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Defeasible Reasoning

Cognitive Science 11 (4):481-518 (1987)

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  1. Presumptions, and How They Relate to Arguments from Ignorance.Petar Bodlović - 2019 - Argumentation 33 (4):579-604.
    By explaining the argument from ignorance in terms of the presumption of innocence, many textbooks in argumentation theory suggest that some arguments from ignorance might share essential features with some types of presumptive reasoning. The stronger version of this view, suggesting that arguments from ignorance and presumptive reasoning are almost indistinguishable, is occasionally proposed by Douglas Walton. This paper explores the nature and limits of the stronger proposal and argues that initial presumptions and arguments from ignorance are not closely connected. (...)
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  • Logic, Reasoning, Argumentation: Insights From the Wild.Frank Zenker - forthcoming - Logic and Logical Philosophy.
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  • Peirce Knew Why Abduction Isn’T IBE—A Scheme and Critical Questions for Abductive Argument.Shiyang Yu & Frank Zenker - 2018 - Argumentation 32 (4):569-587.
    Whether abduction is treated as an argument or as an inference, the mainstream view presupposes a tight connection between abduction and inference to the best explanation. This paper critically evaluates this link and supports a narrower view on abduction. Our main thesis is that merely the hypothesis-generative aspect, but not the evaluative aspect, is properly abductive in the sense introduced by C. S. Peirce. We show why equating abduction with IBE unnecessarily complicates argument evaluation by levelling the status of abduction (...)
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  • Philosophy and Machine Learning.Paul Thagard - 1990 - Canadian Journal of Philosophy 20 (2):261-76.
    This article discusses the philosophical relevance of recent computational work on inductive inference being conducted in the rapidly growing branch of artificial intelligence called machine learning.
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  • Philosophy and Machine Learning.Paul Thagard - 1990 - Canadian Journal of Philosophy 20 (2):261-276.
    Philosophers since the ancient Greeks have investigated the nature of different kinds of inference. Although deductive inference in the form of Aristotelian syllogisms and Fregean formal logic has predominated, much attention has also been paid to induction, inference where the conclusion does not follow necessarily from the premises.
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  • Entkräftung und Widerruf: Fügsame Überzeugungen im Zeitverlauf.Benjamin McMyler - 2019 - Deutsche Zeitschrift für Philosophie 67 (6):992-1007.
    A speaker’s retraction of her own previous testimony serves to defeat the reason for belief provided by her testimony in a distinctive way. In telling an addressee that p, the speaker purports to settle for the addressee the question whether p. In retracting her testimony, the speaker then revokes her settling of this question for the addressee, cancelling the addressee’s entitlement to pass the epistemic buck back to her should the content of her belief be challenged, and this entitlement is (...)
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  • Mental Files.François Recanati - 2012 - Oxford University Press.
    Over the past fifty years the philosophy of language and mind has been dominated by a nondescriptivist approach to content and reference. This book attempts to recast and systematize that approach by offering an indexical model in terms of mental files. According to Recanati, we refer through mental files, the function of which is to store information derived through certain types of contextual relation the subject bears to objects in his or her environment. The reference of a file is determined (...)
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  • On Degrees of Justification.Gregor Betz - 2012 - Erkenntnis 77 (2):237-272.
    This paper gives an explication of our intuitive notion of strength of justification in a controversial debate. It defines a thesis' degree of justification within the bipolar argumentation framework of the theory of dialectical structures as the ratio of coherently adoptable positions according to which that thesis is true over all coherently adoptable positions. Broadening this definition, the notion of conditional degree of justification, i.e.\ degree of partial entailment, is introduced. Thus defined degrees of justification correspond to our pre-theoretic intuitions (...)
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  • Abstract Argumentation.Robert A. Kowalski & Francesca Toni - 1996 - Artificial Intelligence and Law 4 (3-4):275-296.
