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  1. On the merging of Dung's argumentation systems.Sylvie Coste-Marquis, Caroline Devred, Sébastien Konieczny, Marie-Christine Lagasquie-Schiex & Pierre Marquis - 2007 - Artificial Intelligence 171 (10-15):730-753.
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  • Computing ideal sceptical argumentation.P. M. Dung, P. Mancarella & F. Toni - 2007 - Artificial Intelligence 171 (10-15):642-674.
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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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  • Artificial argument assistants for defeasible argumentation.Bart Verheij - 2003 - Artificial Intelligence 150 (1-2):291-324.
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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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  • Generation and evaluation of user tailored responses in multimodal dialogue.Marilyn Walker, S. Whittaker, A. Stent, P. Maloor, J. Moore, M. Johnston & G. Vasireddy - 2004 - Cognitive Science 28 (5):811-840.
    When people engage in conversation, they tailor their utterances to their conversational partners, whether these partners are other humans or computational systems. This tailoring, or adaptation to the partner takes place in all facets of human language use, and is based on a mental model or a user model of the conversational partner. Such adaptation has been shown to improve listeners' comprehension, their satisfaction with an interactive system, the efficiency with which they execute conversational tasks, and the likelihood of achieving (...)
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  • Practical reasoning as presumptive argumentation using action based alternating transition systems.Katie Atkinson & Trevor Bench-Capon - 2007 - Artificial Intelligence 171 (10-15):855-874.
    In this paper we describe an approach to practical reasoning, reasoning about what it is best for a particular agent to do in a given situation, based on presumptive justifications of action through the instantiation of an argument scheme, which is then subject to examination through a series of critical questions. We identify three particular aspects of practical reasoning which distinguish it from theoretical reasoning. We next provide an argument scheme and an associated set of critical questions which is able (...)
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  • A Formal Model of Legal Argumentation.Giovanni Sartor - 1994 - Ratio Juris 7 (2):177-211.
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  • A logic for default reasoning.Ray Reiter - 1980 - Artificial Intelligence 13 (1-2):81-137.
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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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  • Towards a formal account of reasoning about evidence: Argumentation schemes and generalisations. [REVIEW]Floris Bex, Henry Prakken, Chris Reed & Douglas Walton - 2003 - Artificial Intelligence and Law 11 (2-3):125-165.
    This paper studies the modelling of legal reasoning about evidence within general theories of defeasible reasoning and argumentation. In particular, Wigmore's method for charting evidence and its use by modern legal evidence scholars is studied in order to give a formal underpinning in terms of logics for defeasible argumentation. Two notions turn out to be crucial, viz. argumentation schemes and empirical generalisations.
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  • SCC-recursiveness: a general schema for argumentation semantics.Pietro Baroni, Massimiliano Giacomin & Giovanni Guida - 2005 - Artificial Intelligence 168 (1-2):162-210.
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  • Dialectic proof procedures for assumption-based, admissible argumentation.P. M. Dung, R. A. Kowalski & F. Toni - 2006 - Artificial Intelligence 170 (2):114-159.
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  • On the computational complexity of assumption-based argumentation for default reasoning.Yannis Dimopoulos, Bernhard Nebel & Francesca Toni - 2002 - Artificial Intelligence 141 (1-2):57-78.
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  • Abstract argumentation systems.Gerard A. W. Vreeswijk - 1997 - Artificial Intelligence 90 (1-2):225-279.
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  • Argument based machine learning applied to law.Martin Možina, Jure Žabkar, Trevor Bench-Capon & Ivan Bratko - 2005 - Artificial Intelligence and Law 13 (1):53-73.
    In this paper we discuss the application of a new machine learning approach – Argument Based Machine Learning – to the legal domain. An experiment using a dataset which has also been used in previous experiments with other learning techniques is described, and comparison with previous experiments made. We also tested this method for its robustness to noise in learning data. Argumentation based machine learning is particularly suited to the legal domain as it makes use of the justifications of decisions (...)
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  • Games that agents play: A formal framework for dialogues between autonomous agents. [REVIEW]Peter McBurney & Simon Parsons - 2002 - Journal of Logic, Language and Information 11 (3):315-334.
