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19th international conference on logic for programming, Artificial Intelligence, and reasoning, LPAR 2013

作者： Benhamou, Belaïd Domaine univ. S. Jerome Ave. Escadrille Normandie Niemen 13397 Marseille Cedex 20 France Université d'Artois SP 18 Rue Jean Souvraz F 62307 Lens Cedex France

ISBN: (纸本)9783642452208

Many research works had been done in order to define a semantics for logic programs. the well know is the stable model semantics which selects for each program one of its canonical models. the stable models of a logic program are in a certain sens the minimal Herbrand models of its reduct programs. On the other hand, the notion of symmetry elimination had been widely studied in constraint programming and shown to be useful to increase the efficiency of the associated solvers. However symmetry in non monotonic reasoning still not well studied in general. For instance Answer Set programming (ASP) is a very known framework but only few recent works on symmetry breaking are known in this domain. Ignoring symmetry breaking in the answer set systems could make them doing redundant work and lose on their efficiency. Here we study the notion of local and global symmetry in the framework of answer set programming. We show how local symmetries of a logic program can be detected dynamically by means of the automorphisms of its graph representation. We also give some properties that allow to eliminate theses symmetries in SAT-based answer set solvers and show how to integrate this symmetry elimination in these methods in order to enhance their efficiency. © Springer-Verlag 2013.

关键词： Efficiency

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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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eclingo : A Solver for Epistemic logic Programs

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thEORY AND PRACTICE OF logic programming 2020年第6期20卷 834-847页

作者： Cabalar, Pedro Fandinno, Jorge Garea, Javier Romero, Javier Schaub, Torsten Univ A Coruna La Coruna Spain Univ Potsdam Potsdam Germany

We describe eclingo, a solver for epistemic logic programs under Gelfond 1991 semantics built upon the Answer Set programming system clingo. the input language of eclingo uses the syntax extension capabilities of clingo to define subjective literals that, as usual in epistemic logic programs, allow for checking the truth of a regular literal in all or in some of the answer sets of a program. the eclingo solving process follows a guess and check strategy. It first generates potential truth values for subjective literals and, in a second step, it checks the obtained result with respect to the cautious and brave consequences of the program. this process is implemented using the multi-shot functionalities of clingo. We have also implemented some optimisations, aiming at reducing the search space and, therefore, increasing eclingo 's efficiency in some scenarios. Finally, we compare the efficiency of eclingo with two state-of-the-art solvers for epistemic logic programs on a pair of benchmark scenarios and show that eclingo generally outperforms their obtained results.

关键词： Answer Set programming Epistemic logic Programs non-monotonic reasoning Conformant Planning

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Enumeration of Minimal Models and MUSes in WASP 16th

Enumeration of Minimal Models and MUSes in WASP

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16th international conference on logic programming and non-monotonic reasoning (LPNMR)

作者： Alviano, Mario Dodaro, Carmine Fiorentino, Salvatore Previti, Alessandro Ricca, Francesco Dept Math & Comp Sci Arcavacata Di Rende Italy Ericsson Res Stockholm Sweden Univ Calabria Arcavacata Di Rende Italy

ISBN: (纸本)9783031157073;9783031157066

Several AI problems can be conveniently modelled in ASP, and many of them require to enumerate solutions characterized by an optimality property that can be expressed in terms of subset-minimality with respect to some objective atoms. In this context, solutions are often either (i) answer sets or (ii) sets of atoms that enforce the absence of answer sets on the ASP program at hand such sets are referred to as minimal unsatisfiable subsets (MUSes). In both cases, the required enumeration task is currently not supported by state-of-the-art ASP solvers.

关键词： Answer Set programming Enumeration Minimal models MUS

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Modal logic S5 in Answer Set programming with Lazy Creation of Worlds 16th

Modal Logic S5 in Answer Set Programming with Lazy Creation ...

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16th international conference on logic programming and non-monotonic reasoning (LPNMR)

作者： Alviano, Mario Batsakis, Sotiris Baryannis, George Univ Calabria Arcavacata Di Rende Italy Tech Univ Crete Iraklion Greece Univ Huddersfield Sch Comp & Engn Huddersfield W Yorkshire England

ISBN: (纸本)9783031157073;9783031157066

Modal logic S5 is used extensively for representing knowledge that includes statements about necessity and possibility, owing to its simplicity in handling chained modal operators. Significant research effort has been devoted in developing efficient reasoning mechanisms over complex S5 formulas, resulting in various solvers taking advantage of the boolean satisfiability problem (SAT). Among them, the most performant solver implements a heuristic for identifying worlds that can be merged, hence reducing the size of SAT instances to be checked. Recently, Answer Set programming (ASP) has also been considered, and different ASP encodings were proposed and tested, reaching state-of-the-art performance. In particular, a heuristic for identifying the propositional atoms that are relevant in every world resulted in a performance gain in previous experiments. this work addresses the open question of whether the aforementioned two heuristics can be combined, as well as possibly enabling lazy instantiation of the resulting encodings, and what their potential impact is on the performance of the ASP-based solver. Experiments show that lazy creation of worlds provides some further performance gain to the ASP-based solver on the tested instances.

