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  1. An assumption-based TMS.Johan de Kleer - 1986 - Artificial Intelligence 28 (2):127-162.
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  • A Formal Characterisation Of Institutionalised Power.Andrew Jones & Marek Sergot - 1996 - Logic Journal of the IGPL 4 (3):427-443.
    We extend the monotonic and regular modal logics to the multi-modal cue, and give semantical characterization w.r.t. a semantics of minimal frames. For this we introduce a calculus over neighbourhoods and we obtain simpler conditions than those from the literature.
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  • Representing and applying knowledge for argumentation in a social context.Chris Reed - 1997 - AI and Society 11 (1-2):138-154.
    The concept of argumentation in AI is based almost exclusively on the use of formal, abstract representations. Despite their appealing computational properties, these abstractions become increasingly divorced from their real world counterparts, and, crucially, lose the ability to express the rich gamut of natural argument forms required for creating effective text. In this paper, the demands that socially situated argumentation places on knowledge representation are explored, and the various problems with existing formalisations are discussed. Insights from argumentation theory and social (...)
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  • Symbolic Logic: A Razor-edge Tool for Drafting and Interpreting Legal Documents.Layman E. Allen & Gabriel Orechkoff - 1964 - Journal of Symbolic Logic 29 (1):43-44.
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  • (1 other version)Normative Systems.D. D. Todd - 1973 - Philosophy and Phenomenological Research 33 (3):437.
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  • Deontic logic in the representation of law: Towards a methodology. [REVIEW]Andrew J. I. Jones & Marek Sergot - 1992 - Artificial Intelligence and Law 1 (1):45-64.
    There seems to be no clear consensus in the existing literature about the role of deontic logic in legal knowledge representation — in large part, we argue, because of an apparent misunderstanding of what deontic logic is, and a misplaced preoccupation with the surface formulation of legislative texts. Our aim in this paper is to indicate, first, which aspects of legal reasoning are addressed by deontic logic, and then to sketch out the beginnings of a methodology for its use in (...)
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  • An Artificial Intelligence Approach to Legal Reasoning.Anne von der Lieth Gardner - 1980 - MIT Press.
    Law and legal reasoning are a natural target for artificial intelligence systems. Like medical diagnosis and other tasks for expert systems, legal analysis is a matter of interpreting data in terms of higher-level concepts. But in law the data are more like those for a system aimed at understanding natural language: they tell a story about human events that may lead to a lawsuit. Statements of the law, too, are written in natural language and legal arguments are often arguments about (...)
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  • Logical Tools for Modelling Legal Argument: A Study of Defeasible Reasoning in Law.Henry Prakken - 2000 - Studia Logica 64 (1):143-146.
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  • (1 other version)Rights and Parliamentarism.Stig Kanger & Helle Kanger - 1971 - Journal of Symbolic Logic 36 (1):183-183.
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  • A Formal Model of Legal Argumentation.Giovanni Sartor - 1994 - Ratio Juris 7 (2):177-211.
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  • A system of temporally relative modal and deontic predicate logic and its philosophical applications.J. Van Eck - 1982 - Logique Et Analyse 25:339.
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  • Logical Tools for Modelling Legal Argument: A Study of Defeasible Reasoning in Law.Henry Prakken - 1993 - Dordrecht, Netherland: Springer.
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  • Contrary-to-duty obligations.Henry Prakken & Marek Sergot - 1996 - Studia Logica 57 (1):91 - 115.
    We investigate under what conditions contrary-to-duty (CTD) structures lacking temporal and action elements can be given a coherent reading. We argue, contrary to some recent proposals, that CTD is not an instance of defeasible reasoning, and that methods of nonmonotonic logics are inadequate since they are unable to distinguish between defeasibility and violation of primary obligations. We propose a semantic framework based on the idea that primary and CTD obligations are obligations of different kinds: a CTD obligation pertains to, or (...)
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  • Technology report: Building legal practice systems with today's commercial authoring tools. [REVIEW]Marc Lauritsen - 1992 - Artificial Intelligence and Law 1 (1):87-102.
    Document assembly and other substantive legal practice applications are the most knowledge-intense forms of software now widely available in the legal technology marketplace. This article provides an illustrative look at two contemporary practice system engines-CAPS and Scrivener-and examines their relevance for AI-and-law researchers.
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  • A method for conceptualising legal domains. An example from the dutch unemployment benefits act.Pepijn Visser, Trevor Bench-Capon & Jaap van den Herik - 1997 - Artificial Intelligence and Law 5 (3):207-242.
    There has been much talk of the need to build intermediate models of the expertise required preparatory to constructing a knowledge-based system in the legal domain. Such models offer advantages for verification, validation, maintenance and reuse. As yet, however, few such models have been reported at a useful level of detail. In this paper we describe a method for conceptualising legal domains as well as its application to a substantial fragment of the Dutch Unemployment Benefits Act (DUBA).We first discuss the (...)
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  • Deontic Logic and Legal Knowledge Representation.Andrew J. I. Jones - 1990 - Ratio Juris 3 (2):237-244.
    . The current literature in the Artificial Intelligence and Law field reveals uncertainty concerning the potential role of deontic logic in legal knowledge representation. For instance, the Logic Programming Group at Imperial College has shown that a good deal can be achieved in this area in the absence of explicit representation of the deontic notions. This paper argues that some rather ordinary parts of the law contain structures which, if they are to be represented in logic, will call for use (...)
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  • Normative Systems.D. G. Londey - 1973 - Philosophical Quarterly 23 (92):280.
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  • (1 other version)Rights and Parliamentarism.Stig Kanger & Helle Kanger - 1966 - Theoria 32 (2):85-115.
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