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32nd International Conference on Logic programming (ICLP)

作者： Redl, Christoph Vienna Univ Technol Inst Informat Syst Favoritenstr 9-11 A-1040 Vienna Austria

The DLVHEX system implements the hex-semantics, which integrates answer set programming (ASP) with arbitrary external sources. Since its first release ten years ago, significant advancements were achieved. Most importantly, the exploitation of properties of external sources led to efficiency improvements and flexibility enhancements of the language, and technical improvements on the system side increased user's convenience. In this paper, we present the current status of the system and point out the most important recent enhancements over early versions. While existing literature focuses on theoretical aspects and specific components, a bird's eye view of the overall system is missing. In order to promote the system for real-world applications, we further present applications which were already successfully realized on top of DLVHEX.

关键词： answer set programming Nonmonotonic Reasoning Knowledge representation

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Influence of ASP Language Constructs on the Performance of State-of-the-Art Solvers 39th

Influence of ASP Language Constructs on the Performance of S...

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39th Annual German Conference on Artificial Intelligence (KI)

作者： Taupe, Richard Teppan, Erich Alpen Adria Univ Klagenfurt Univ Str 65-67 A-9020 Klagenfurt Austria Siemens AG Osterreich Corp Technol Siemensstr 90 A-1210 Vienna Austria

ISBN: (纸本)9783319460734;9783319460727

answer set programming (ASP) under the stable model semantics supports various language constructs which can be used to express the same realities in syntactically different, but semantically equivalent ways. However, these equivalent programs may not perform equally well. This is because performance depends on the underlying solver implementations that may treat different language constructs differently. As performance is very important for the successful application of ASP in real-life domains, knowledge about the mutual interchangeability and performance of ASP language constructs is crucial for knowledge engineers. In this article, we present an investigation on how the usage of different language constructs affects the performance of stateof-the-art solvers and grounders on benchmark problems from the ASP competition. Hereby, we focus on constructs used to express disjunction or choice, classical negation, and various aggregate functions. Some interesting effects of language constructs on solving performance are revealed.

关键词： answer set programming Evaluation ASP Competition

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An Exercise in Declarative Modeling for Relational Query Mining 1

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25th International Conference on Inductive Logic programming (ILP)

作者： Paramonov, Sergey van Leeuwen, Matthijs Denecker, Marc De Raedt, Luc Katholieke Univ Leuven Celestijnenlaan 200A B-3001 Heverlee Belgium

ISBN: (数字)9783319405667

ISBN: (纸本)9783319405667;9783319405650

Motivated by the declarative modeling paradigm for data mining, we report on our experience in modeling and solving relational query and graph mining problems with the IDP system, a variation on the answer set programming paradigm. Using IDP or other ASPlanguages for modeling appears to be natural given that they provide rich logical languages for modeling and solving many search problems and that relational query mining (and ILP) is also based on logic. Nevertheless, our results indicate that second order extensions to these languages are necessary for expressing the model as well as for efficient solving, especially for what concerns subsumption testing. We propose such second order extensions and evaluate their potential effectiveness with a number of experiments in subsumption as well as in query mining.

关键词： Knowledge representation answer set programming Data mining Query mining Pattern mining

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Adaptive Reasoning for Context-Sensitive Access Controls 40

Adaptive Reasoning for Context-Sensitive Access Controls

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40th Annual IEEE Computer Software and Applications Conference Symposium (COMPSAC) / Symposium on Software Engineering Technology and Applications (setA)

作者： Sartoli, Sara Namin, Akbar Siami Texas Tech Univ Dept Comp Sci Lubbock TX 79409 USA

ISBN: (纸本)9781467388450

many of the current policy-based management systems implement policies that depend on dynamic operational environment contexts. The existing formal-based approaches for enforcing security policies are mainly expressed using first-order logic. A major drawback of using first-order logic in implementing dynamic policies is that new observations cannot override previously inferred consequences. In fact, a security system whose enterprise policies are implemented using first-order logic is required to have complete access to data in advance in order to be able to perform an informed reasoning and enforce restricting policies. As a major problem, the systems designed based on these first order logic-based approaches are often static, inflexible, and hard to manage and scale. This paper introduces an approach for expressing and enforcing adaptive access control policies dynamically. The paper presents a non-monotonic formal approach based on answer set programming where default policies are explicitly separated from context-dependent and exception policies that often occur in dynamic systems and in particular when the required context data are unavailable ahead of time. The results of presented case study demonstrate the flexibility of the proposed approach compared to the first order logic-based context-sensitive approaches as implemented in Organizational-Based Access Control (ORBAC) model.

