Results for 'defeasible logic programming'

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  1.  61
    Defeasible logic programming: DeLP-servers, contextual queries, and explanations for answers.Alejandro J. García & Guillermo R. Simari - 2014 - Argument and Computation 5 (1):63-88.
    Argumentation represents a way of reasoning over a knowledge base containing possibly incomplete and/or inconsistent information, to obtain useful conclusions. As a reasoning mechanism, the way an argumentation reasoning engine reaches these conclusions resembles the cognitive process that humans follow to analyze their beliefs; thus, unlike other computationally reasoning systems, argumentation offers an intellectually friendly alternative to other defeasible reasoning systems. LogicProgrammingisacomputationalparadigmthathasproducedcompu- tationallyattractivesystemswithremarkablesuccessinmanyapplications. Merging ideas from both areas, Defeasible Logic Programming offers a computational reasoning system that (...)
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  2.  23
    An informant-based approach to argument strength in Defeasible Logic Programming.Andrea Cohen, Sebastian Gottifredi, Luciano H. Tamargo, Alejandro J. García & Guillermo R. Simari - 2021 - Argument and Computation 12 (1):115-147.
    This work formalizes an informant-based structured argumentation approach in a multi-agent setting, where the knowledge base of an agent may include information provided by other agents, and each piece of knowledge comes attached with its informant. In that way, arguments are associated with the set of informants corresponding to the information they are built upon. Our approach proposes an informant-based notion of argument strength, where the strength of an argument is determined by the credibility of its informant agents. Moreover, we (...)
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  3.  8
    An informant-based approach to argument strength in Defeasible Logic Programming.Gabriella Pigozzi & Srdjan Vesic - 2021 - Argument and Computation 12 (1):115-147.
    This work formalizes an informant-based structured argumentation approach in a multi-agent setting, where the knowledge base of an agent may include information provided by other agents, and each piece of knowledge comes attached with its informant. In that way, arguments are associated with the set of informants corresponding to the information they are built upon. Our approach proposes an informant-based notion of argument strength, where the strength of an argument is determined by the credibility of its informant agents. Moreover, we (...)
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  4.  98
    Argument-based extended logic programming with defeasible priorities.Henry Prakken & Giovanni Sartor - 1997 - Journal of Applied Non-Classical Logics 7 (1-2):25-75.
    ABSTRACT Inspired by legal reasoning, this paper presents a semantics and proof theory of a system for defeasible argumentation. Arguments are expressed in a logic-programming language with both weak and strong negation, conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is that these priorities are not fixed, but are themselves defeasibly derived as conclusions within the system. Thus debates on the choice between conflicting arguments can also (...)
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  5.  47
    Defeasible reasoning and logic programming.Timothy R. Colburn - 1991 - Minds and Machines 1 (4):417-436.
    The general conditions of epistemic defeat are naturally represented through the interplay of two distinct kinds of entailment, deductive and defeasible. Many of the current approaches to modeling defeasible reasoning seek to define defeasible entailment via model-theoretic notions like truth and satisfiability, which, I argue, fails to capture this fundamental distinction between truthpreserving and justification-preserving entailments. I present an alternative account of defeasible entailment and show how logic programming offers a paradigm in which the (...)
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  6.  31
    On the relation between vector annotated logic programs and defeasible theories.Kazumi Nakamatsu - 2000 - Logic and Logical Philosophy 8:181.
    In this paper, we propose an annotated logic program called aVALPSN to dealwith defeasible reasoning. We propose a translation from Billington’s defeasible theory into VALPSN and clarify the relation between them based onthe translation.
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  7.  66
    Well-founded semantics for defeasible logic.Frederick Maier & Donald Nute - 2010 - Synthese 176 (2):243 - 274.
    Fixpoint semantics are provided for ambiguity blocking and propagating variants of Nute's defeasible logic. The semantics are based upon the well-founded semantics for logic programs. It is shown that the logics are sound with respect to their counterpart semantics and complete for locally finite theories. Unlike some other nonmonotonic reasoning formalisms such as Reiter's default logic, the two defeasible logics are directly skeptical and so reject floating conclusions. For defeasible theories with transitive priorities on (...)
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  8.  13
    Compiling defeasible inheritance networks to general logic programs.Jia-Huai You, Xianchang Wang & Li Yan Yuan - 1999 - Artificial Intelligence 113 (1-2):247-268.