    In this paper we explore the thesis that the role of argumentation in practical reasoning in general and legal reasoning in particular is to justify the use of defeasible rules to derive a conclusion in preference to the use of other defeasible rules to derive a conflicting conclusion. The defeasibility of rules is expressed by means of non-provability claims as additional conditions of the rules.We outline an abstract approach to defeasible reasoning and argumentation which includes many existing formalisms, including default (...)
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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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  • Dialectical Models in Artificial Intelligence and Law.Jaap Hage - 2000 - Artificial Intelligence and Law 8 (2-3):137-172.
    Dialogues and dialectics have come to playan important role in the field of ArtificialIntelligence and Law. This paper describes thelegal-theoretical and logical background of this role,and discusses the different services into whichdialogues are put. These services include:characterising logical operators, modelling thedefeasibility of legal reasoning, providing the basisfor legal justification and identifying legal issues,and establishing the law in concrete cases. Specialattention is given to the requirements oflaw-establishing dialogues.
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  • Self-Defeating Arguments.John L. Pollock - 1991 - Minds and Machines 1 (4):367-392.
    An argument is self-defeating when it contains defeaters for some of its own defeasible lines. It is shown that the obvious rules for defeat among arguments do not handle self-defeating arguments correctly. It turns out that they constitute a pervasive phenomenon that threatens to cripple defeasible reasoning, leading to almost all defeasible reasoning being defeated by unexpected interactions with self-defeating arguments. This leads to some important changes in the general theory of defeasible reasoning.
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  • A Model of Argumentation and its Application to Legal Reasoning.Kathleen Freeman & Arthur M. Farley - 1996 - Artificial Intelligence and Law 4 (3-4):163-197.
    We present a computational model of dialectical argumentation that could serve as a basis for legal reasoning. The legal domain is an instance of a domain in which knowledge is incomplete, uncertain, and inconsistent. Argumentation is well suited for reasoning in such weak theory domains. We model argument both as information structure, i.e., argument units connecting claims with supporting data, and as dialectical process, i.e., an alternating series of moves by opposing sides. Our model includes burden of proof as a (...)
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  • Solving a Murder Case by Asking Critical Questions: An Approach to Fact-Finding in Terms of Argumentation and Story Schemes. [REVIEW]Floris Bex & Bart Verheij - 2012 - Argumentation 26 (3):325-353.
    In this paper, we look at reasoning with evidence and facts in criminal cases. We show how this reasoning may be analysed in a dialectical way by means of critical questions that point to typical sources of doubt. We discuss critical questions about the evidential arguments adduced, about the narrative accounts of the facts considered, and about the way in which the arguments and narratives are connected in an analysis. Our treatment shows how two different types of knowledge, represented as (...)
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  • Institutions with a Hierarchy of Authorities in Distributed Dynamic Environments.Guido Boella & Leendert van der Torre - 2008 - Artificial Intelligence and Law 16 (1):53-71.
    A single global authority is not sufficient to regulate heterogenous agents in multiagent systems based on distributed architectures, due to idiosyncratic local situations and to the need to regulate new issues as soon as they arise. On the one hand institutions should be structured as normative systems with a hierarchy of authorities able to cope with the dynamics of local situations, but on the other hand higher authorities should be able to delimit the autonomy of lower authorities to issue valid (...)
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  • Hard Cases: A Procedural Approach. [REVIEW]Jaap C. Hage, Ronald Leenes & Arno R. Lodder - 1993 - Artificial Intelligence and Law 2 (2):113-167.
    Much work on legal knowledge systems treats legal reasoning as arguments that lead from a description of the law and the facts of a case, to the legal conclusion for the case. The reasoning steps of the inference engine parallel the logical steps by means of which the legal conclusion is derived from the factual and legal premises. In short, the relation between the input and the output of a legal inference engine is a logical one. The truth of the (...)
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  • The Theory of Nomic Probability.John L. Pollock - 1992 - Synthese 90 (2):263 - 299.
