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  1. How much of commonsense and legal reasoning is formalizable? A review of conceptual obstacles.James Franklin - 2012 - Law, Probability and Risk 11:225-245.
    Fifty years of effort in artificial intelligence (AI) and the formalization of legal reasoning have produced both successes and failures. Considerable success in organizing and displaying evidence and its interrelationships has been accompanied by failure to achieve the original ambition of AI as applied to law: fully automated legal decision-making. The obstacles to formalizing legal reasoning have proved to be the same ones that make the formalization of commonsense reasoning so difficult, and are most evident where legal reasoning has to (...)
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  • Reconstructing Popov v. Hayashi in a framework for argumentation with structured arguments and Dungean semantics.Henry Prakken - 2012 - Artificial Intelligence and Law 20 (1):57-82.
    In this article the argumentation structure of the court’s decision in the Popov v. Hayashi case is formalised in Prakken’s (Argument Comput 1:93–124; 2010) abstract framework for argument-based inference with structured arguments. In this framework, arguments are inference trees formed by applying two kinds of inference rules, strict and defeasible rules. Arguments can be attacked in three ways: attacking a premise, attacking a conclusion and attacking an inference. To resolve such conflicts, preferences may be used, which leads to three corresponding (...)
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  • A framework for the extraction and modeling of fact-finding reasoning from legal decisions: lessons from the Vaccine/Injury Project Corpus. [REVIEW]Vern R. Walker, Nathaniel Carie, Courtney C. DeWitt & Eric Lesh - 2011 - Artificial Intelligence and Law 19 (4):291-331.
    This article describes the Vaccine/Injury Project Corpus, a collection of legal decisions awarding or denying compensation for health injuries allegedly due to vaccinations, together with models of the logical structure of the reasoning of the factfinders in those cases. This unique corpus provides useful data for formal and informal logic theory, for natural-language research in linguistics, and for artificial intelligence research. More importantly, the article discusses lessons learned from developing protocols for manually extracting the logical structure and generating the logic (...)
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  • Formalising ordinary legal disputes: A case study. [REVIEW]Henry Prakken - 2008 - Artificial Intelligence and Law 16 (4):333-359.
    This paper presents a formal reconstruction of a Dutch civil legal case in Prakken’s formal model of adjudication dialogues. The object of formalisation is the argumentative speech acts exchanged during the dispute by the adversaries and the judge. The goal of this formalisation is twofold: to test whether AI & law models of legal dialogues in general, and Prakken’s model in particular, are suitable for modelling particular legal procedures; and to learn about the process of formalising an actual legal dispute.
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  • The Analysis and Evaluation of Legal Argumentation: Approaches from Legal Theory and Argumentation Theory.Eveline Feteris & Harm Klossterhuis - 2009 - Studies in Logic, Grammar and Rhetoric 16 (29).
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  • (1 other version)Argumentation Theory and the conception of epistemic justification.Lilian Bermejo-Luque - 2009 - In Marcin Koszowy (ed.), Informal logic and argumentation theory. Białystok: University of Białystok. pp. 285--303.
    I characterize the deductivist ideal of justification and, following to a great extent Toulmin’s work The Uses of Argument, I try to explain why this ideal is erroneous. Then I offer an alternative model of justification capable of making our claims to knowledge about substantial matters sound and reasonable. This model of justification will be based on a conception of justification as the result of good argumentation, and on a model of argumentation which is a pragmatic linguistic reconstruction of Toulmin’s (...)
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  • The cognitive legacy of norm simulation.Martin Neumann - 2012 - Artificial Intelligence and Law 20 (4):339-357.
    The comprehension of norms in complex social systems is one of the most active fields of research in agent-based modelling. This is faced with the challenge to comprehend the recursive interaction between inter- and intra-agent processes. In this article, a comparative analysis of selected cases of normative agent architectures will be given based on a review of theories of norms in the social sciences. This allows to identify the prerequisites for a representation of the cognitive processes of norm recognition. As (...)
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  • Value-based argumentation for justifying compliance.Brigitte Burgemeestre, Joris Hulstijn & Yao-Hua Tan - 2011 - Artificial Intelligence and Law 19 (2-3):149-186.
    Compliance is often achieved ‘by design’ through a coherent system of controls consisting of information systems and procedures. This system-based control requires a new approach to auditing in which companies must demonstrate to the regulator that they are ‘in control’. They must determine the relevance of a regulation for their business, justify which set of control measures they have taken to comply with it, and demonstrate that the control measures are operationally effective. In this paper we show how value-based argumentation (...)
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  • Research in progress: report on the ICAIL 2017 doctoral consortium.Maria Dymitruk, Réka Markovich, Rūta Liepiņa, Mirna El Ghosh, Robert van Doesburg, Guido Governatori & Bart Verheij - 2018 - Artificial Intelligence and Law 26 (1):49-97.
    This paper arose out of the 2017 international conference on AI and law doctoral consortium. There were five students who presented their Ph.D. work, and each of them has contributed a section to this paper. The paper offers a view of what topics are currently engaging students, and shows the diversity of their interests and influences.
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  • Working on the argument pipeline: Through flow issues between natural language argument, instantiated arguments, and argumentation frameworks.Adam Wyner, Tom van Engers & Anthony Hunter - 2016 - Argument and Computation 7 (1):69-89.
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