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  1. A logic for default reasoning.Ray Reiter - 1980 - Artificial Intelligence 13 (1-2):81-137.
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  • (2 other versions)The socratic elenchus.Gregory Vlastos - 1982 - Journal of Philosophy 79 (11):711-714.
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  • Using arguments for making and explaining decisions.Leila Amgoud & Henri Prade - 2009 - Artificial Intelligence 173 (3-4):413-436.
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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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  • On Inferences from Inconsistent Premises.Nicholas Rescher & Ruth Manor - 1970 - Theory and Decision 1 (2):179-217, 1970-1971.
    The main object of this paper is to provide the logical machinery needed for a viable basis for talking of the ‘consequences’, the ‘content’, or of ‘equivalences’ between inconsistent sets of premisses.With reference to its maximal consistent subsets (m.c.s.), two kinds of ‘consequences’ of a propositional set S are defined. A proposition P is a weak consequence (W-consequence) of S if it is a logical consequence of at least one m.c.s. of S, and P is an inevitable consequence (I-consequence) of (...)
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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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  • On the evaluation of argumentation formalisms.Martin Caminada & Leila Amgoud - 2007 - Artificial Intelligence 171 (5-6):286-310.
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  • Sequent-based logical argumentation.Ofer Arieli & Christian Straßer - 2015 - Argument and Computation 6 (1):73-99.
    We introduce a general approach for representing and reasoning with argumentation-based systems. In our framework arguments are represented by Gentzen-style sequents, attacks between arguments are represented by sequent elimination rules, and deductions are made according to Dung-style skeptical or credulous semantics. This framework accommodates different languages and logics in which arguments may be represented, allows for a flexible and simple way of expressing and identifying arguments, supports a variety of attack relations, and is faithful to standard methods of drawing conclusions (...)
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  • Behavioral Experiments for Assessing the Abstract Argumentation Semantics of Reinstatement.Iyad Rahwan, Mohammed I. Madakkatel, Jean-François Bonnefon, Ruqiyabi N. Awan & Sherief Abdallah - 2010 - Cognitive Science 34 (8):1483-1502.
    Argumentation is a very fertile area of research in Artificial Intelligence, and various semantics have been developed to predict when an argument can be accepted, depending on the abstract structure of its defeaters and defenders. When these semantics make conflicting predictions, theoretical arbitration typically relies on ad hoc examples and normative intuition about what prediction ought to be the correct one. We advocate a complementary, descriptive-experimental method, based on the collection of behavioral data about the way human reasoners handle these (...)
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  • On Argumentation Logic and Propositional Logic.Antonis C. Kakas, Paolo Mancarella & Francesca Toni - 2018 - Studia Logica 106 (2):237-279.
    This paper studies the relationship between Argumentation Logic, a recently defined logic based on the study of argumentation in AI, and classical Propositional Logic. In particular, it shows that AL and PL are logically equivalent in that they have the same entailment relation from any given classically consistent theory. This equivalence follows from a correspondence between the non-acceptability of sentences in AL and Natural Deduction proofs of the complement of these sentences. The proof of this equivalence uses a restricted form (...)
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  • The problem of logical omniscience, I.Robert Stalnaker - 1991 - Synthese 89 (3):425 - 440.
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  • Computational Representation of Practical Argument.Katie Atkinson, Trevor Bench-Capon & Peter McBurney - 2006 - Synthese 152 (2):157-206.
    In this paper we consider persuasion in the context of practical reasoning, and discuss the problems associated with construing reasoning about actions in a manner similar to reasoning about beliefs. We propose a perspective on practical reasoning as presumptive justification of a course of action, along with critical questions of this justification, building on the account of Walton. From this perspective, we articulate an interaction protocol, which we call PARMA, for dialogues over proposed actions based on this theory. We outline (...)
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  • A general account of argumentation with preferences.Sanjay Modgil & Henry Prakken - 2013 - Artificial Intelligence 195 (C):361-397.
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  • Audiences in argumentation frameworks.Trevor J. M. Bench-Capon, Sylvie Doutre & Paul E. Dunne - 2007 - Artificial Intelligence 171 (1):42-71.
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  • Instantiating abstract argumentation with classical logic arguments: Postulates and properties.Nikos Gorogiannis & Anthony Hunter - 2011 - Artificial Intelligence 175 (9-10):1479-1497.
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  • Argument graphs and assumption-based argumentation.Robert Craven & Francesca Toni - 2016 - Artificial Intelligence 233 (C):1-59.
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  • A general framework for sound assumption-based argumentation dialogues.Xiuyi Fan & Francesca Toni - 2014 - Artificial Intelligence 216 (C):20-54.
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