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  9. Equivalence of defeasible normative systems.José Júlio Alferes, Ricardo Gonçalves & João Leite - 2013 - Journal of Applied Non-Classical Logics 23 (1-2):25-48.
    Normative systems have been advocated as an effective tool to regulate interaction in multi-agent systems. The use of deontic operators and the ability to represent defeasible information are known to be two fundamental ingredients to represent and reason about normative systems. In this paper, after introducing a framework that combines standard deontic logic and non-monotonic logic programming, deontic logic programs (DLP), we tackle the fundamental problem of equivalence between normative systems using a deontic extension of (...)
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  10.  4
    Handbook of Defeasible Reasoning and Uncertainty Management Systems, Volume 2: Reasoning with Actual and Potential Contradictions.Philippe Besnard & Anthony Hunter (eds.) - 1998 - Dordrecht, Netherland: Kluwer Academic Publishers.
    This volume deals with approaches to handling contradictory information. These include approaches for actual contradiction - both A and not-A can be proven from the information - and approaches for potential contradiction - where the information may contain arguments for A and arguments for not-A, but the system suppresses the contradiction by, for example, preferring some arguments over others. Approaches covered include paraconsistent logics, modal logics, default logics, conditional logics, defeasible logics and paraconsistent semantics for logic programming. (...)
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  11.  55
    The epistemic basis of defeasible reasoning.Robert L. Causey - 1991 - Minds and Machines 1 (4):437-458.
    This article argues that: (i) Defeasible reasoning is the use of distinctive procedures for belief revision when new evidence or new authoritative judgment is interpolated into a system of beliefs about an application domain. (ii) These procedures can be explicated and implemented using standard higher-order logic combined with epistemic assumptions about the system of beliefs. The procedures mentioned in (i) depend on the explication in (ii), which is largely described in terms of a Prolog program, EVID, which implements (...)
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  12.  76
    Review: Dov M. Gabbay, C. J. Hogger, J. A. Robinson, D. Nute, Handbook of Logic in Artificial Intelligence and Logic Programming, Volume 3, Nonmonotonic Reasoning and Uncertain Reasoning. [REVIEW]G. Aldo Antonelli - 2000 - Bulletin of Symbolic Logic 6 (4):480-484.
    The emergence, over the last twenty years or so, of so-called “non-monotonic” logics represents one of the most significant developments both in logic and artificial intelligence. These logics were devised in order to represent defeasible reasoning, i.e., that kind of inference in which reasoners draw conclusions tentatively, reserving the right to retract them in the light of further evidence.
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  13.  57
    Computational Dialogic Defeasible Reasoning.Robert L. Causey - 2003 - Argumentation 17 (4):421-450.
    This article begins with an introduction to defeasible (nonmonotonic) reasoning and a brief description of a computer program, EVID, which can perform such reasoning. I then explain, and illustrate with examples, how this program can be applied in computational representations of ordinary dialogic argumentation. The program represents the beliefs and doubts of the dialoguers, and uses these propositional attitudes, which can include commonsense defeasible inference rules, to infer various changing conclusions as a dialogue progresses. It is proposed that (...)
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  14. A dialectical model of assessing conflicting arguments in legal reasoning.H. Prakken & G. Sartor - 1996 - Artificial Intelligence and Law 4 (3-4):331-368.
    Inspired by legal reasoning, this paper presents a formal framework for assessing conflicting arguments. Its use is illustrated with applications to realistic legal examples, and the potential for implementation is discussed. The framework has the form of a logical system for defeasible argumentation. Its language, which is of a logic-programming-like nature, has both weak and explicit negation, and conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is (...)
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  15.  34
    Incremental computation for structured argumentation over dynamic DeLP knowledge bases.Gianvincenzo Alfano, Sergio Greco, Francesco Parisi, Gerardo I. Simari & Guillermo R. Simari - 2021 - Artificial Intelligence 300 (C):103553.
    Structured argumentation systems, and their implementation, represent an important research subject in the area of Knowledge Representation and Reasoning. Structured argumentation advances over abstract argumentation frameworks by providing the internal construction of the arguments that are usually defined by a set of (strict and defeasible) rules. By considering the structure of arguments, it becomes possible to analyze reasons for and against a conclusion, and the warrant status of such a claim in the context of a knowledge base represents the (...)
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  16.  37
    Evidential bilattice logic and lexical inference.Andreas Schöter - 1996 - Journal of Logic, Language and Information 5 (1):65-105.
