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A refinement operator based learning algorithm for the ALC description logic

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

作者： Lehmann, Jens Hitzler, Pascal Univ Leipzig Dept Comp Sci Johannisgasse 26 D-04103 Leipzig Germany Univ Karlsruhe TH AIFB Inst D-76128 Karlsruhe Germany

ISBN: (纸本)9783540784685

With the advent of the Semantic Web, description logics have become one of the most prominent paradigms for knowledge representation and reasoning. Progress in research and applications, however, faces a bottleneck due to the lack of available knowledge bases, and it is paramount that suitable automated methods for their acquisition will be developed. In this paper, we provide the first learning algorithm based on refinement operators for the most fundamental description logic ALC. We develop the algorithm from thorough theoretical foundations and report on a prototype implementation.

关键词： Learning algorithms

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the System BioC for reasoning about Biological Models in Action Language C

The System BioC for Reasoning about Biological Models in Act...

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20th IEEE international conference on Tools with artificial intelligence

作者： Dworschak, Steve Grote, Torsten Koenig, Ame Schaub, Torsten Veber, Philippe Univ Potsdam Inst Informat D-14882 Potsdam Germany

ISBN: (纸本)9780769534404

We elaborate upon the usage of action language C for representing and reasoning about biological models. First, we provide a simple extension of C allowing for variables and show its usefulness in modeling biochemical reactions according to the well-known model of BIOCHAM. Second, we show how the biological action description language C-TAID can be mapped onto C. Finally, we describe a toolbox for using action languages, including among them, a compiler mapping C and C-TAID to logic programs under answer sets semantics along with a web-service integrating different front- and back-ends for addressing dynamical systems by means of action description languages via answer set programming. this is accompanied by an empirical evaluation with existing systems for processing action description languages.

关键词： Web services

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Combining answer set programming with description logics for the semantic Web

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artificial intelligence 2008年第12-13期172卷 1495-1539页

作者： Eiter, thomas Ianni, Giovambattista Lukasiewicz, thomas Schindlauer, Roman Tompits, Hans Vienna Univ Technol Inst Informat Syst A-1040 Vienna Austria Univ Oxford Comp Lab Oxford OX1 3DD England Univ Calabria Dipartmento Matemat I-87036 Arcavacata Di Rende Italy

We propose a combination of logic programming under the answer set semantics with the description logics SHIF(D) and SHOIN(D), which underly the Web ontology languages OWL Lite and OWL DL, respectively. To this end, we introduce description logic programs (or di-programs), which consist of a description logic knowledge base L and a finite set P of description logic rules (or dl-rules). Such rules are similar to usual rules in nonmonotonic logic programs, but they may also contain queries to L, possibly under default negation, in their bodies. they allow for building rules on top of ontologies but also, to a limited extent, building ontologies on top of rules. We define a suite of semantics for various classes of dl-programs, which conservatively extend the standard semantics of the respective classes and coincide with it in absence of a description logic knowledge base. More concretely, we generalize positive, stratified, and arbitrary normal logic programs to dl-programs, and define a Herbrand model semantics for them. We show that they have similar properties as ordinary logic programs, and also provide fixpoint characterizations in terms of (iterated) consequence operators. For arbitrary dl-programs, we define answer sets by generalizing Gelfond and Lifschitz's notion of a transform, leading to a strong and a weak answer set semantics, which are based on reductions to the semantics of positive dl-programs and ordinary positive logic programs, respectively. We also show how the weak answer sets can be computed utilizing answer sets of ordinary normal logic programs. Furthermore, we show how some advanced reasoning tasks for the Semantic Web, including different forms of closed-world reasoning and default reasoning, as well as DL-safe rules, can be realized on top of dl-programs. Finally, we give a precise picture of the computational complexity of dl-programs, and we describe efficient algorithms and a prototype implementation of dl-programs which is available on

关键词： answer set programming description logics rules ontologies semantic web computational complexity closed-world reasoning default logic

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A logic programming framework for possibilistic argumentation:: Formalization and logical properties

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FUZZY SETS AND SYSTEMS 2008年第10期159卷 1208-1228页

作者： Alsinet, Teresa Chesnevar, Carlos I. Godo, Lluis Simari, Guillermo R. Univ Lleida Dept Comp Sci Lleida 6925001 Spain UAB Artificial Intelligence Res Inst IIIA Bellaterra Spain Univ Nacl Sur Dept Comp Sci & Engn RA-8000 Bahia Blanca Buenos Aires Argentina

In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. the logic programming paradigm has shown to be particularly useful for developing different argument-based frameworks on the basis of different variants of logic programming which incorporate defeasible rules. Most of such frameworks, however, are unable to deal with both explicit uncertainty and vague knowledge, as defeasibility is directly encoded in the object language. this paper presents possibilistic defeasible logic programming (P-DeLP), a new logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty. Such features are formalized on the basis of PGL, a possibilistic logic based on Godel fuzzy logic. One of the applications of P-DeLP is providing an intelligent agent with non-monotonic, argumentative inference capabilities. In this paper we also provide a better understanding of such capabilities by defining two non-monotonic operators which model the expansion of a given program by adding new weighed facts associated with argument conclusions and warranted literals, respectively. Different logical properties for the proposed operators are studied. (c) 2008 Elsevier B.V. All rights reserved.

