Results for 'Answer set programming'

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  1.  54
    Answer-set programming encodings for argumentation frameworks.Uwe Egly, Sarah Alice Gaggl & Stefan Woltran - 2010 - Argument and Computation 1 (2):147-177.
    Answer-set programming (ASP) has emerged as a declarative programming paradigm where problems are encoded as logic programs, such that the so-called answer sets of theses programs represent the solutions of the encoded problem. The efficiency of the latest ASP solvers reached a state that makes them applicable for problems of practical importance. Consequently, problems from many different areas, including diagnosis, data integration, and graph theory, have been successfully tackled via ASP. In this work, we present such (...)
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  2.  14
    Hybrid Answer Set Programming.Alex Brik & Jeffrey Remmel - 2014 - Annals of Pure and Applied Logic 165 (1):134-163.
    This paper discusses an extension of Answer Set Programming called Hybrid Answer Set Programming which allows the user to reason about dynamical systems that exhibit both discrete and continuous aspects. The unique feature of Hybrid ASP is that it allows the use of ASP type rules as controls for when to apply algorithms to advance the system to the next position. That is, if the prerequisites of a rule are satisfied and the constraints of the rule (...)
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  3.  12
    Combining answer set programming with description logics for the Semantic Web.Thomas Eiter, Giovambattista Ianni, Thomas Lukasiewicz, Roman Schindlauer & Hans Tompits - 2008 - Artificial Intelligence 172 (12-13):1495-1539.
  4.  19
    Open answer set programming for the semantic web.Stijn Heymans, Davy Van Nieuwenborgh & Dirk Vermeir - 2007 - Journal of Applied Logic 5 (1):144-169.
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  5. Answer Set Programming on Expert Feedback to Populate and Extend.Colin Allen - 2008 - In David Wilson & H. Chad Lane (eds.), Proceedings of the Twenty-First International Florida Artificial Intelligence Research Society Conference. AAAI Press. pp. 500-505.
    dynamic ontologies must be inferred and populated in part from the reference corpora themselves, but ontological rela-.
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  6. What is answer set programming?Vladimir Lifschitz - unknown
    Answer set programming (ASP) is a form of declarative programming oriented towards difficult search problems. As an outgrowth of research on the use of nonmonotonic reasoning in knowledge representation, it is particularly useful in knowledge-intensive applications. ASP programs consist of rules that look like Prolog rules, but the computational mechanisms used in ASP are different: they are based on the ideas that have led to the creation of fast satisfiability solvers for propositional logic.
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  7.  52
    Modelling ethical rules of lying with answer set programming.Jean-Gabriel Ganascia - 2007 - Ethics and Information Technology 9 (1):39-47.
    There has been considerable discussion in the past about the assumptions and basis of different ethical rules. For instance, it is commonplace to say that ethical rules are defaults rules, which means that they tolerate exceptions. Some authors argue that morality can only be grounded in particular cases while others defend the existence of general principles related to ethical rules. Our purpose here is not to justify either position, but to try to model general ethical rules with artificial intelligence formalisms (...)
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  8.  6
    From Felicitous Models to Answer Set Programming.Vladimir Lifschitz - 2023 - In Federico L. G. Faroldi & Frederik Van De Putte (eds.), Kit Fine on Truthmakers, Relevance, and Non-classical Logic. Springer Verlag. pp. 79-96.
    Felicitous models were defined by Kit Fine in 1987 for the purpose of describing the semantics of negation in the programming language Prolog. They are often referred to as stable models, or answer sets. Years later, sophisticated software systems for generating answer sets were designed, and they became the basis of a new programming paradigm, called answer set programming. That programming method is used now for solving computational problems in many areas of science (...)
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  9.  8
    Autoepistemic answer set programming.Pedro Cabalar, Jorge Fandinno & Luis Fariñas del Cerro - 2020 - Artificial Intelligence 289 (C):103382.
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  10.  12
    Answer set programming and plan generation.Vladimir Lifschitz - 2002 - Artificial Intelligence 138 (1-2):39-54.
  11.  15
    Definitions in Answer Set Programming.Vladimir Lifschitz - unknown
    affects the collection of answer sets. In particular, it is useful to be able to describe the effects of adding definitions to a program with nested expressions, in view of the relation of this class of programs to the input language of the answer set programming system sMonELs. In this..
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  12.  14
    Model-based recasting in answer-set programming.Thomas Eiter, Michael Fink, Jörg Pührer, Hans Tompits & Stefan Woltran - 2013 - Journal of Applied Non-Classical Logics 23 (1-2):75-104.