    This paper presents an information-based logic that is applied to the analysis of entailment, implicature and presupposition in natural language. The logic is very fine-grained and is able to make distinctions that are outside the scope of classical logic. It is independently motivated by certain properties of natural human reasoning, namely partiality, paraconsistency, relevance, and defeasibility: once these are accounted for, the data on implicature and presupposition comes quite naturally.The logic is based on the family of (...)
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  17. Acquiring knowledge from expert agents in a structured argumentation setting.Ramiro Andres Agis, Sebastian Gottifredi & Alejandro Javier García - 2019 - Argument and Computation 10 (2):149-189.
    Information-seeking interactions in multi-agent systems are required for situations in which there exists an expert agent that has vast knowledge about some topic, and there are other agents (questioners or clients) that lack and need information regarding that topic. In this work, we propose a strategy for automatic knowledge acquisition in an information-seeking setting in which agents use a structured argumentation formalism for knowledge representation and reasoning. In our approach, the client conceives the other agent as an expert in a (...)
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  18.  11
    Logic Programming: Proceedings of the Joint International Conference and Symposium on Logic Programming.Krzysztof R. Apt & Association for Logic Programming - 1992 - MIT Press (MA).
    The Joint International Conference on Logic Programming, sponsored by the Association for Logic Programming, is a major forum for presentations of research, applications, and implementations in this important area of computer science. Logic programming is one of the most promising steps toward declarative programming and forms the theoretical basis of the programming language Prolog and its various extensions. Logic programming is also fundamental to work in artificial intelligence, where it has (...)
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  19.  2
    Representing argumentation schemes with Constraint Handling Rules (CHR).Floriana Grasso & Nancy L. Green - 2018 - Argument and Computation 9 (2):91-119.
    We present a high-level declarative programming language for representing argumentation schemes, where schemes represented in this language can be easily validated by domain experts, including developers of argumentation schemes in informal logic and philosophy, and serve as executable specifications for automatically constructing arguments, when applied to a set of assumptions. Since argumentation schemes are defeasible inference rules, both premises and conclusions of schemes can be second-order schema variables, i.e. without a fixed predicate symbol. Thus, while particular schemes (...)
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  20.  8
    Logic Programming: 10th International Symposium : Preprinted Papers and Abstracts.Dale Miller & Association for Logic Programming - 1993
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  21.  5
    Logic Programming and Non-monotonic Reasoning: Proceedings of the First International Workshop.Wiktor Marek, Anil Nerode, V. S. Subrahmanian & Association for Logic Programming - 1991 - MIT Press (MA).
    The First International Workshop brings together researchers from the theoretical ends of the logic programming and artificial intelligence communities to discuss their mutual interests. Logic programming deals with the use of models of mathematical logic as a way of programming computers, where theoretical AI deals with abstract issues in modeling and representing human knowledge and beliefs. One common ground is nonmonotonic reasoning, a family of logics that includes room for the kinds of variations that (...)
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  22. Computing Generalized Specificity.Frieder Stolzenberg, Alejandro Javier Garcia, Carlos Ivan Chesñevar & Guillermo Ricardo Simari - 2003 - Journal of Applied Non-Classical Logics 13 (1):87-113.
    Most formalisms for representing common-sense knowledge allow incomplete and potentially inconsistent information. When strong negation is also allowed, contradictory conclusions can arise. A criterion for deciding between them is needed. The aim of this paper is to investigate an inherent and autonomous comparison criterion, based on specificity as defined in [POO 85, SIM 92]. In contrast to other approaches, we consider not only defeasible, but also strict knowledge. Our criterion is context-sensitive, i. e., preference among defeasible rules is (...)
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  23. An abstract framework for argumentation with structured arguments.Henry Prakken - 2010 - Argument and Computation 1 (2):93-124.
    An abstract framework for structured arguments is presented, which instantiates Dung's ('On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming, and n- Person Games', Artificial Intelligence , 77, 321-357) abstract argumentation frameworks. Arguments are defined as inference trees formed by applying two kinds of inference rules: strict and defeasible rules. This naturally leads to three ways of attacking an argument: attacking a premise, attacking a conclusion and attacking an inference. To resolve such (...)
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  24.  94
    Conditionals: from philosophy to computer science.G. Crocco, Luis Fariñas del Cerro & Andreas Herzig (eds.) - 1995 - New York: Oxford University Press.
