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Range-based argumentation semantics as two-valued models

theory and practice of logic programming 2017年第1期17卷 75-90页

作者： Osorio, Mauricio Nieves, Juan Carlos Univ Americas Puebla Dept Actuaria Fis & Matemat Cholula 72820 Mexico Umea Univ Dept Comp Sci SE-90187 Umea Sweden

Characterizations of semi-stable and stage extensions in terms of two-valued logical models are presented. To this end, the so-called GL-supported and GL-stage models are defined. These two classes of logical models are logic programming counterparts of the notion of range which is an established concept in argumentation semantics.

关键词： logic programming semantics argumentation semantics non-monotonic reasoning

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logic programming in the context of multiparadigm programming: the Oz experience

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theory and practice of logic programming 2003年第6期3卷 717-763页

作者： Van Roy, P Brand, P Duchier, D Haridi, S Schulte, C Henz, M Catholic Univ Louvain B-1348 Louvain Belgium Swedish Inst Comp Sci S-16428 Kista Sweden Univ Saarland D-66123 Saarbrucken Germany Royal Inst Technol KTH S-16428 Kista Sweden Natl Univ Singapore Singapore 117543 Singapore

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This paper has two goals: to give a tutorial of logic programming in Oz;and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. We give examples that can be run interactively on the Mozart system, which implements Oz, To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Furthermore, as consequences of its multiparadigm nature, the model supports new abilities such as first-class top levels, deep guards, active objects, and sophisticated control of the search process. Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We give a brief history of Oz that traces the development of its main ideas and we summarize the lessons learned from this work. Finally, we give many entry points into the Oz literature.

关键词： multiparadigm programming language design Prolog Oz encapsulated search concurrent constraint programming history software development

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TCHR: a framework for tabled CLP

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theory and practice of logic programming 2008年第4期8卷 491-526页

作者： Schrijvers, Tom Demoen, Bart Warren, David S. Katholieke Univ Leuven Dept Comp Sci Louvain Belgium SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA

Tabled Constraint logic programming is a powerful execution mechanism for dealing with Constraint logic programming without worrying about fixpoint computation. Various applications, e.g. in the fields of program analysis and model checking, have been proposed. Unfortunately, a high-level system for developing new applications is lacking, and programmers are forced to resort to complicated ad hoc solutions. This papers presents TCHR, a high-level framework for tabled Constraint logic programming. It integrates in a light-weight manner Constraint Handling Rules (CHR), a high-level language for constraint solvers, with tabled logic programming. The framework is easily instantiated with new application-specific constraint domains. Various high-level operations can be instantiated to control performance. In particular, we propose a novel, generalized technique for compacting answer sets.

关键词： constraint logic programming constraint handling rules tabled execution

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Optimizing phylogenetic supertrees using answer set programming

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theory and practice of logic programming 2015年第4-5期15卷 604-619页

作者： Koponen, Laura Oikarinen, Emilia Janhunen, Tomi Saila, Laura Aalto Univ HIIT FI-00076 Aalto Finland Aalto Univ Dept Comp Sci FI-00076 Aalto Finland Univ Helsinki Dept Geosci & Geog FIN-00014 Helsinki Finland

The supertree construction problem is about combining several phylogenetic trees with possibly conflicting information into a single tree that has all the leaves of the source trees as its leaves and the relationships between the leaves are as consistent with the source trees as possible. This leads to an optimization problem that is computationally challenging and typically heuristic methods, such as matrix representation with parsimony (MRP), are used. In this paper we consider the use of answer set programming to solve the supertree construction problem in terms of two alternative encodings. The first is based on an existing encoding of trees using substructures known as quartets, while the other novel encoding captures the relationships present in trees through direct projections. We use these encodings to compute a genus-level supertree for the family of cats (Felidae). Furthermore, we compare our results to recent supertrees obtained by the MRP method.

关键词： answer set programming phylogenetic supertree quartets projections Felidae

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On Uniform Equivalence of Epistemic logic Programs

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theory and practice of logic programming 2019年第5-6期19卷 826-840页

作者： Faber, Wolfgang Morak, Michael Woltran, Stefan Univ Klagenfurt Klagenfurt Austria TU Wien Vienna Austria

Epistemic logic Programs (ELPs) extend Answer Set programming (ASP) with epistemic negation and have received renewed interest in recent years. This led to the development of new research and efficient solving systems for ELPs. In practice, ELPs are often written in a modular way, where each module interacts with other modules by accepting sets of facts as input, and passing on sets of facts as output. An interesting question then presents itself: under which conditions can such a module be replaced by another one without changing the outcome, for any set of input facts? This problem is known as uniform equivalence, and has been studied extensively for ASP. For ELPs, however, such an investigation is, as of yet, missing. In this paper, we therefore propose a characterization of uniform equivalence that can be directly applied to the language of state-of-the-art ELP solvers. We also investigate the computational complexity of deciding uniform equivalence for two ELPs, and show that it is on the third level of the polynomial hierarchy.

关键词： logic programming Epistemic Negation Non-monotonic Reasoning Uniform Equivalence

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Mapping fusion and synchronized hyperedge replacement into logic programming

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theory and practice of logic programming 2007年第1-2期7卷 123-151页

作者： Lanese, Ivan Montanari, Ugo Univ Bologna Dept Comp Sci I-40127 Bologna Italy

In this paper we compare three different formalisms that can be used in the area of models for distributed, concurrent and mobile systems. In particular we analyze the relationships between a process calculus, the Fusion Calculus, graph transformations in the Synchronized Hyperedge Replacement with Hoare synchronization (HSHR) approach and logic programming. We present a translation from Fusion Calculus into HSHR (whereas Fusion Calculus uses Milner synchronization) and prove a correspondence between the reduction semantics of Fusion Calculus and HSHR transitions. We also present a mapping from HSHR into a transactional version of logic programming and prove that there is a full correspondence between the two formalisms. The resulting mapping from Fusion Calculus to logic programming is interesting since it shows the tight analogies between the two formalisms, in particular for handling name generation and mobility. The intermediate step in terms of HSHR is convenient since graph transformations allow for multiple, remote synchronizations, as required by Fusion Calculus semantics.