    This article sketches a theory of objective probability focusing on nomic probability, which is supposed to be the kind of probability figuring in statistical laws of nature. The theory is based upon a strengthened probability calculus and some epistemological principles that formulate a precise version of the statistical syllogism. It is shown that from this rather minimal basis it is possible to derive theorems comprising (1) a theory of direct inference, and (2) a theory of induction. The theory of induction (...)
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  • Heuristics, Justification, and Defeasible Reasoning.Timothy R. Colburn - 1995 - Minds and Machines 5 (4):467-487.
    Heuristics can be regarded as justifying the actions and beliefs of problem-solving agents. I use an analysis of heuristics to argue that a symbiotic relationship exists between traditional epistemology and contemporary artificial intelligence. On one hand, the study of models of problem-solving agents usingquantitative heuristics, for example computer programs, can reveal insight into the understanding of human patterns of epistemic justification by evaluating these models'' performance against human problem-solving. On the other hand,qualitative heuristics embody the justifying ability of defeasible rules, (...)
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  • Book Review. [REVIEW]Ronald P. Loui & David B. Skalak - 1995 - Artificial Intelligence and Law 3 (1-2):143-150.
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  • Argument Construction and Reinstatement in Logics for Defeasible Reasoning.John F. Horty - 2001 - Artificial Intelligence and Law 9 (1):1-28.
    This paper points out some problems with two recent logical systems – one due to Prakken and Sartor, the other due to Kowalski and Toni – designedfor the representation of defeasible arguments in general, but with a specialemphasis on legal reasoning.
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  • Rationality, Function, and Content.John L. Pollock - 1992 - Philosophical Studies 65 (1-2):129-151.
    To summarize, in order for rational agents to be able to engage in the sophisticated kinds of reasoning exemplified by human beings, they must be able to introspect much of their cognition. The problem of other minds and the problem of knowing the mental states of others will arise automatically for any rational agent that is able to introspect its own cognition. The most that a rational agent can reasonably believe about other rational agents is that they have rational architectures (...)
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  • Argument and Belief: Where We Stand in the Keynesian Tradition. [REVIEW]R. P. Loui - 1991 - Minds and Machines 1 (4):357-365.
    There is the idea that rational belief for a single individual can be constructed via a process of unilateral argument. To preempt antipathy between the AI communities that can claim the idea that rational belief can be so constructed, we trace the idea to the beginning of this century, to Keynes' dispute with Russell over logic and probability. We review how Keynesian ideas were revived in AI's work on non-monotonic reasoning and parallel developments in philosophical logic.
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  • How to Use Probabilities in Reasoning.John L. Pollock - 1991 - Philosophical Studies 64 (1):65 - 85.
    Probabilities are important in belief updating, but probabilistic reasoning does not subsume everything else (as the Bayesian would have it). On the contrary, Bayesian reasoning presupposes knowledge that cannot itself be obtained by Bayesian reasoning, making generic Bayesianism an incoherent theory of belief updating. Instead, it is indefinite probabilities that are of principal importance in belief updating. Knowledge of such indefinite probabilities is obtained by some form of statistical induction, and inferences to non-probabilistic conclusions are carried out in accordance with (...)
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  • Pollock on Defeasible Reasons.Scott Sturgeon - 2012 - Philosophical Studies (1):1-14.
  • Evaluating Dialectical Structures.Gregor Betz - 2009 - Journal of Philosophical Logic 38 (3):283-312.
    This paper develops concepts and procedures for the evaluation of complex debates. They provide means for answering such questions as whether a thesis has to be considered as proven or disproven in a debate or who carries a burden of proof. While being based on classical logic, this framework represents an (argument-based) approach to non-monotonic, or defeasible reasoning. Debates are analysed as dialectical structures, i.e. argumentation systems with an attack- as well as a support-relationship. The recursive status assignment over the (...)
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  • Abstract Argument Games Via Modal Logic.Davide Grossi - 2013 - Synthese 190 (S1).
