14,675 research outputs found

    A Proof Theoretic View of Constraint Programming

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    We provide here a proof theoretic account of constraint programming that attempts to capture the essential ingredients of this programming style. We exemplify it by presenting proof rules for linear constraints over interval domains, and illustrate their use by analyzing the constraint propagation process for the {\tt SEND + MORE = MONEY} puzzle. We also show how this approach allows one to build new constraint solvers.Comment: 25 page

    An Effective Fixpoint Semantics for Linear Logic Programs

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    In this paper we investigate the theoretical foundation of a new bottom-up semantics for linear logic programs, and more precisely for the fragment of LinLog that consists of the language LO enriched with the constant 1. We use constraints to symbolically and finitely represent possibly infinite collections of provable goals. We define a fixpoint semantics based on a new operator in the style of Tp working over constraints. An application of the fixpoint operator can be computed algorithmically. As sufficient conditions for termination, we show that the fixpoint computation is guaranteed to converge for propositional LO. To our knowledge, this is the first attempt to define an effective fixpoint semantics for linear logic programs. As an application of our framework, we also present a formal investigation of the relations between LO and Disjunctive Logic Programming. Using an approach based on abstract interpretation, we show that DLP fixpoint semantics can be viewed as an abstraction of our semantics for LO. We prove that the resulting abstraction is correct and complete for an interesting class of LO programs encoding Petri Nets.Comment: 39 pages, 5 figures. To appear in Theory and Practice of Logic Programmin

    Value withdrawal explanations: a theoretical tool for programming environments

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    Constraint logic programming combines declarativity and efficiency thanks to constraint solvers implemented for specific domains. Value withdrawal explanations have been efficiently used in several constraints programming environments but there does not exist any formalization of them. This paper is an attempt to fill this lack. Furthermore, we hope that this theoretical tool could help to validate some programming environments. A value withdrawal explanation is a tree describing the withdrawal of a value during a domain reduction by local consistency notions and labeling. Domain reduction is formalized by a search tree using two kinds of operators: operators for local consistency notions and operators for labeling. These operators are defined by sets of rules. Proof trees are built with respect to these rules. For each removed value, there exists such a proof tree which is the withdrawal explanation of this value.Comment: 14 pages; Alexandre Tessier, editor; WLPE 2002, http://xxx.lanl.gov/abs/cs.SE/020705

    Extensional and Intensional Strategies

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    This paper is a contribution to the theoretical foundations of strategies. We first present a general definition of abstract strategies which is extensional in the sense that a strategy is defined explicitly as a set of derivations of an abstract reduction system. We then move to a more intensional definition supporting the abstract view but more operational in the sense that it describes a means for determining such a set. We characterize the class of extensional strategies that can be defined intensionally. We also give some hints towards a logical characterization of intensional strategies and propose a few challenging perspectives

    The CIFF Proof Procedure for Abductive Logic Programming with Constraints: Theory, Implementation and Experiments

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    We present the CIFF proof procedure for abductive logic programming with constraints, and we prove its correctness. CIFF is an extension of the IFF proof procedure for abductive logic programming, relaxing the original restrictions over variable quantification (allowedness conditions) and incorporating a constraint solver to deal with numerical constraints as in constraint logic programming. Finally, we describe the CIFF system, comparing it with state of the art abductive systems and answer set solvers and showing how to use it to program some applications. (To appear in Theory and Practice of Logic Programming - TPLP)
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