This paper introduced logicprogramming into the dynamic scheduling model based on controlled hybrid Petri nets and event logic nets. logicprogramming represents the experience rules of human beings when resolving ac...
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This paper introduced logicprogramming into the dynamic scheduling model based on controlled hybrid Petri nets and event logic nets. logicprogramming represents the experience rules of human beings when resolving actual problems. The resolution of the logicprogramming model is taken as the mark of the continuous control places in controlled hybrid Petri nets to realize the control of the controlled continuous transitions. Finally a typical example of chemical production process is given to illustrate the validity of the theory.
We present the CIFF proof procedure for abductive logicprogramming with constraints, and we prove its correctness. CIFF is an extension of the IFF proof procedure for abductive logicprogramming, relaxing the origina...
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We present the CIFF proof procedure for abductive logicprogramming with constraints, and we prove its correctness. CIFF is an extension of the IFF proof procedure for abductive logicprogramming, relaxing the original restrictions over variable quantification (allowedness conditions) and incorporating a constraint solver to deal with numerical constraints as in constraint logicprogramming. 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.
On the one hand, termination analysis of logic programs is now a fairly established research topic within the logicprogramming community. On the other hand, non-termination analysis seems to remain a much less attrac...
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On the one hand, termination analysis of logic programs is now a fairly established research topic within the logicprogramming community. On the other hand, non-termination analysis seems to remain a much less attractive Subject. If we divide this line of research into two kinds of approaches, dynamic versus static analysis, this paper belongs to the latter. It proposes a criterion for detecting non-terminating atomic queries with respect to binary constraint logicprogramming (CLP) rules, which strictly generalizes our previous works on this subject. We give a generic operational definition and an implemented logical form of this criterion. Then we show that the logical form is correct and complete with respect to the operational definition.
Approximate probabilistic model checking, and more generally sampling based model checking methods, proceed by drawing independent executions of a given model and by checking a temporal formula on these executions. In...
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Approximate probabilistic model checking, and more generally sampling based model checking methods, proceed by drawing independent executions of a given model and by checking a temporal formula on these executions. In theory, these methods can be easily massively parallelized, but in practice one has to consider, for this purpose, important aspects such as the communication paradigm, the physical architecture of the machine, etc. Moreover, being able to develop multiple implementations of this algorithm on architectures as different as a cluster or many-cores requires various levels of expertise that may be problematic to gather. In this paper we propose to investigate the runtime behavior of approximate probabilistic model checking on various state of the art parallel machines - clusters, SMP, hybrid SMP clusters and the Cell processor - using a high-level parallel programming tool based on the Bulk Synchronous Parallelism paradigm to quickly instantiate model checking problems over a large variety of parallel architectures. Our conclusion assesses the relative efficiency of these architectures with respect to the algorithm classes and promotes guidelines for further work on parallel APMC implementation.
The paper introduces FUZZY linguistic logicprogramming, which is a combination of fuzzy logicprogramming, introduced by P. Vojtas, and hedge algebras in order to facilitate the representation and reasoning on human ...
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The paper introduces FUZZY linguistic logicprogramming, which is a combination of fuzzy logicprogramming, introduced by P. Vojtas, and hedge algebras in order to facilitate the representation and reasoning on human knowledge expressed in natural languages. In fuzzy linguistic logicprogramming, truth values are linguistic ones, e.g., Very True, Very Probably True and Little False, taken from a hedge algebra of a linguistic truth variable, and linguistic hedges (modifiers) can be used as unary connectives in formulae. This is motivated by the fact that humans reason mostly in terms of linguistic terms rather than in terms of numbers, and linguistic hedges are often used in natural languages to express different levels of emphasis. The paper presents: (a) the language Of fuzzy linguistic logicprogramming;(b) a declarative semantics in terms of Herbrand interpretations and models;(c) a procedural semantics which directly manipulates linguistic terms to Compute a lower bound to the truth Value of a query, and proves its soundness;(d) a fixpoint semantics of logic programs, and based on it, proves the completeness of the procedural semantics;(e) several applications of fuzzy linguistic logicprogramming;and (f) an idea of implementing a system to execute fuzzy linguistic logic programs.