关键词： fusion calculus graph transformation Synchronized Hyperedge Replacement logic programming mobility

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On the Foundations of Grounding in Answer Set programming

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theory and practice of logic programming 2023年第6期23卷 1138-1197页

作者： Kaminski, Roland Schaub, Torsten Univ Potsdam Potsdam Germany

We provide a comprehensive elaboration of the theoretical foundations of variable instantiation, or grounding, in Answer Set programming (ASP). Building on the semantics of ASP's modeling language, we introduce a formal characterization of grounding algorithms in terms of (fixed point) operators. A major role is played by dedicated well-founded operators whose associated models provide semantic guidance for delineating the result of grounding along with on-the-fly simplifications. We address an expressive class of logic programs that incorporates recursive aggregates and thus amounts to the scope of existing ASP modeling languages. This is accompanied with a plain algorithmic framework detailing the grounding of recursive aggregates. The given algorithms correspond essentially to the ones used in the ASP grounder gringo.

关键词： answer set programming grounding theory grounding algorithms

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The PITA system: Tabling and answer subsumption for reasoning under uncertainty

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theory and practice of logic programming 2011年第4-5期11卷 433-449页

作者： Riguzzi, Fabrizio Swift, Terrance Univ Ferrara ENDIF I-44122 Ferrara Italy Univ Nova Lisboa CENTRIA P-1200 Lisbon Portugal

Many real world domains require the representation of a measure of uncertainty. The most common such representation is probability, and the combination of probability with logic programs has given rise to the field of Probabilistic logic programming (PLP), leading to languages such as the Independent Choice logic, logic Programs with Annotated Disjunctions (LPADs), Problog, PRISM, and others. These languages share a similar distribution semantics, and methods have been devised to translate programs between these languages. The complexity of computing the probability of queries to these general PLP programs is very high due to the need to combine the probabilities of explanations that may not be exclusive. As one alternative, the PRISM system reduces the complexity of query answering by restricting the form of programs it can evaluate. As an entirely different alternative, Possibilistic logic Programs adopt a simpler metric of uncertainty than probability. Each of these approaches-general PLP, restricted PLP, and Possibilistic logic programming-can be useful in different domains depending on the form of uncertainty to be represented, on the form of programs needed to model problems, and on the scale of the problems to be solved. In this paper, we show how the PITA system, which originally supported the general PLP language of LPADs, can also efficiently support restricted PLP and Possibilistic logic Programs. PITA relies on tabling with answer subsumption and consists of a transformation along with an API for library functions that interface with answer subsumption. We show that, by adapting its transformation and library functions, PITA can be parameterized to PITA(IND,EXC) which supports the restricted PLP of PRISM, including optimizations that reduce non-discriminating arguments and the computation of Viterbi paths. Furthermore, we show PITA to be competitive with PRISM for complex queries to Hidden Markov Model examples, and sometimes much faster. We further show

关键词： Probabilistic logic programming Possibilistic logic programming Tabling Answer Subsumption Program Transformation

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Well-definedness and efficient inference for probabilistic logic programming under the distribution semantics

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theory and practice of logic programming 2013年第02期13卷 279-302页

作者： Riguzzi, Fabrizio Swift, Terrance Univ Ferrara ENDIF I-44122 Ferrara Italy Univ Nova Lisboa CENTRIA Caparica Portugal

Distribution semantics is one of the most prominent approaches for the combination of logic programming and probability theory. Many languages follow this semantics, such as Independent Choice logic, PRISM, pD, logic Programs with Annotated Disjunctions (LPADs), and ProbLog. When a program contains functions symbols, the distribution semantics is well-defined only if the set of explanations for a query is finite and so is each explanation. Well-definedness is usually either explicitly imposed or is achieved by severely limiting the class of allowed programs. In this paper, we identify a larger class of programs for which the semantics is well-defined together with an efficient procedure for computing the probability of queries. Since logic Programs with Annotated Disjunctions offer the most general syntax, we present our results for them, but our results are applicable to all languages under the distribution semantics. We present the algorithm "Probabilistic Inference with Tabling and Answer subsumption" (PITA) that computes the probability of queries by transforming a probabilistic program into a normal program and then applying SLG resolution with answer subsumption. PITA has been implemented in XSB and tested on six domains: two with function symbols and four without. The execution times are compared with those of ProbLog, cplint, and CVE. PITA was almost always able to solve larger problems in a shorter time, on domains with and without function symbols.

关键词： Probabilistic logic programming Tabling Answer subsumption logic programs with annotated disjunction Program transformation

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Fuzzy linguistic logic programming and its applications

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theory and practice of logic programming 2009年第3期9卷 309-341页

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 Technol Hanoi Vietnam

The paper introduces FUZZY linguistic logic programming, which is a combination of fuzzy logic programming, 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 logic programming, 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 logic programming;(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 logic programming;and (f) an idea of implementing a system to execute fuzzy linguistic logic programs.

关键词： fuzzy logic programming hedge algebra linguistic value linguistic hedge computing with words databases querying threshold computation fuzzy control

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