    This book looks at the ways in which conditionals, an integral part of philosophy and logic, can be of practical use in computer programming. It analyzes the different types of conditionals, including their applications and potential problems. Other topics include defeasible logics, the Ramsey test, and a unified view of consequence relation and belief revision. Its implications will be of interest to researchers in logic, philosophy, and computer science, particularly artificial intelligence.
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  25.  75
    Abstract argumentation.Robert A. Kowalski & Francesca Toni - 1996 - Artificial Intelligence and Law 4 (3-4):275-296.
    In this paper we explore the thesis that the role of argumentation in practical reasoning in general and legal reasoning in particular is to justify the use of defeasible rules to derive a conclusion in preference to the use of other defeasible rules to derive a conflicting conclusion. The defeasibility of rules is expressed by means of non-provability claims as additional conditions of the rules.We outline an abstract approach to defeasible reasoning and argumentation which includes many existing (...)
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  26.  31
    A Language For Handling Hypothetical Updates And Inconsistency.Dov Gabbay, Laura Giordano, Alberto Martelli & Nicola Olivetti - 1996 - Logic Journal of the IGPL 4 (3):385-416.
    In this paper we propoee a logic programming language which supports hypothetical updates together with integrity constraints. The language makes use of a revision mechanism, which is needed to restore consistency when an update violates some integrity constraint. The revision policy adopted is based on the simple idea that more recent information is preferred to earlier one. We show how this language can be used to represent and perform several types of defeasible reasoning. We develop a logical (...)
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  27.  50
    A Defeasible Logic For Modelling Policy-based Intentions And Motivational Attitudes.Guido Governatori, Vineet Padmanabhan, Antonio Rotolo & Abdul Sattar - 2009 - Logic Journal of the IGPL 17 (3):227-265.
    In this paper we show how defeasible logic could formally account for the non-monotonic properties involved in motivational attitudes like intention and obligation. Usually, normal modal operators are used to represent such attitudes wherein classical logical consequence and the rule of necessitation comes into play, i.e., ⊢A/⊢ □A, that is from ⊢A derive ⊢ □A. This means that such formalisms are affected by the Logical Omniscience problem. We show that policy-based intentions exhibit non-monotonic behaviour which could be captured (...)
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  28.  7
    Inductive Logic Programming: 10th International Conference, ILP 2000, London, UK, July 24-27, 2000 Proceedings.James Cussens & Alan Frisch - 2000 - Springer.
    This book constitutes the refereed proceedings of the 10th International Conference on Inductive Logic Programming, ILP 2000, held in London, UK in July 2000 as past of CL 2000. The 15 revised full papers presented together with an invited paper were carefully reviewed and selected from 37 submissions. The papers address all current issues in inductive logic programming and inductive learning, from foundational aspects to applications in various fields like data mining, knowledge discovery, and ILP system (...)
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  29.  20
    Which are the true defeasible logics?Michael J. Maher - forthcoming - Journal of Applied Non-Classical Logics:1-29.
    The class of defeasible logics is only vaguely defined – it is defined by a few exemplars and the general idea of efficient reasoning with defeasible rules. The recent definition of the defeasible logic DL(∂||) introduced new features to such logics, which have repercussions that we explore. In particular, we define a class of logics that accommodates the new logic while retaining the traditional properties of defeasible logics.
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  30.  63
    Grounded Consequence for Defeasible Logic.Aldo Antonelli - 2005 - New York: Cambridge University Press.
    This is a title on the foundations of defeasible logic, which explores the formal properties of everyday reasoning patterns whereby people jump to conclusions, reserving the right to retract them in the light of further information. Although technical in nature the book contains sections that outline basic issues by means of intuitive and simple examples. This book is primarily targeted at philosophers interested in the foundations of defeasible logic, logicians, and specialists in artificial intelligence and theoretical (...)
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  31.  36
    A Defeasible Logic of Policy-Based Intention.Guido Governatori & Vineet Nair - unknown
    Most of the theories on formalising intention interpret it as a unary modal operator in Kripkean semantics, which gives it a monotonic look. We argue that policy-based intentions exhibit non-monotonic behaviour which could be captured through a non-monotonic system like defeasible logic. To this end we outline a defeasible logic of intention. The proposed technique alleviates most of the problems related to logical omniscience. The proof theory given shows how our approach helps in the maintenance of (...)
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  32.  9
    A Logic Programming Language with Lambda-abstraction, Function Variables, and Simple Unification.Dale Miller - 1991 - LFCS, Department of Computer Science, University of Edinburgh.