关键词： Modal logic S5 Answer Set programming

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Knowledge acquisition via non-monotonic reasoning in distributed heterogeneous environments 13th

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13th international conference on logic programming and nonmonotonic reasoning, LPNMR 2015

作者： Costantini, Stefania Universitá degli Studi dell’Aquila L’Aquila Italy

ISBN: (纸本)9783319232638

the role of data and knowledge exchange is becoming increasingly important. the approach of DACMAS [1] proposes a quite general modeling of Multi-Agent Systems (MAS), including data representation in a MAS via DRL-Lite Ontologies. Yet, data/knowledge acquisition from heterogeneous sources which are not agents and which are external to the MAS is not provided. In the Knowledge Representation and reasoning field, this topic is coped with by mMCSs (Managed Multi-Context Systems). In this paper, we propose an integration of the two approaches into DACMACSs. the aim is to obtain an enhanced integrated flexible framework where non-monotonicity is present: in the modalities for defining knowledge acquisition;in the conditions for triggering the acquisition and for knowledge exploitation. © Springer international Publishing Switzerland 2015.

关键词： Knowledge acquisition

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17th international conference on logic programming, ICLP 2001

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17th international conference on logic programming, ICLP 2001

ISBN: (纸本)9783540429357

the proceedings contain 31 papers. the special focus in this conference is on logic programming. the topics include: Solving the multiplication constraint in several approximation spaces;design of syntactic program transformations by abstract interpretation of semantic transformations;building real-life applications with prolog;a close look at constraint-based concurrency;probabilistic databases and logic programming;understanding memory management in prolog systems;on a tabling engine that can exploit or-parallelism;revisiting the cardinality operator and introducing the cardinality-path constraint family;optimizing compilation of constraint handling rules;practical aspects for a working compile time garbage collection system for mercury;positive boolean functions as multiheaded clauses;speculative beats conservative justification;local and symbolic bisimulation using tabled constraint logic programming;a simple scheme for implementing tabled logic programming systems based on dynamic reordering of alternatives;ultimate well-founded and stable semantics for logic programs with aggregates;alternating fixed points in boolean equation systems as preferred stable models;semantics of normal logic programs with embedded implications;a multi-adjoint logic approach to abductive reasoning;an order-sorted resolution with implicitly negative sorts;logic programming in a fragment of intuitionistic temporal linear logic;a computational model for functional logic deductive databases and a logic programming approach to the integration, repairing and querying of inconsistent databases.

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Learning to assign degrees of belief in relational domains

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Joint conference of the 17th international conference on Inductive logic programming/24th international conference on Machine Learning

作者： Koriche, Frederic Univ Montpellier 2 LIRMM F-34392 Montpellier 5 France

ISBN: (纸本)3540784683

A recurrent problem in the development of reasoning agents is how to assign degrees of beliefs to uncertain events in a complex environment. the standard knowledge representation framework imposes a sharp separation between learning and reasoning;the agent starts by acquiring a "model" of its environment, represented into an expressive language, and then uses this model to quantify the likelihood of various queries. Yet, even for simple queries, the problem of evaluating probabilities from a general purpose representation is computationally prohibitive. In contrast, this study embarks on the learning to reason (L2R) framework that aims at eliciting degrees of belief in an inductive manner. the agent is viewed as an anytime reasoner that iteratively improves its performance in light of the knowledge induced from its mistakes. Indeed, by coupling exponentiated gradient strategies in learning and weighted model counting techniques in reasoning, the L2R framework is shown to provide efficient solutions to relational probabilistic reasoning problems that are provably intractable in the classical paradigm.

关键词： learning to reason online learning relational probabilistic reasoning exponentiated gradient learning Markov networks weighted model counting

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Towards rational closure for fuzzy logic: the case of propositional Gödel logic

Towards rational closure for fuzzy logic: The case of propos...

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19th international conference on logic for programming, Artificial Intelligence, and reasoning, LPAR 2013

作者： Casini, Giovanni Straccia, Umberto Centre for Artificial Intelligence Research CSIR Meraka Institute UKZN South Africa Pisa Italy

ISBN: (纸本)9783642452208

In the field of non-monotonic logics, the notion of rational closure is acknowledged as a landmark and we are going to see whether such a construction can be adopted in the context of mathematical fuzzy logic, a so far (apparently) unexplored journey. As a first step, we will characterise rational closure in the context of Propositional Gödel logic. © Springer-Verlag 2013.

关键词： Fuzzy logic

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Collective Entity Resolution in Familial Networks 17

Collective Entity Resolution in Familial Networks

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17th IEEE international conference on Data Mining (ICDMW)

作者： Kouki, Pigi Pujara, Jay Marcum, Christopher Koehly, Laura Getoor, Lise Univ Calif Santa Cruz Sch Engn Santa Cruz CA 95064 USA NHGRI NIH Bethesda MD 20892 USA

ISBN: (纸本)9781538638354

Entity resolution in settings with rich relational structure often introduces complex dependencies between co-references. Exploiting these dependencies is challenging - it requires seamlessly combining statistical, relational, and logical dependencies. One task of particular interest is entity resolution in familial networks. In this setting, multiple partial representations of a family tree are provided, from the perspective of different family members, and the challenge is to reconstruct a family tree from these multiple, noisy, partial views. this reconstruction is crucial for applications such as understanding genetic inheritance, tracking disease contagion, and performing census surveys. Here, we design a model that incorporates statistical signals, such as name similarity, relational information, such as sibling overlap, and logical constraints, such as transitivity and bijective matching, in a collective model. We show how to integrate these features using probabilistic soft logic, a scalable probabilistic programming framework. In experiments on real-world data, our model significantly outperforms state-of-the-art classifiers that use relational features but are incapable of collective reasoning.

关键词： Probabilistic logic programming History Electronic mail Image color analysis Diabetes

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