    As is well known, answer-set programs do not satisfy the replacement property in general, i.e., programs and that are equivalent may cease to be so when they are put in the context of some other program, i.e., and may have different answer sets. Lifschitz, Pearce, and Valverde thus introduced strong equivalence for context-independent equivalence, and proved that such equivalence holds between given programs and iff and are equivalent theories in the monotonic logic of here-and-there. In this article, we (...)
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  13.  41
    On the relation between SPARQL1.1 and Answer Set Programming.Axel Polleres & Johannes Peter Wallner - 2013 - Journal of Applied Non-Classical Logics 23 (1-2):159-212.
    In the context of the emerging Semantic Web and the quest for a common logical framework underpinning its architecture, the relation of rule-based languages such as Answer Set Programming (ASP) and ontology languages such as the Web Ontology Language (OWL) has attracted a lot of attention in the literature over the past years. With its roots in Deductive Databases and Datalog though, ASP shares much more commonality with another Semantic Web standard, namely the Simple Protocol and RDF Query (...)
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  14.  6
    Evaluating epistemic negation in answer set programming.Yi-Dong Shen & Thomas Eiter - 2016 - Artificial Intelligence 237 (C):115-135.
  15.  12
    Answers set programs for non-transferable utility games: Expressiveness, complexity and applications.Giovanni Amendola, Gianluigi Greco & Pierfrancesco Veltri - 2022 - Artificial Intelligence 302 (C):103606.
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  16.  3
    Backdoors to tractable answer set programming.Johannes Klaus Fichte & Stefan Szeider - 2015 - Artificial Intelligence 220 (C):64-103.
  17.  8
    Approximate postdictive reasoning with answer set programming.Manfred Eppe & Mehul Bhatt - 2015 - Journal of Applied Logic 13 (4):676-719.
  18.  4
    Semantic forgetting in answer set programming.Thomas Eiter & Kewen Wang - 2008 - Artificial Intelligence 172 (14):1644-1672.
  19.  13
    Computing argumentation semantics in answer set programming.Toshiko Wakaki & Katsumi Nitta - 2009 - In Hiromitsu Hattori, Takahiro Kawamura, Tsuyoshi Ide, Makoto Yokoo & Yohei Murakami (eds.), New Frontiers in Artificial Intelligence: JSAI 2008 Conference and Workshops, Asahikawa, Japan, June 11-13, 2008, Revised Selected Papers. Springer. pp. 254--269.
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  20.  9
    Relating constraint answer set programming languages and algorithms.Yuliya Lierler - 2014 - Artificial Intelligence 207 (C):1-22.
  21.  18
    Mathematical Foundations of Answer Set Programming.Vladimir Lifschitz - unknown
    applied, for instance, to developing a decision support system for the Space Shuttle INogueira et al., 2001] and to graph-theoretic problems arising in..
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  22.  12
    Abstraction for non-ground answer set programs.Zeynep G. Saribatur, Thomas Eiter & Peter Schüller - 2021 - Artificial Intelligence 300 (C):103563.
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  23. Using criticalities as a heuristic for answer set programming.Orkunt Sabuncu, Ferda N. Alpaslan & Varol Akman - 2003 - In Vladimir Lifschitz & Ilkka Niemela (eds.), Logic Programming and Nonmonotonic Reasoning, Lecture Notes in Artificial Intelligence 2923 (7th International Conference, LPNMR 2004, Fort Lauderdale, FL, January 6-8, 2004 Proceedings). Berlin, Heidelberg: Springer. pp. 234-246.
    Answer Set Programming is a new paradigm based on logic programming. The main component of answer set programming is a system that finds the answer sets of logic programs. During the computation of an answer set, systems are faced with choice points where they have to select a literal and assign it a truth value. Generally, systems utilize some heuristics to choose new literals at the choice points. The heuristic used is one of (...)
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  24.  32
    A reductive semantics for counting and choice in answer set programming.Vladimir Lifschitz - unknown
    In a recent paper, Ferraris, Lee and Lifschitz conjectured that the concept of a stable model of a first-order formula can be used to treat some answer set programming expressions as abbreviations. We follow up on that suggestion and introduce an answer set programming language that defines the mean- ing of counting and choice by reducing these constructs to first-order formulas. For the new language, the concept of a safe program is defined, and its semantic role (...)
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  25.  18
    Semantics and complexity of recursive aggregates in answer set programming.Wolfgang Faber, Gerald Pfeifer & Nicola Leone - 2011 - Artificial Intelligence 175 (1):278-298.
  26.  4
    Preferred answer sets for extended logic programs.Gerhard Brewka & Thomas Eiter - 1999 - Artificial Intelligence 109 (1-2):297-356.
  27.  13
    FLP answer set semantics without circular justifications for general logic programs.Yi-Dong Shen, Kewen Wang, Thomas Eiter, Michael Fink, Christoph Redl, Thomas Krennwallner & Jun Deng - 2014 - Artificial Intelligence 213 (C):1-41.
