In this paper we present a successful application of logic programming for e-tourism: the iTravel system. The system exploits two technologies that are based on the state-of-the-art computational logic system DLV: (i)...
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In this paper we present a successful application of logic programming for e-tourism: the iTravel system. The system exploits two technologies that are based on the state-of-the-art computational logic system DLV: (i) a system for ontology representation and reasoning, called OntoDLV;and, (ii) HlLeX a semantic information-extraction tool. The core of iTravel is an ontology which models the domain of tourism offers. The ontology is automatically populated by extracting the information contained in the tourism leaflets produced by tour operators. A set of specifically devised logic programs is used to reason on the information contained in the ontology for selecting the holiday packages that best fit the customer needs. An intuitive web-based user interface eases the task of interacting with the system for both the customers and the operators of a travel agency.
Querying over disjunctive ASP with functions is a highly undecidable task in general. In this paper we focus on disjunctive logic programs with stratified negation and functions under the stable model semantics (ASP(f...
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Querying over disjunctive ASP with functions is a highly undecidable task in general. In this paper we focus on disjunctive logic programs with stratified negation and functions under the stable model semantics (ASP(fs)). We show that query answering in this setting is decidable, if the query is finitely recursive (ASP(fr)(fs)). Our proof yields also an effective method for query evaluation. It is done by extending the magic set technique to ASP(fr)(fs). We show that the magic-set rewritten program is query equivalent to the original one (under both brave and cautious reasoning). Moreover, we prove that the rewritten program is also finitely ground, implying that it is decidable. Importantly, finitely ground programs are evaluable using existing ASP solvers, making the class of ASP(fr)(fs) queries usable in practice.
In the current practice of answer set programming (ASP), evaluable functions are represented as special kinds of relations. This often makes the resulting program unnecessarily large when instantiated over a large dom...
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In the current practice of answer set programming (ASP), evaluable functions are represented as special kinds of relations. This often makes the resulting program unnecessarily large when instantiated over a large domain. The extra constraints needed to enforce the relation as a function also make the logic program less transparent. In this paper, we consider adding evaluable functions to answerset logic programs. The class of logic programs that we consider here is that of weight constraint programs, which are widely used in ASP. We propose an answerset semantics to these extended weight constraint programs and define loop completion to characterize the semantics. Computationally, we provide a translation from loop completions of these programs to instances of the Constraint Satisfaction Problem (CSP) and use the off-the-shelf CSP solvers to compute the answersets of these programs. A main advantage of this approach is that global constraints implemented in such CSP solvers become available to ASP. The approach also provides a new encoding for CSP problems in the style of weight constraint programs. We have implemented a prototype system based on these results, and our experiments show that this prototype system competes well with the state-of-the-art ASP solvers. In addition, we illustrate the utilities of global constraints in the ASP context.
answer set programming (ASP) is a novel logic programming paradigm, that has already had a profound impact in several application domains, especially in the areas of knowledge representation and reasoning. In spite of...
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answer set programming (ASP) is a novel logic programming paradigm, that has already had a profound impact in several application domains, especially in the areas of knowledge representation and reasoning. In spite of the development of excellent inference engines for ASP, efficiency and scalability remain challenging aspects that prevent the use of ASP in various real-world domains. Parallelism has been identified as a natural avenue to address these problems. This paper describes the design of a complete ASP parallel engine, derived from the basic design of the SMODELS architecture. The paper places emphasis on addressing the problem of the irregular structure of the search trees generated by typical ASP computations (in a SMODELS-like computation), which requires the use of dynamic load balancing mechanisms. The paper provides a systematic investigation of alternative strategies for dynamic scheduling and task sharing. These are the two components that more directly affect the efficiency of a parallel engine. (c) 2009 Elsevier Ltd. All rights reserved.
Unlike conventional rule based knowledge bases (KBs) that support monotonic reasoning, a key correctness issue, i.e. the correctness of a sub-KB with respect to the full KB, arises when using a KB represented by non-m...
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Unlike conventional rule based knowledge bases (KBs) that support monotonic reasoning, a key correctness issue, i.e. the correctness of a sub-KB with respect to the full KB, arises when using a KB represented by non-monotonic reasoning languages such as answer set programming (ASP). Since a user may have rights to access only a subset of a KB, the non-monotonic nature of ASP may cause the occurrence of consequences, which are erroneous in the sense that the consequences are not reasonable in the full KB. This paper proposes an approach dealing with the problem. The main idea is to let the usage of Closed World Assumptions (CWAs) for literals in a KB satisfy certain constraints. Two kinds of access right propositions are created, rule retrieval right propositions to control the access to rules, and CWA right propositions to control the usage of CWAs for literals. Based on these right propositions, this paper first defines an algorithm for translating an original KB into a KB tagged by right propositions, and then discusses the right dependency in a KB and proposes methods for checking and obtaining a set of rights that is closed under a set of dependency rules. Finally, several results on the correctness of a set of rights in a KB are presented, which serve as guidelines for the correct use of a KB. As an example, a KB of illness-related financial support for teachers of a university is presented to illustrate the application of our approach. (C) 2010 Elsevier B.V. All rights reserved.