    As a result of these restrictions, an implementation of L [subscript lambda] does not need to implement full higher-order unification. Instead, an extension to first-order unification that respects bound variable names and scopes is all that is required. Such unification problems are shown to be decidable and to possess most general unifiers when unifiers exist. A unification algorithm and logic programming interpreter are described and proved correct. Several examples of using L[subscript lambda] as a meta-programming language are (...)
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  33.  76
    Reasoning about knowledge using defeasible logic.Douglas Walton - 2011 - Argument and Computation 2 (2-3):131 - 155.
    In this paper, the Carneades argumentation system is extended to represent a procedural view of inquiry in which evidence is marshalled to support or defeat claims to knowledge. The model is a sequence of moves in a collaborative group inquiry in which parties take turns making assertions about what is known or not known, putting forward evidence to support them, and subjecting these moves to criticisms. It is shown how this model of evaluating evidence in an inquiry is based on (...)
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  34.  15
    Meta-programming in Logic Programming.Harvey Abramson & M. H. Rogers - 1989
    Meta-programs, which treat other computer programs as data, include compilers, editors, simulators, debuggers, and program transformers. Because of the wide ranging applications, meta-programming has become a subject of considerable practical and theoretical interest. This book provides the first comprehensive view of topics in the theory and application of meta-programming, covering problems of representation and of soundness and correctness of interpreters, analysis and evaluation of meta-logic programs, and applications to sophisticated knowledge-based systems.Harvey Abramson is Reader in Computer Science (...)
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  35.  14
    From Logic Programming to Prolog.Krzysztof R. Apt - 1997
    Provides a systematic introduction to the theory of logic programming and shows how this theory can be applied to reason about pure Prolog programs. The text includes an introduction to programming in Prolog and deals with such programming issues as determination, occur-check freedom and absence of errors. It covers both the natural interpretations of logic programming, as declarative specification and as procedure for computer execution.
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  36.  8
    Logic Programming: Proceedings.John Lloyd - 1995 - MIT Press.
    The International Logic Programming Symposium is one of two major international conferences sponsored by the Association of Logic Programming. Both conferences are held annually. The theme for the 1995 conference was "Declarative Systems", particularly the integration of the logic programming, functional programming, and object-oriented programming paradigms.
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  37. Conciliatory views, higher-order disagreements, and defeasible logic.Aleks Knoks - 2022 - Synthese 200 (2).
    Conciliatory views of disagreement say, roughly, that it’s rational for you to become less confident in your take on an issue in case you find out that an epistemic peer’s take on it is the opposite. Their intuitive appeal notwithstanding, there are well-known worries about the behavior of conciliatory views in scenarios involving higher-order disagreements, which include disagreements over these views themselves and disagreements over the peer status of alleged epistemic peers. This paper does two things. First, it explains how (...)
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  38. (1 other version)Misleading higher-order evidence, conflicting ideals, and defeasible logic.Aleks Https://Orcidorg Knoks - 2020 - Ergo: An Open Access Journal of Philosophy 8:141--74.
    Thinking about misleading higher-order evidence naturally leads to a puzzle about epistemic rationality: If one’s total evidence can be radically misleading regarding itself, then two widely-accepted requirements of rationality come into conflict, suggesting that there are rational dilemmas. This paper focuses on an often misunderstood and underexplored response to this (and similar) puzzles, the so-called conflicting-ideals view. Drawing on work from defeasible logic, I propose understanding this view as a move away from the default metaepistemological position according to (...)
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  39.  15
    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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  40.  84
    Comparing logic programming and formal argumentation; the case of ideal and eager semantics.Martin Caminada, Sri Harikrishnan & Samy Sá - 2022 - Argument and Computation 13 (1):93-120.
    The connection between logic programming and formal argumentation has been studied starting from the landmark 1995 paper of Dung. Subsequent work has identified a standard translation from logic programs to argumentation frameworks, under which pairwise correspondences hold between various logic programming semantics and various formal argumentation semantics. This includes the correspondence between 3-valued stable and complete semantics, between well-founded and grounded semantics and between 2-valued stable and stable semantics. In the current paper, we show that (...)
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  41.  2
    Logic Programming Via Proof-valued Computations.David J. Pym & Lincoln A. Wallen - 1992 - LFCS, Department of Computer Science, University of Edinburgh.