    We present a logic-based formalism for modeling ofdialogues between intelligent and autonomous software agents,building on a theory of abstract dialogue games which we present.The formalism enables representation of complex dialogues assequences of moves in a combination of dialogue games, and allowsdialogues to be embedded inside one another. The formalism iscomputational and its modular nature enables different types ofdialogues to be represented.
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  • Rationales and argument moves.R. P. Loui & Jeff Norman - 1995 - Artificial Intelligence and Law 3 (3):159-189.
    We discuss five kinds of representations of rationales and provide a formal account of how they can alter disputation. The formal model of disputation is derived from recent work in argument. The five kinds of rationales are compilation rationales, which can be represented without assuming domain-knowledge (such as utilities) beyond that normally required for argument. The principal thesis is that such rationales can be analyzed in a framework of argument not too different from what AI already has. The result is (...)
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  • The relative efficiency of propositional proof systems.Stephen A. Cook & Robert A. Reckhow - 1979 - Journal of Symbolic Logic 44 (1):36-50.
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  • A mathematical treatment of defeasible reasoning and its implementation.Guillermo R. Simari & Ronald P. Loui - 1992 - Artificial Intelligence 53 (2-3):125-157.
    We present a mathematical approach to defeasible reasoning based on arguments. This approach integrates the notion of specificity introduced by Poole and the theory of warrant presented by Pollock. The main contribution of this paper is a precise, well-defined system which exhibits correct behavior when applied to the benchmark examples in the literature. It aims for usability rather than novelty. We prove that an order relation can be introduced among equivalence classes of arguments under the equi-specificity relation. We also prove (...)
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  • On the complexity of choosing the branching literal in DPLL.Paolo Liberatore - 2000 - Artificial Intelligence 116 (1-2):315-326.
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  • Persuasive argumentation in negotiation.Katia P. Sycara - 1990 - Theory and Decision 28 (3):203-242.
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  • Semantic Considerations on nonmonotonic Logic.Robert C. Moore - 1985 - Artificial Intelligence 25 (1):75-94.
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  • Criteria and our knowledge of the material world.John L. Pollock - 1967 - Philosophical Review 76 (1):28-60.
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  • An executable specification of a formal argumentation protocol.Alexander Artikis, Marek Sergot & Jeremy Pitt - 2007 - Artificial Intelligence 171 (10-15):776-804.
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  • Laying the foundations for a World Wide Argument Web.Iyad Rahwan, Fouad Zablith & Chris Reed - 2007 - Artificial Intelligence 171 (10-15):897-921.
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  • Nonmonotonic reasoning, conditional objects and possibility theory.Salem Benferhat, Didier Dubois & Henri Prade - 1997 - Artificial Intelligence 92 (1-2):259-276.
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  • Reaching agreements through argumentation: a logical model and implementation.Sarit Kraus, Katia Sycara & Amir Evenchik - 1998 - Artificial Intelligence 104 (1-2):1-69.
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  • A logic-based theory of deductive arguments☆☆This is an extended version of a paper entitled “Towards a logic-based theory of argumentation” published in the Proceedings of the National Conference on Artificial Intelligence (AAAI'2000), Austin, TX, MIT Press, Cambridge, MA, 2000. [REVIEW]Philippe Besnard & Anthony Hunter - 2001 - Artificial Intelligence 128 (1-2):203-235.
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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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  • On principle-based evaluation of extension-based argumentation semantics.Pietro Baroni & Massimiliano Giacomin - 2007 - Artificial Intelligence 171 (10-15):675-700.
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  • Negotiating using rewards.Sarvapali D. Ramchurn, Carles Sierra, Lluís Godo & Nicholas R. Jennings - 2007 - Artificial Intelligence 171 (10-15):805-837.
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  • Two party immediate response disputes: Properties and efficiency.Paul E. Dunne & T. J. M. Bench-Capon - 2003 - Artificial Intelligence 149 (2):221-250.
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  • Generation and evaluation of user tailored responses in multimodal dialogue.M. A. Walker, S. J. Whittaker, A. Stent, P. Maloor, J. Moore, M. Johnston & G. Vasireddy - 2004 - Cognitive Science 28 (5):811-840.