关键词： possibilistic logic vague knowledge defeasible argumentation intelligent systems

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logic-free reasoning in Isabelle/Isar

Logic-free reasoning in Isabelle/Isar

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9th international conference on artificial intelligence and Symbolic Computation/15th Symposium on Integration of Symbolic Computation and Mechanized Research/7th international conference on Mathematical Knowledge Management

作者： Berghofer, Stefan Wenzel, Makarius Tech Univ Munich Inst Informat D-85748 Garching Germany

ISBN: (纸本)9783540851097

Traditionally a rigorous mathematical document consists of a sequence of definition - statement - proof. Taking this basic outline as starting point we investigate how these three categories of text can be represented adequately in the formal language of Isabelle/Isar. Proofs represented in human-read able form have been the initial motivation of Isar language design 10 years ago. I he principles developed here allow to turn deductions of the Isabelle logical framework into a format that transcends the raw logical calculus, with more direct description of reasoning using pseudo-natural language elements. Statements describe the main result of a theorem in an open format as a reasoning scheme, saying that in the context of certain parameters and assumptions certain conclusions can be derived. this idea of turning Isar context elements into rule statements has been recently refined to support, the dual form of elimination rules as well. Definitions in their primitive form merely name existing elements of the logical environment, by stating a suitable equation or logical equivalence. Inductive definitions provide a convenient derived principle to describe a new predicate as the closure of given natural deduction rules. Again there is a direct connection to Isar principles, rules stemming from an inductive characterization are immediately available in structured reasoning. All three categories benefit from replacing raw logical encodings by native Isar language elements. the overall formality in the presented mathematical text is reduced. Instead of manipulating auxiliary logical connectives and quantifiers, the mathematical concepts are emphasized.

关键词： Formal languages

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Canonicity!

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4th international Joint conference on Automated reasoning

作者： Dershowitz, Nachum Tel Aviv Univ Sch Comp Sci IL-69978 Ramat Aviv Israel

ISBN: (纸本)9783540710691

We describe an abstract proof-theoretic framework based on normal-form proofs, defined using well-founded orderings on proof objects. this leads to robust notions of canonical presentation and redundancy. Fairness of deductive mechanisms - in this general framework - leads to completeness or saturation. the method has so far been applied to the equational, Horn-clause, and deduction-modulo cases.

关键词： logic programming

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Terminating tableaux for hybrid logic with the difference modality and converse

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4th international Joint conference on Automated reasoning

作者： Kaminski, Mark Smolka, Gert Univ Saarland Programming Syst Lab D-66123 Saarbrucken Germany

ISBN: (纸本)9783540710691

We present the first terminating tableau calculus for basic hybrid logic with the difference modality and converse modalities. the language under consideration is basic multi-modal logic extended with nominals, the satisfaction operator, converse, global and difference modalities. All of the constructs are handled natively. To obtain termination, we extend chain-based blocking for logics with converse by a complete treatment of difference. Completeness of our calculus is shown via a model existence theorem that refines previous constructions by distinguishing between modal and equational state equivalence.

关键词： modal and hybrid logics difference modality converse tableau systems decision procedures

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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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Fixpoint Semantics and Completeness of the Computational Model for Fuzzy Linguistic logic programming

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4th international conference on Intelligent Computing

作者： Le, Van Hung Liu, Fei Tran, Dinh Khang La Trobe Univ Dept Comp Sci & Comp Engn Bundoora Vic 3086 Australia Hanoi Univ Technol Fac Informat Hanoi Vietnam

ISBN: (纸本)9783540859833

Fuzzy linguistic logic programming, which is a result of integrating hedge algebras and fuzzy logic programming, is proposed to facilitate the representation and reasoning on knowledge expressed in natural language, in which vague sentences are usually given a degree of truth stated in linguistic terms rather than a number, and linguistic hedges are very often used. To compute the truth value of a query, a computational model which directly manipulates linguistic terms is provided. the computational model has been proved to be sound. this paper presents a fixpoint semantics for fuzzy linguistic logic programs and based on it proves the completeness of the computational model.

关键词： fuzzy logic programming hedge algebra linguistic value linguistic hedge fixpoint semantics completeness

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Fuzzy Linguistic logic programming

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4th international conference on Intelligent Computing

作者： Le, Van Hung Liu, Fei Tran, Dinh Khang La Trobe Univ Dept Comp Sci & Comp Engn Bundoora Vic 3086 Australia Hanoi Univ Technol Fac Informat Hanoi Vietnam

ISBN: (纸本)9783540859833

this paper presents fuzzy linguistic logic programming which is developed based on fuzzy logic programming introduced by P. Vojtas in order to facilitate the representation and reasoning on knowledge expressed in natural language. In fuzzy linguistic logic programming, truth values are linguistic terms such as true, very true, more or less true, and false taken from a hedge algebra of the truth variable, and linguistic hedges, e.g., very, more or less, quite, and rather, which are frequently used in natural language, can be used as unary connectives in formulae. In order to compute the truth value of a query, we provide a computational model which directly manipulates linguistic terms. the soundness of the computational model is proved. A fixpoint semantics of logic programs and the completeness of the computational model are discussed.

关键词： fuzzy logic programming hedge algebra linguistic value linguistic hedge

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