  28.  7
    Pruning external minimality checking for answer set programs using semantic dependencies.Thomas Eiter & Tobias Kaminski - 2021 - Artificial Intelligence 290 (C):103402.
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  29.  16
    A system for the use of answer set programming in reinforcement learning.Matthias Nickles - 2012 - In Luis Farinas del Cerro, Andreas Herzig & Jerome Mengin (eds.), Logics in Artificial Intelligence. Springer. pp. 488--491.
  30.  9
    The complexity and generality of learning answer set programs.Mark Law, Alessandra Russo & Krysia Broda - 2018 - Artificial Intelligence 259:110-146.
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  31.  9
    On the limits of forgetting in Answer Set Programming.Ricardo Gonçalves, Matthias Knorr, João Leite & Stefan Woltran - 2020 - Artificial Intelligence 286 (C):103307.
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  32.  4
    From answer set logic programming to circumscription via logic of GK.Fangzhen Lin & Yi Zhou - 2011 - Artificial Intelligence 175 (1):264-277.
  33.  10
    Belief base change operations for answer set programming.Patrick Krümpelmann & Gabriele Kern-Isberner - 2012 - In Luis Farinas del Cerro, Andreas Herzig & Jerome Mengin (eds.), Logics in Artificial Intelligence. Springer. pp. 294--306.
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  34.  20
    Design and results of the Fifth Answer Set Programming Competition.Francesco Calimeri, Martin Gebser, Marco Maratea & Francesco Ricca - 2016 - Artificial Intelligence 231 (C):151-181.
  35.  7
    Semi-equilibrium models for paracoherent answer set programs.Giovanni Amendola, Thomas Eiter, Michael Fink, Nicola Leone & João Moura - 2016 - Artificial Intelligence 234 (C):219-271.
  36.  4
    Characterizing causal action theories and their implementations in answer set programming.Haodi Zhang & Fangzhen Lin - 2017 - Artificial Intelligence 248 (C):1-8.
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  37.  16
    A general framework for preferences in answer set programming.Gerhard Brewka, James Delgrande, Javier Romero & Torsten Schaub - 2023 - Artificial Intelligence 325 (C):104023.
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  38.  30
    Disjunctive logic programs, answer sets, and the cut rule.Éric Martin - 2022 - Archive for Mathematical Logic 61 (7):903-937.
    In Minker and Rajasekar (J Log Program 9(1):45–74, 1990), Minker proposed a semantics for negation-free disjunctive logic programs that offers a natural generalisation of the fixed point semantics for definite logic programs. We show that this semantics can be further generalised for disjunctive logic programs with classical negation, in a constructive modal-theoretic framework where rules are built from _claims_ and _hypotheses_, namely, formulas of the form \(\Box \varphi \) and \(\Diamond \Box \varphi \) where \(\varphi \) is a literal, respectively, (...)
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  39.  14
    Hybrid planning for challenging construction problems: An Answer Set Programming approach.Faseeh Ahmad, Volkan Patoglu & Esra Erdem - 2023 - Artificial Intelligence 319 (C):103902.
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  40.  18
    ASSAT: computing answer sets of a logic program by SAT solvers.Fangzhen Lin & Yuting Zhao - 2004 - Artificial Intelligence 157 (1-2):115-137.
  41.  21
    Answer Sets and Qualitative Decision Making.Gerhard Brewka - 2005 - Synthese 146 (1-2):171-187.
    Logic programs under answer set semantics have become popular as a knowledge representation formalism in Artificial Intelligence. In this paper we investigate the possibility of using answer sets for qualitative decision making. Our approach is based on an extension of the formalism, called logic programs with ordered disjunction (LPODs). These programs contain a new connective called ordered disjunction. The new connective allows us to represent alternative, ranked options for problem solutions in the heads of rules: A × B (...)
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  42.  16
    Answer Sets and Qualitative Optimization.Gerhard Brewka - 2006 - Logic Journal of the IGPL 14 (3):413-433.
    One of the major reasons for the success of answer set programming in recent years was the shift from a theorem proving to a constraint programming view: problems are represented such that stable models, respectively answer sets, rather than theorems correspond to solutions. This shift in perspective proved extremely fruitful in many areas. We believe that going one step further from a “hard” to a “soft” constraint programming paradigm, or, in other words, to a paradigm (...)
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  43.  16
    On deductive bases for paraconsistent answer set semantics.N. V. Mayatskiy & S. P. Odintsov - 2013 - Journal of Applied Non-Classical Logics 23 (1-2):131-146.