关键词： Access Control Formal Analysis Adaptive Security Policies Management answer set programming

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An answer set programming encoding of Prioritized Removed sets Revision: application to GIS

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APPLIED INTELLIGENCE 2010年第1期32卷 60-87页

作者： Benferhat, Salem Ben-Naim, Jonathan Papini, Odile Wuerbel, Eric Univ Artois CNRS CRIL F-62307 Lens France Univ Toulouse 3 CNRS IRIT F-31062 Toulouse 2 France Univ Mediterranee Dept Informat ESIL LSISCNRS F-13288 Marseille 09 France Univ Sud Toulon Var CNRS LSIS F-83957 La Garde France

Geographical information systems are ones of the most important application areas of belief revision. Recently, Wurbel and colleagues (Proceedings of the seventh international conference about principles of knowledge representation and reasoning, KR2000, pp. 505-516, 2000) have applied the so-called "removed sets revision" (RSR) to the problem of assessment of water heights in a flooded valley. The application was partially satisfactory since only a small part of the valley has been handled. This paper goes one step further, and proposes an extension of (RSR) called "Prioritized Removed sets Revision" (PRSR). We show that (PRSR) performed using answer set programming makes possible to solve a practical revision problem provided by a real application in the framework of geographical information system (GIS). We first show how PRSR can be encoded into a logic program with answer set semantics, we then present an adaptation of the smodels system devoted to efficiently compute the answer sets in order to perform PRSR. The experimental study shows that the answer set programming approach gives better results than previous implementations of RSR and in particular it allows to handle the whole valley. Lastly, some experimental studies comparing our encoding with implementations based on SAT-solvers are also provided.

关键词： Belief revision answer set programming Knowledge representation

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Characterizing and extending answer set semantics using possibility theory

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THEORY AND PRACTICE OF LOGIC programming 2015年第1期15卷 79-116页

作者： Bauters, Kim Schockaert, Steven De Cock, Martine Vermeir, Dirk Univ Ghent Dept Appl Math Comp Sci & Stat B-9000 Ghent Belgium Cardiff Univ Sch Comp Sci & Informat Cardiff CF24 3AA S Glam Wales Vrije Univ Brussel Dept Comp Sci B-1050 Brussels Belgium

answer set programming (ASP) is a popular framework for modelling combinatorial problems. However, ASP cannot be used easily for reasoning about uncertain information. Possibilistic ASP (PASP) is an extension of ASP that combines possibilistic logic and ASP. In PASP a weight is associated with each rule, whereas this weight is interpreted as the certainty with which the conclusion can be established when the body is known to hold. As such, it allows us to model and reason about uncertain information in an intuitive way. In this paper we present new semantics for PASP in which rules are interpreted as constraints on possibility distributions. Special models of these constraints are then identified as possibilistic answer sets. In addition, since ASP is a special case of PASP in which all the rules are entirely certain, we obtain a new characterization of ASP in terms of constraints on possibility distributions. This allows us to uncover a new form of disjunction, called weak disjunction, that has not been previously considered in the literature. In addition to introducing and motivating the semantics of weak disjunction, we also pinpoint its computational complexity. In particular, while the complexity of most reasoning tasks coincides with standard disjunctive ASP, we find that brave reasoning for programs with weak disjunctions is easier.

关键词： logic programming answer set programming possibility theory

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Rapid Publication On equivalence of infinitary formulas under the stable model semantics

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THEORY AND PRACTICE OF LOGIC programming 2015年第1期15卷 18-34页

作者： Harrison, Amelia Lifschitz, Vladimir Truszczynski, Miroslaw Univ Texas Austin Dept Comp Sci Austin TX 78712 USA Univ Kentucky Dept Comp Sci Lexington KY 40506 USA

Propositional formulas that are equivalent in intuitionistic logic, or in its extension known as the logic of here-and-there, have the same stable models. We extend this theorem to propositional formulas with infinitely long conjunctions and disjunctions and show how to apply this generalization to proving properties of aggregates in answer set programming.

