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  1. A Computational Model of Argumentation Schemes for Multi-Agent Systems.Alison R. Panisson, Peter McBurney & Rafael H. Bordini - 2021 - Argument and Computation 12 (3):357-395.
    There are many benefits of using argumentation-based techniques in multi-agent systems, as clearly shown in the literature. Such benefits come not only from the expressiveness that argumentation-based techniques bring to agent communication but also from the reasoning and decision-making capabilities under conditions of conflicting and uncertain information that argumentation enables for autonomous agents. When developing multi-agent applications in which argumentation will be used to improve agent communication and reasoning, argumentation schemes are useful in addressing the requirements of the application domain (...)
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  • A Generalized Proof-Theoretic Approach to Logical Argumentation Based on Hypersequents.AnneMarie Borg, Christian Straßer & Ofer Arieli - 2021 - Studia Logica 109 (1):167-238.
    In this paper we introduce hypersequent-based frameworks for the modelling of defeasible reasoning by means of logic-based argumentation and the induced entailment relations. These structures are an extension of sequent-based argumentation frameworks, in which arguments and the attack relations among them are expressed not only by Gentzen-style sequents, but by more general expressions, called hypersequents. This generalization allows us to overcome some of the known weaknesses of logical argumentation frameworks and to prove several desirable properties of the entailments that are (...)
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  • A Structured Argumentation Framework for Modeling Debates in the Formal Sciences.Marcos Cramer & Jérémie Dauphin - 2020 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 51 (2):219-241.
    Scientific research in the formal sciences comes in multiple degrees of formality: fully formal work; rigorous proofs that practitioners know to be formalizable in principle; and informal work like rough proof sketches and considerations about the advantages and disadvantages of various formal systems. This informal work includes informal and semi-formal debates between formal scientists, e.g. about the acceptability of foundational principles and proposed axiomatizations. In this paper, we propose to use the methodology of structured argumentation theory to produce a formal (...)
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  • The Elusive Notion of “Argument Quality”.Michael H. G. Hoffmann - 2018 - Argumentation 32 (2):213-240.
    We all seem to have a sense of what good and bad arguments are, and there is a long history—focusing on fallacies—of trying to provide objective standards that would allow a clear separation of good and bad arguments. This contribution discusses the limits of attempts to determine the quality of arguments. It begins with defining bad arguments as those that deviate from an established standard of good arguments. Since there are different conceptualizations of “argument”—as controversy, as debate, and as justification—and (...)
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  • Incremental Computation for Structured Argumentation Over Dynamic DeLP Knowledge Bases.Gianvincenzo Alfano, Sergio Greco, Francesco Parisi, Gerardo I. Simari & Guillermo R. Simari - 2021 - Artificial Intelligence 300:103553.
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  • A Top-Level Model of Case-Based Argumentation for Explanation: Formalisation and Experiments.Henry Prakken & Rosa Ratsma - forthcoming - Argument and Computation:1-36.
    This paper proposes a formal top-level model of explaining the outputs of machine-learning-based decision-making applications and evaluates it experimentally with three data sets. The model draws on AI & law research on argumentation with cases, which models how lawyers draw analogies to past cases and discuss their relevant similarities and differences in terms of relevant factors and dimensions in the problem domain. A case-based approach is natural since the input data of machine-learning applications can be seen as cases. While the (...)
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  • An Informant-Based Approach to Argument Strength in Defeasible Logic Programming.Andrea Cohen, Sebastian Gottifredi, Luciano H. Tamargo, Alejandro J. García & Guillermo R. Simari - 2021 - Argument and Computation 12 (1):115-147.
    This work formalizes an informant-based structured argumentation approach in a multi-agent setting, where the knowledge base of an agent may include information provided by other agents, and each piece of knowledge comes attached with its informant. In that way, arguments are associated with the set of informants corresponding to the information they are built upon. Our approach proposes an informant-based notion of argument strength, where the strength of an argument is determined by the credibility of its informant agents. Moreover, we (...)
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  • Computational Complexity of Flat and Generic Assumption-Based Argumentation, with and Without Probabilities.Kristijonas Čyras, Quentin Heinrich & Francesca Toni - 2021 - Artificial Intelligence 293:103449.
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  • A General Semi-Structured Formalism for Computational Argumentation: Definition, Properties, and Examples of Application.Pietro Baroni, Massimiliano Giacomin & Beishui Liao - 2018 - Artificial Intelligence 257:158-207.
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  • Assumption-Based Argumentation with Preferences and Goals for Patient-Centric Reasoning with Interacting Clinical Guidelines.Kristijonas Čyras, Tiago Oliveira, Amin Karamlou & Francesca Toni - forthcoming - Argument and Computation:1-41.
    A paramount, yet unresolved issue in personalised medicine is that of automated reasoning with clinical guidelines in multimorbidity settings. This entails enabling machines to use computerised generic clinical guideline recommendations and patient-specific information to yield patient-tailored recommendations where interactions arising due to multimorbidities are resolved. This problem is further complicated by patient management desiderata, in particular the need to account for patient-centric goals as well as preferences of various parties involved. We propose to solve this problem of automated reasoning with (...)
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  • On Searching Explanatory Argumentation Graphs.Régis Riveret - 2020 - Journal of Applied Non-Classical Logics 30 (2):123-192.
    Cases or examples can be often explained by the interplay of arguments in favour or against their outcomes. This paper addresses the problem of finding explanations for a collection of cases where an explanation is a labelled argumentation graph consistent with the cases, and a case is represented as a statement labelling. The focus is on semi-abstract argumentation graphs specifying attack and subargument relations between arguments, along with particular complete argument labellings taken from probabilistic argumentation where arguments can be excluded. (...)
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  • 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.
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  • Structural Constraints for Dynamic Operators in Abstract Argumentation.Johannes P. Wallner - 2020 - Argument and Computation 11 (1-2):151-190.
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  • Acquiring Knowledge From Expert Agents in a Structured Argumentation Setting.Ramiro Andres Agis, Sebastian Gottifredi & Alejandro Javier García - 2019 - Argument and Computation 10 (2):149-189.
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