    It was proved by Odintsov and Pearce that the logic is a deductive base for paraconsistent answer set semantics of logic programs with two kinds of negation. Here we describe the lattice of logics extending, characterise these logics via classes of -models, and prove that none of the proper extensions of is a deductive base for PAS.
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  44.  12
    Logic Programming: 20th International Conference, ICLP 2004, Saint-Malo, France, September 6-10, 2004, Proceedings.Bart Demoen & Vladimir Lifschitz - 2004 - Springer Verlag.
    This book constitutes the refereed proceedings of the 20th International Conference on Logic Programming, ICLP 2004, held in Saint-Malo, France in September 2004. The 28 revised full papers and 16 poster papers presented together with 2 invited papers were carefully reviewed and selected from 70 submissions. The papers are organized in topical sections on program analysis, constraints, alternative programming paradigms, answer set programming, and implementation.
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  45. A Deontic Logic for Programming Rightful Machines: Kant’s Normative Demand for Consistency in the Law.Ava Thomas Wright - 2023 - Logics for Ai and Law: Joint Proceedings of the Third International Workshop on Logics for New-Generation Artificial Intelligence (Lingai) and the International Workshop on Logic, Ai and Law (Lail).
    In this paper, I set out some basic elements of a deontic logic with an implementation appropriate for handling conflicting legal obligations for purposes of programming autonomous machine agents. Kantian justice demands that the prescriptive system of enforceable public laws be consistent, yet statutes or case holdings may often describe legal obligations that contradict; moreover, even fundamental constitutional rights may come into conflict. I argue that a deontic logic of the law should not try to work around such conflicts (...)
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  46.  8
    Logic Programming and Nonmonotonic Reasoning: 7th International Conference, LPNMR 2004, Fort Lauderdale, FL, USA, January 6-8, 2004, Proceedings.Vladimir Lifschitz & Ilkka Niemelä - 2004 - Springer Verlag.
    This book constitutes the refereed proceedings of the 7th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2004, held in Fort Lauderdale, Florida, USA in January 2004. The 24 revised full papers presented together with 8 system descriptions were carefully reviewed and selected for presentation. Among the topics addressed are declarative logic programming, nonmonotonic reasoning, knowledge representation, combinatorial search, answer set programming, constraint programming, deduction in ontologies, and planning.
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  47.  23
    生成と検査の論理プログラムの統合による極小限定・定理証明器の構築.富田 一夫 若木 利子 - 2007 - Transactions of the Japanese Society for Artificial Intelligence 22 (5):472-481.
    Recently we proposed a method of compiling prioritized circumscription into answer set programming. However, its encoding has the guess and check structure, where the candidates are generated by the guess program and the check is expressed by the inconsistency of the check program. In this paper, we present another method which compiles prioritized circumscription into a single general disjunctive program by means of integration of the guess and check programs. The answer sets of the transformed GDP yield (...)
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  48.  22
    Temporal Phylogenetic Networks and Logic Programming.Vladimir Lifschitz - unknown
    The concept of a temporal phylogenetic network is a mathematical model of evolution of a family of natural languages. It takes into account the fact that languages can trade their characteristics with each other when linguistic communities are in contact, and also that a contact is only possible when the languages are spoken at the same time. We show how computational methods of answer set programming and constraint logic programming can be used to generate plausible conjectures about (...)
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  49.  9
    Assumption-based argumentation for extended disjunctive logic programming and its relation to nonmonotonic reasoning.Toshiko Wakaki - forthcoming - Argument and Computation:1-45.
    The motivation of this study is that Reiter’s default theory as well as assumption-based argumentation frameworks corresponding to default theories have difficulties in handling disjunctive information, while a disjunctive default theory (ddt) avoids them. This paper presents the semantic correspondence between generalized assumption-based argumentation (ABA) and extended disjunctive logic programming as well as the correspondence between ABA and nonmonotonic reasoning approaches such as disjunctive default logic and prioritized circumscription. To overcome the above-mentioned difficulties of ABA frameworks corresponding to default (...)
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  50.  49
    Temporal Equilibrium Logic with past operators.Felicidad Aguado, Pedro Cabalar, Martín Diéguez, Gilberto Pérez & Concepción Vidal - 2017 - Journal of Applied Non-Classical Logics 27 (3-4):161-177.
    In this paper, we study the introduction of modal past temporal operators in Temporal Equilibrium Logic, an hybrid formalism that mixes linear-time modalities and logic programs interpreted under stable models and their characterisation in terms of Equilibrium Logic. We show that Kamp’s translation can also be used to translate the new extension of TEL with past operators into Quantified Equilibrium Logic. Additionally, we provide a method for removing past operators that consists in replacing past-time subformulas by fresh auxiliary atoms, obtaining (...)
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