关键词： answer set programming semantics of aggregates intuitionistic logic strong equivalence

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Ordered completion for logic programs with aggregates

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ARTIFICIAL INTELLIGENCE 2015年 224卷 72-102页

作者： Asuncion, Vernon Chen, Yin Zhang, Yan Zhou, Yi Univ Western Sydney Sch Comp Engn & Math AIRG Penrith NSW 1797 Australia S China Normal Univ Dept Comp Sci Guangzhou Guangdong Peoples R China

We consider the problem of translating first-order answer set programs with aggregates into first-order sentences with the same type of aggregates. In particular, we show that, on finite structures, normal logic programs with convex aggregates, which cover both monotone and antimonotone aggregates as well as the aggregates appearing in most benchmark programs, can always be captured in first-order logic with the same type of aggregates by introducing auxiliary predicates. More precisely, we prove that every finite stable model of a normal program with convex aggregates is corresponding to a classical model of its enhanced ordered completion. This translation then suggests an alternative way for computing the stable models of such kind of programs. We report some experimental results, which demonstrate that our solver GROCv2 is comparable to the state-of-the-art answer set solvers. We further show that convex aggregates form a maximal class for this purpose. That is, we can always construct a normal logic program under any given non-convex aggregate context and prove that it can never be translated into first-order sentences with the same type of aggregates unless NP = coNP. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Knowledge representation and reasoning answer set programming Aggregates First-order logic Logic programming

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Learning Boolean logic models of signaling networks with ASP

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THEORETICAL COMPUTER SCIENCE 2015年 599卷 79-101页

作者： Videla, Santiago Guziolowski, Carito Eduati, Federica Thiele, Sven Gebser, Martin Nicolas, Jacques Saez-Rodriguez, Julio Schaub, Torsten Siegel, Anne IRISA CNRS UMR 6074 F-35042 Rennes France INRIA Dyliss Project F-35042 Rennes France Univ Potsdam Inst Informat D-14482 Potsdam Germany Ecole Cent Nantes IRCCyN UMR CNRS 6597 F-44321 Nantes France European Bioinformat Inst European Mol Biol Lab Hinxton CB10 1SD Cambs England

Boolean networks provide a simple yet powerful qualitative modeling approach in systems biology. However, manual identification of logic rules underlying the system being studied is in most cases out of reach. Therefore, automated inference of Boolean logical networks from experimental data is a fundamental question in this field. This paper addresses the problem consisting of learning from a prior knowledge network describing causal interactions and phosphorylation activities at a pseudo-steady state, Boolean logic models of immediate-early response in signaling transduction networks. The underlying optimization problem has been so far addressed through mathematical programming approaches and the use of dedicated genetic algorithms. In a recent work we have shown severe limitations of stochastic approaches in this domain and proposed to use answer set programming (ASP), considering a simpler problem setting. Herein, we extend our previous work in order to consider more realistic biological conditions including numerical datasets, the presence of feedback-loops in the prior knowledge network and the necessity of multi-objective optimization. In order to cope with such extensions, we propose several discretization schemes and elaborate upon our previous ASP encoding. Towards real-world biological data, we evaluate the performance of our approach over in silico numerical datasets based on a real and large-scale prior knowledge network. The correctness of our encoding and discretization schemes are dealt with in Appendices A-B. (C) 2014 Elsevier B.V. All rights reserved.

关键词： answer set programming Signaling transduction networks Boolean logic models Combinatorial multi-objective optimization Systems biology

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Fuzzy answer set computation via satisfiability modulo theories

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THEORY AND PRACTICE OF LOGIC programming 2015年第4-5期15卷 588-603页

作者： Alviano, Mario Penaloza, Rafael Univ Calabria I-87030 Commenda Di Rende Italy Free Univ Bozen Bolzano Bolzano Italy

Fuzzy answer set programming (FASP) combines two declarative frameworks, answer set programming and fuzzy logic, in order to model reasoning by default over imprecise information. Several connectives are available to combine different expressions;in particular the Godel and Lukasiewicz fuzzy connectives are usually considered, due to their properties. Although the Godel conjunction can be easily eliminated from rule heads, we show through complexity arguments that such a simplification is infeasible in general for all other connectives. The paper analyzes a translation of FASP programs into satisfiability modulo theories (SMT), which in general produces quantified formulas because of the minimality of the semantics. Structural properties of many FASP programs allow to eliminate the quantification, or to sensibly reduce the number of quantified variables. Indeed, integrality constraints can replace recursive rules commonly used to force Boolean interpretations, and completion subformulas can guarantee minimality for acyclic programs with atomic heads. Moreover, head cycle free rules can be replaced by shifted subprograms, whose structure depends on the eliminated head connective, so that ordered completion may replace the minimality check if also Lukasiewicz disjunction in rule bodies is acyclic. The paper also presents and evaluates a prototype system implementing these translations.

关键词： answer set programming fuzzy logic satisfiability modulo theories

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