In previous work we have proposed an extension to ASP (answer set programming), called RASP, standing for ASP with Resources. RASP supports declarative reasoning on production and consumption of (amounts of) resources...
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In previous work we have proposed an extension to ASP (answer set programming), called RASP, standing for ASP with Resources. RASP supports declarative reasoning on production and consumption of (amounts of) resources. The approach combines answerset semantics with quantitative reasoning and relies on an algebraic structure to support computations and comparisons of amounts. The RASP framework provides some form of preference reasoning on resources usage. In this paper, we go further in this direction by introducing expressive constructs for supporting complex preferences specification on aggregate resources. We present a refinement of the semantics of RASP so as to take into account the new constructs. For all the extensions, we provide an encoding into plain ASP. We prove that the complexity of establishing the existence of an answerset, in such an enriched framework, remains NP-complete as in ASP. Finally, we report on raspberry, a prototypical implementation of RASP. This tool consists of a compiler that, given a ground RASP program, produces a pure ASP encoding suitable to be processed by commonly available ASP-solvers.
answer set programming ( ASP) emerged in the late 1990s as a new logic programming paradigm that has been successfully applied in various application domains. Also motivated by the availability of efficient solvers fo...
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answer set programming ( ASP) emerged in the late 1990s as a new logic programming paradigm that has been successfully applied in various application domains. Also motivated by the availability of efficient solvers for propositional satisfiability ( SAT), various reductions from logic programs to SAT were introduced. All these reductions, however, are limited to a subclass of logic programs or introduce new variables or may produce exponentially bigger propositional formulas. In this paper, we present a SAT-based procedure, called ASP-SAT, that ( 1) deals with any (nondisjunctive) logic program, ( 2) works on a propositional formula without additional variables ( except for those possibly introduced by the clause form transformation), and ( 3) is guaranteed to work in polynomial space. From a theoretical perspective, we prove soundness and completeness of ASP-SAT. From a practical perspective, we have ( 1) implemented ASP-SAT in CMODELS, ( 2) extended the basic procedures in order to incorporate the most popular SAT reasoning strategies, and ( 3) conducted an extensive comparative analysis involving other state-of-the-art answerset solvers. The experimental analysis shows that our solver is competitive with the other solvers we considered and that the reasoning strategies that work best on 'small but hard' problems are ineffective on 'big but easy' problems and vice versa.
The need for integration of ontologies with nonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantic...
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The need for integration of ontologies with nonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantics for hybrid knowledge bases composed of both an ontology (expressed in a fragment of first-order logic) and nonmonotonic rules. These semantics have matured over the years, but only provide solutions for the static case when knowledge does not need to evolve. In this paper we take a first step towards addressing the dynamics of hybrid knowledge bases. We focus on knowledge updates and, considering the state of the art of belief update, ontology update and rule update, we show that current solutions are only partial and difficult to combine. Then we extend the existing work on ABox updates with rules, provide a semantics for such evolving hybrid knowledge bases and study its basic properties. To the best of our knowledge, this is the first time that an update operator is proposed for hybrid knowledge bases.
This paper develops automated testing and debugging techniques for answerset solver development. We describe a flexible grammar-based black-box ASP fuzz testing tool which is able to reveal various defects such as un...
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This paper develops automated testing and debugging techniques for answerset solver development. We describe a flexible grammar-based black-box ASP fuzz testing tool which is able to reveal various defects such as unsound and incomplete behavior, i.e. invalid answersets and inability to find existing solutions, in state-of-the-art answerset solver implementations. Moreover, we develop delta debugging techniques for shrinking failure-inducing inputs on which solvers exhibit defective behavior. In particular, we develop a delta debugging algorithm in the context of answerset solving, and evaluate two different elimination strategies for the algorithm.
We present a new approach to enhancing answer set programming (ASP) with Constraint Processing techniques which allows for solving interesting Constraint Satisfaction Problems in ASP. We show how constraints on finite...
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We present a new approach to enhancing answer set programming (ASP) with Constraint Processing techniques which allows for solving interesting Constraint Satisfaction Problems in ASP. We show how constraints on finite domains can be decomposed into logic programs such that unit-propagation achieves arc, bound or range consistency. Experiments with our encodings demonstrate their computational impact.
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