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  1. The Uses of Argument.Stephen E. Toulmin - 1958 - Philosophy 34 (130):244-245.
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  • Generating and evaluating evaluative arguments.Giuseppe Carenini & Johanna D. Moore - 2006 - Artificial Intelligence 170 (11):925-952.
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  • The New Rhetoric: A Treatise on Argumentation.Ch Perelman, L. Olbrechts-Tyteca, John Wilkinson & Purcell Weaver - 1969 - Philosophy and Rhetoric 3 (4):249-254.
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  • Representation of Argumentation in Text with Rhetorical Structure Theory.Nancy L. Green - 2010 - Argumentation 24 (2):181-196.
    Various argumentation analysis tools permit the analyst to represent functional components of an argument (e.g., data, claim, warrant, backing), how arguments are composed of subarguments and defenses against potential counterarguments, and argumentation schemes. In order to facilitate a study of argument presentation in a biomedical corpus, we have developed a hybrid scheme that enables an analyst to encode argumentation analysis within the framework of Rhetorical Structure Theory (RST), which can be used to represent the discourse structure of a text. This (...)
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  • A method for the computational modelling of dialectical argument with dialogue games.T. J. M. Bench-Capon, T. Geldard & P. H. Leng - 2000 - Artificial Intelligence and Law 8 (2-3):233-254.
    In this paper we describe a method for the specification of computationalmodels of argument using dialogue games. The method, which consists ofsupplying a set of semantic definitions for the performatives making upthe game, together with a state transition diagram, is described in full.Its use is illustrated by some examples of varying complexity, includingtwo complete specifications of particular dialogue games, Mackenzie's DC,and the authors' own TDG. The latter is also illustrated by a fully workedexample illustrating all the features of the game.
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  • Lessons from a failure: Generating tailored smoking cessation letters.Ehud Reiter, Roma Robertson & Liesl M. Osman - 2003 - Artificial Intelligence 144 (1-2):41-58.
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  • The Carneades model of argument and burden of proof.Thomas F. Gordon, Henry Prakken & Douglas Walton - 2007 - Artificial Intelligence 171 (10-15):875-896.
    We present a formal, mathematical model of argument structure and evaluation, taking seriously the procedural and dialogical aspects of argumentation. The model applies proof standards to determine the acceptability of statements on an issue-by-issue basis. The model uses different types of premises (ordinary premises, assumptions and exceptions) and information about the dialectical status of statements (stated, questioned, accepted or rejected) to allow the burden of proof to be allocated to the proponent or the respondent, as appropriate, for each premise separately. (...)
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  • Fundamental concepts of qualitative probabilistic networks.Michael P. Wellman - 1990 - Artificial Intelligence 44 (3):257-303.
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