We face the problems of correctness, optimality, and precision for the static analysis of logic programs, using the theory of abstract interpretation. We propose a framework with a denotational, goal-dependent semanti...
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We face the problems of correctness, optimality, and precision for the static analysis of logic programs, using the theory of abstract interpretation. We propose a framework with a denotational, goal-dependent semantics equipped With two unification operators for forward Unification (calling a procedure) and backward unification (returning from a procedure). The latter is implemented through a matching operation. Our proposal clarifies and unifies many different frameworks and ideas oil static analysis of logicprogramming in a single, formal setting. On the abstract side, we focus Oil the domain Sharing by Jacobs and Langen (The Journal of logicprogramming, 1992, vol. 13, nos. 2-3, pp. 291-314) and provide the best correct approximation of all the primitive semantic operators, namely, projection, renaming, and forward and backward unifications. We show that the abstract Unification operators arc strictly more precise than those in the literature defined over the same abstract domain. In some cases, our operators are more precise than those developed for more complex domains involving linearity and freeness.
This paper develops a logical language for representing probabilistic causal laws. Our interest in Such a language is two-fold. First, it can be motivated as a fundamental study of the representation of causal knowled...
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This paper develops a logical language for representing probabilistic causal laws. Our interest in Such a language is two-fold. First, it can be motivated as a fundamental study of the representation of causal knowledge. Causality has an inherent dynamic aspect, which has been studied at the semantical level by Shafer in his framework of probability trees. In such a dynamic context, where the evolution of a domain over time is considered, the idea of a causal law as something which guides this evolution is quite natural. In our formalization, a set of probabilistic causal laws can be used to represent a class of probability trees in a concise, flexible and modular way. In this way, Our work extends Shafer's by offering a convenient logical representation for his semantical objects. Second, this language also has relevance for the area of probabilistic logicprogramming. In particular, we prove that the formal semantics of a theory in Our language can be equivalently defined as a probability distribution over the well-founded models of certain logic programs, rendering it formally quite similar to existing languages Such as ICL or PRISM. Because we can motivate and explain Our language in a completely self-contained way as a representation of probabilistic causal laws, this provides a new way of explaining the intuitions behind such probabilistic logic programs: we can say precisely which knowledge such a program expresses, in terms that are equally understandable by a non-logician. Moreover, we also obtain an additional piece of knowledge representation methodology for probabilistic logic programs, by showing how they call express probabilistic causal laws.
A recent framework of relativized hyperequivalence of programs offers a unifying generalization of strong and uniform equivalence. It seems to be especially well suited for applications in program optimization and mod...
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A recent framework of relativized hyperequivalence of programs offers a unifying generalization of strong and uniform equivalence. It seems to be especially well suited for applications in program optimization and modular programming due to its flexibility that allows us to restrict, independently of each other, the head and body alphabets in context programs. We study relativized hyperequivalence for the three semantics of logic programs given by stable, supported, and supported minimal models. For each semantics, we identify four types of contexts, depending on whether the head and body alphabets are given directly or as the complement of a given set. Hyperequivalence relative to contexts where the head and body alphabets are specified directly has been studied before. In this paper, we establish the complexity of deciding relativized hyperequivalence with respect to the three other types of context programs.
The paper introduces the notion of offline justification for answer set programming (ASP). Justifications provide a graph-based explanation of the truth value of an atom with respect to a given answer set. The paper e...
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The paper introduces the notion of offline justification for answer set programming (ASP). Justifications provide a graph-based explanation of the truth value of an atom with respect to a given answer set. The paper extends also this notion to provide justification of atoms during the computation of an answer set (on-line justification) and presents an integration of online justifications within the computation model Of SMODELS. Offline and online justifications provide useful tools to enhance understanding of ASP, and they offer a basic data structure to support methodologies and tools for debugging answer set programs. A preliminary implementation has been developed in ASP - PROLOG.
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