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  1. A mathematical treatment of defeasible reasoning and its implementation.Guillermo R. Simari & Ronald P. Loui - 1992 - Artificial Intelligence 53 (2-3):125-157.
    We present a mathematical approach to defeasible reasoning based on arguments. This approach integrates the notion of specificity introduced by Poole and the theory of warrant presented by Pollock. The main contribution of this paper is a precise, well-defined system which exhibits correct behavior when applied to the benchmark examples in the literature. It aims for usability rather than novelty. We prove that an order relation can be introduced among equivalence classes of arguments under the equi-specificity relation. We also prove (...)
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  • On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games.Phan Minh Dung - 1995 - Artificial Intelligence 77 (2):321-357.
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  • 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 be modelled. The (...)
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  • Defeasible Reasoning.John L. Pollock - 1987 - Cognitive Science 11 (4):481-518.
    There was a long tradition in philosophy according to which good reasoning had to be deductively valid. However, that tradition began to be questioned in the 1960’s, and is now thoroughly discredited. What caused its downfall was the recognition that many familiar kinds of reasoning are not deductively valid, but clearly confer justification on their conclusions. Here are some simple examples.
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  • Argument construction and reinstatement in logics for defeasible reasoning.John F. Horty - 2001 - Artificial Intelligence and Law 9 (1):1-28.
    This paper points out some problems with two recent logical systems – one due to Prakken and Sartor, the other due to Kowalski and Toni – designedfor the representation of defeasible arguments in general, but with a specialemphasis on legal reasoning.
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  • A model of argumentation and its application to legal reasoning.Kathleen Freeman & Arthur M. Farley - 1996 - Artificial Intelligence and Law 4 (3-4):163-197.
    We present a computational model of dialectical argumentation that could serve as a basis for legal reasoning. The legal domain is an instance of a domain in which knowledge is incomplete, uncertain, and inconsistent. Argumentation is well suited for reasoning in such weak theory domains. We model argument both as information structure, i.e., argument units connecting claims with supporting data, and as dialectical process, i.e., an alternating series of moves by opposing sides. Our model includes burden of proof as a (...)
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  • (1 other version)Towards a formal account of reasoning about evidence: Argumentation schemes and generalisations. [REVIEW]Floris Bex, Henry Prakken, Chris Reed & Douglas Walton - 2003 - Artificial Intelligence and Law 11 (2-3):125-165.
    This paper studies the modelling of legal reasoning about evidence within general theories of defeasible reasoning and argumentation. In particular, Wigmore's method for charting evidence and its use by modern legal evidence scholars is studied in order to give a formal underpinning in terms of logics for defeasible argumentation. Two notions turn out to be crucial, viz. argumentation schemes and empirical generalisations.
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  • An integrated view on rules and principles.Bart Verheij, Jaap C. Hage & H. Jaap Van Den Herik - 1998 - Artificial Intelligence and Law 6 (1):3-26.
    In the law, it is generally acknowledged that there are intuitive differences between reasoning with rules and reasoning with principles. For instance, a rule seems to lead directly to its conclusion if its condition is satisfied, while a principle seems to lead merely to a reason for its conclusion. However, the implications of these intuitive differences for the logical status of rules and principles remain controversial.A radical opinion has been put forward by Dworkin (1978). The intuitive differences led him to (...)
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  • Dialectical argumentation with argumentation schemes: An approach to legal logic. [REVIEW]Bart Verheij - 2003 - Artificial Intelligence and Law 11 (2-3):167-195.
    This paper describes an approach to legal logic based on the formal analysis of argumentation schemes. Argumentation schemes a notion borrowed from the .eld of argumentation theory - are a kind of generalized rules of inference, in the sense that they express that given certain premises a particular conclusion can be drawn. However, argumentation schemes need not concern strict, abstract, necessarily valid patterns of reasoning, but can be defeasible, concrete and contingently valid, i.e., valid in certain contexts or under certain (...)
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  • The pleadings game.Thomas F. Gordon - 1993 - Artificial Intelligence and Law 2 (4):239-292.
    The Pleadings Game is a normative formalization and computational model of civil pleading, founded in Roberty Alexy''s discourse theory of legal argumentation. The consequences of arguments and counterarguments are modelled using Geffner and Pearl''s nonmonotonic logic,conditional entailment. Discourse in focussed using the concepts of issue and relevance. Conflicts between arguments can be resolved by arguing about the validity and priority of rules, at any level. The computational model is fully implemented and has been tested using examples from Article Nine of (...)
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  • A truth maintenance system.Jon Doyle - 1979 - Artificial Intelligence 12 (3):231-272.
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  • Floating conclusions and zombie paths: Two deep difficulties in the “directly skeptical” approach to defeasible inheritance nets.David Makinson & Karl Schlechta - 1991 - Artificial Intelligence 48 (2):199-209.
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  • An abstract, argumentation-theoretic approach to default reasoning.A. Bondarenko, P. M. Dung, R. A. Kowalski & F. Toni - 1997 - Artificial Intelligence 93 (1-2):63-101.
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  • An assumption-based TMS.Johan de Kleer - 1986 - Artificial Intelligence 28 (2):127-162.
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  • SCC-recursiveness: a general schema for argumentation semantics.Pietro Baroni, Massimiliano Giacomin & Giovanni Guida - 2005 - Artificial Intelligence 168 (1-2):162-210.
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  • Argument Structure: A Pragmatic Theory.Douglas N. Walton - 1996 - Toronto and Buffalo: University of Toronto Press.
    William Baird collection in Social Sciences is the gift of the Estate of William Cameron Baird.
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  • (1 other version)Towards a Formal Account of Reasoning about Evidence: Argumentation Schemes and Generalisations.Bex Floris, Prakken Henry, Reed Chris & Walton Douglas - 2003 - Artificial Intelligence and Law 11 (2-3):125-165.
    This paper studies the modelling of legal reasoning about evidence within general theories of defeasible reasoning and argumentation. In particular, Wigmore's method for charting evidence and its use by modern legal evidence scholars is studied in order to give a formal underpinning in terms of logics for defeasible argumentation. Two notions turn out to be crucial, viz. argumentation schemes and empirical generalisations.
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  • Conditional entailment: Bridging two approaches to default reasoning.Hector Geffner & Judea Pearl - 1992 - Artificial Intelligence 53 (2-3):209-244.
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  • Modelling Defeasibility in Law: Logic or Procedure?Henry Prakken - 2001 - Fundamenta Informaticae 48 (2-3):253-271.
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