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  1. Audiences in argumentation frameworks.Trevor J. M. Bench-Capon, Sylvie Doutre & Paul E. Dunne - 2007 - Artificial Intelligence 171 (1):42-71.
  • On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games: 25 years later.Pietro Baroni, Francesca Toni & Bart Verheij - 2020 - Argument and Computation 11 (1-2):1-14.
  • Argumentation Methods for Artificial Intelligence in Law.Douglas Walton - 2005 - Berlin and Heidelberg: Springer.
    Use of argumentation methods applied to legal reasoning is a relatively new field of study. The book provides a survey of the leading problems, and outlines how future research using argumentation-based methods show great promise of leading to useful solutions. The problems studied include not only these of argument evaluation and argument invention, but also analysis of specific kinds of evidence commonly used in law, like witness testimony, circumstantial evidence, forensic evidence and character evidence. New tools for analyzing these kinds (...)
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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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  • Argument based machine learning.Martin Možina, Jure Žabkar & Ivan Bratko - 2007 - Artificial Intelligence 171 (10-15):922-937.
  • Analogical Arguments: Inferential Structures and Defeasibility Conditions.Fabrizio Macagno, Douglas Walton & Christopher Tindale - 2017 - Argumentation 31 (2):221-243.
    The purpose of this paper is to analyze the structure and the defeasibility conditions of argument from analogy, addressing the issues of determining the nature of the comparison underlying the analogy and the types of inferences justifying the conclusion. In the dialectical tradition, different forms of similarity were distinguished and related to the possible inferences that can be drawn from them. The kinds of similarity can be divided into four categories, depending on whether they represent fundamental semantic features of the (...)
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  • From Berman and Hafner’s teleological context to Baude and Sachs’ interpretive defaults: an ontological challenge for the next decades of AI and Law.Ronald P. Loui - 2016 - Artificial Intelligence and Law 24 (4):371-385.
    This paper revisits the challenge of Berman and Hafner’s “missing link” paper on representing teleological structure in case-based legal reasoning. It is noted that this was mainly an ontological challenge to represent some of what made legal reasoning distinctive, which was given less attention than factual similarity in the dominant AI and Law paradigm, deriving from HYPO. The response to their paper is noted and briefly evaluated. A parallel is drawn to a new challenge to provide deep structure to the (...)
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