    When people engage in conversation, they tailor their utterances to their conversational partners, whether these partners are other humans or computational systems. This tailoring, or adaptation to the partner takes place in all facets of human language use, and is based on a mental model or a user model of the conversational partner. Such adaptation has been shown to improve listeners' comprehension, their satisfaction with an interactive system, the efficiency with which they execute conversational tasks, and the likelihood of achieving (...)
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  • Arguments and cases: An inevitable intertwining. [REVIEW]David B. Skalak & Edwina L. Rissland - 1992 - Artificial Intelligence and Law 1 (1):3-44.
    We discuss several aspects of legal arguments, primarily arguments about the meaning of statutes. First, we discuss how the requirements of argument guide the specification and selection of supporting cases and how an existing case base influences argument formation. Second, we present,our evolving taxonomy of patterns of actual legal argument. This taxonomy builds upon our much earlier work on argument moves and also on our more recent analysis of how cases are used to support arguments for the interpretation of legal (...)
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  • How to reason defeasibly.John L. Pollock - 1992 - Artificial Intelligence 57 (1):1-42.
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  • Subjective logic and arguing with evidence.Nir Oren, Timothy J. Norman & Alun Preece - 2007 - Artificial Intelligence 171 (10-15):838-854.
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  • An application of formal argumentation: Fusing Bayesian networks in multi-agent systems.Søren Holbech Nielsen & Simon Parsons - 2007 - Artificial Intelligence 171 (10-15):754-775.
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  • Argument based machine learning.Martin Možina, Jure Žabkar & Ivan Bratko - 2007 - Artificial Intelligence 171 (10-15):922-937.
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  • Nonmonotonic causal theories.Joohyung Lee, Vladimir Lifschitz & Hudson Turner - 2004 - Artificial Intelligence 153 (1-2):49-104.
    cuted actions. It has been applied to several challenge problems in the theory of commonsense knowledge. We study the relationship between this formalism and other work on nonmonotonic reasoning and knowl-.
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  • E-motion: Moving Toward the Utilization of Artificial Emotion.Michael A. Gilbert & T. J. M. Bench-Capon - 2002 - Informal Logic 22 (3).
    During human-human interaction, emotion plays a vital role in structuring dialogue. Emotional content drives features such as topic shift, lexicalisation change and timing; it affects the delicate balance between goals related to the task at hand and those of social interaction; and it represents one type of feedback on the effect that utterances are having. These various facets are so central to most real-world interaction, that it is reasonable to suppose that emotion should also play an important role in human-computer (...)
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  • More on non-cooperation in dialogue logic.D. Gabbay & J. Woods - 2001 - Logic Journal of the IGPL 9 (2):305-324.
    Stone-walling dialogues are exercises in structured non-cooperation. It is true that dialogue participants need to cooperate with one another and in ways sufficient to make possible the very dialogue they are now having. Beyond that there is room for non-cooperation on a scale that gives great offence to what we call the Goody Two-Shoes Model of argument. In this paper, we argue that non-cooperation dialogues have perfectly legitimate objectives and that in relation to those objectives they need not be considered (...)
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  • Towards a Formal Account of Reasoning about Evidence: Argumentation Schemes and Generalisations.Bex Floris, Prakken Henry, Reed Chris & Walton Douglas - 2003 - Artificial Intelligence and Law 11 (2-3):125-165.
    This paper studies the modelling of legal reasoning about evidence within general theories of defeasible reasoning and argumentation. In particular, Wigmore's method for charting evidence and its use by modern legal evidence scholars is studied in order to give a formal underpinning in terms of logics for defeasible argumentation. Two notions turn out to be crucial, viz. argumentation schemes and empirical generalisations.
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  • Computational properties of argument systems satisfying graph-theoretic constraints.Paul E. Dunne - 2007 - Artificial Intelligence 171 (10-15):701-729.
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  • Coherence in finite argument systems.Paul E. Dunne & T. J. M. Bench-Capon - 2002 - Artificial Intelligence 141 (1-2):187-203.
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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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  • An abstract, argumentation-theoretic approach to default reasoning.A. Bondarenko, P. M. Dung, R. A. Kowalski & F. Toni - 1997 - Artificial Intelligence 93 (1-2):63-101.
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  • Default reasoning using classical logic.Rachel Ben-Eliyahu & Rina Dechter - 1996 - Artificial Intelligence 84 (1-2):113-150.
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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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  • 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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