    "We argue that the computation of a logic program can be usefully divided into two distinct phases: the first being a proof- valued computation or proof-search; the second a residual computation, or answer extraction. Extension of extraction techniques to various theories then permits more extensive languages and proof procedures to be employed for the computational solution of problems. We illustrate these ideas with a simple propositional logic and show that SLD-resolution computes presentations of proofs in which the residual (...)
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  42.  11
    Logic Programming Languages: Constraints, Functions, and Objects.Krzysztof R. Apt & J. J. M. M. Rutten - 1993 - MIT Press.
    This collection of current research on logic programming languages presents results from a three-year, ESPRIT-funded effort to explore the integration of the foundational issues of functional, logic, and object-oriented programming. It offers valuable insights into the fast-developing extensions of logic programming with functions, constraints, concurrency, and objects. Chapters are grouped according to the unifying themes of functional programming, constraint, logic programming, and object-oriented programming.
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  43.  21
    Defeasible logic and the frame problem.Donald Nute - 1990 - In Kyburg Henry E. , Loui Ronald P. & Carlson Greg N. , Knowledge Representation and Defeasible Reasoning. Kluwer Academic Publishers. pp. 3--21.
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  44.  11
    Logic Programming: Proceedings of the 1996 Joint International Conference and Symposium on Logic Programming.Michael Maher - 1996 - MIT Press.
    Includes tutorials, invited lectures, and refereed papers on all aspects of logic programming including: Constraints, Concurrency and Parallelism, Deductive Databases, Implementations, Meta and Higher-order Programming, Theory, and Semantic Analysis. September 2-6, 1996, Bonn, Germany Every four years, the two major international scientific conferences on logic programming merge in one joint event. JICSLP'96 is the thirteenth in the two series of annual conferences sponsored by The Association for Logic Programming. It includes tutorials, invited lectures, (...)
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  45.  14
    Logic Programming: Proceedings of the Fifth International Conference and Symposium.Robert Kowalski & Kenneth A. Bowen - 1988 - MIT Press (MA).
    These two volumes collect papers presented at the first joint meeting of the two principal logic programming conferences, held in August of 1988. The more than fifty contributions cover all aspects of the field, including applications (particularly those that exploit the unique character of logic programming), the role of logic programming in artificial intelligence, deductive databases, relations to other computational paradigms, language issues, methodology, implementations on sequential and parallel architectures, and theory.Logic Programming (...)
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  46.  68
    Modal logic programming revisited.Linh Anh Nguyen - 2009 - Journal of Applied Non-Classical Logics 19 (2):167-181.
    We present optimizations for the modal logic programming system MProlog, including the standard form for resolution cycles, optimized sets of rules used as meta-clauses, optimizations for the version of MProlog without existential modal operators, as well as iterative deepening search and tabulation. Our SLD-resolution calculi for MProlog in a number of modal logics are still strongly complete when resolution cycles are in the standard form and optimized sets of rules are used. We also show that the labelling technique (...)
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  47.  74
    Computing Strong and Weak Permissions in Defeasible Logic.Guido Governatori, Francesco Olivieri, Antonino Rotolo & Simone Scannapieco - 2013 - Journal of Philosophical Logic 42 (6):799-829.
    In this paper we propose an extension of Defeasible Logic to represent and compute different concepts of defeasible permission. In particular, we discuss some types of explicit permissive norms that work as exceptions to opposite obligations or encode permissive rights. Moreover, we show how strong permissions can be represented both with, and without introducing a new consequence relation for inferring conclusions from explicit permissive norms. Finally, we illustrate how a preference operator applicable to contrary-to-duty obligations can be (...)
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  48.  68
    Program verification, defeasible reasoning, and two views of computer science.Timothy R. Colburn - 1991 - Minds and Machines 1 (1):97-116.
    In this paper I attempt to cast the current program verification debate within a more general perspective on the methodologies and goals of computer science. I show, first, how any method involved in demonstrating the correctness of a physically executing computer program, whether by testing or formal verification, involves reasoning that is defeasible in nature. Then, through a delineation of the senses in which programs can be run as tests, I show that the activities of testing and formal verification (...)
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  49.  24
    Logic Programming and Interactive Applications.Alexander Šimko & Jozef Šiška - 2013 - Organon F: Medzinárodný Časopis Pre Analytickú Filozofiu 20 (2):187-205.
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  50. The Logic Programming Paradigm: A 25-Year Perspective.Krzysztof R. Apt, Victor W. Marek, Mirek Truszczynski & David S. Warren - 2002 - Studia Logica 71 (1):145-148.
     
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