletions encountered in scheduling applications. Preliminary experimental results show that the algorithms behave well in practice.
Previous studies have demonstrated that designing special purpose constraint propagators can significantly improve the efficiency of a constraintprogramming approach. In this paper we present an efficient algorithm f...
详细信息
Previous studies have demonstrated that designing special purpose constraint propagators can significantly improve the efficiency of a constraintprogramming approach. In this paper we present an efficient algorithm for bounds consistency propagation of the generalized cardinality constraint (gcc). Using a variety of benchmark and random problems, we show that on some problems our bounds consistency algorithm can dramatically outperform existing state-of-the-art commercial implementations of constraint propagators for the gcc. We also present a new algorithm for domain consistency propagation of the gcc which improves on the worst-case performance of the best previous algorithm for problems that occur often in applications.
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