    Inspired by some logical considerations, the paper proposes a novel perspective on the use of two-players zero-sum games in abstract argumentation. The paper first introduces a second-order modal logic, within which all main Dung-style semantics are shown to be formalizable, and then studies the model checking game of this logic. The model checking game is then used to provide a systematic game theoretic proof procedure to test membership with respect to all those semantics formalizable in the logic. The paper discusses (...)
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  • A History of AI and Law in 50 Papers: 25 Years of the International Conference on AI and Law. [REVIEW]Trevor Bench-Capon, Michał Araszkiewicz, Kevin Ashley, Katie Atkinson, Floris Bex, Filipe Borges, Daniele Bourcier, Paul Bourgine, Jack G. Conrad, Enrico Francesconi, Thomas F. Gordon, Guido Governatori, Jochen L. Leidner, David D. Lewis, Ronald P. Loui, L. Thorne McCarty, Henry Prakken, Frank Schilder, Erich Schweighofer, Paul Thompson, Alex Tyrrell, Bart Verheij, Douglas N. Walton & Adam Z. Wyner - 2012 - Artificial Intelligence and Law 20 (3):215-319.
    We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of the development of AI and Law, while often offering some personal reactions and reflections. As a whole, the subsections build into (...)
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  • An Ontology in Owl for Legal Case-Based Reasoning.Adam Wyner - 2008 - Artificial Intelligence and Law 16 (4):361-387.
    The paper gives ontologies in the Web Ontology Language (OWL) for Legal Case-based Reasoning (LCBR) systems, giving explicit, formal, and general specifications of a conceptualisation LCBR. Ontologies for different systems allows comparison and contrast between them. OWL ontologies are standardised, machine-readable formats that support automated processing with Semantic Web applications. Intermediate concepts, concepts between base-level concepts and higher level concepts, are central in LCBR. The main issues and their relevance to ontological reasoning and to LCBR are discussed. Two LCBR systems (...)
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  • A Theory of Legal Reasoning and a Logic to Match.Jaap Hage - 1996 - Artificial Intelligence and Law 4 (3-4):199-273.
    This paper describes a model of legal reasoning and a logic for reasoning with rules, principles and goals that is especially suited to this model of legal reasoning. The paper consists of three parts. The first part describes a model of legal reasoning based on a two-layered view of the law. The first layer consists of principles and goals that express fundamental ideas of a legal system. The second layer contains legal rules which in a sense summarise the outcome of (...)
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  • Defeasible Reasoning and Logic Programming.Timothy R. Colburn - 1991 - Minds and Machines 1 (4):417-436.
    The general conditions of epistemic defeat are naturally represented through the interplay of two distinct kinds of entailment, deductive and defeasible. Many of the current approaches to modeling defeasible reasoning seek to define defeasible entailment via model-theoretic notions like truth and satisfiability, which, I argue, fails to capture this fundamental distinction between truthpreserving and justification-preserving entailments. I present an alternative account of defeasible entailment and show how logic programming offers a paradigm in which the distinction can be captured, allowing for (...)
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  • The Dynamics of Relevance: Adaptive Belief Revision.Van De Putte Frederik & Verdée Peter - 2012 - Synthese 187 (S1):1-42.
    This paper presents eight (previously unpublished) adaptive logics for belief revision, each of which define a belief revision operation in the sense of the AGM framework. All these revision operations are shown to satisfy the six basic AGM postulates for belief revision, and Parikh's axiom of Relevance. Using one of these logics as an example, we show how their proof theory gives a more dynamic flavor to belief revision than existing approaches. It is argued that this turns belief revision (that (...)
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  • The Epistemic Basis of Defeasible Reasoning.Robert L. Causey - 1991 - Minds and Machines 1 (4):437-458.
    This article argues that: (i) Defeasible reasoning is the use of distinctive procedures for belief revision when new evidence or new authoritative judgment is interpolated into a system of beliefs about an application domain. (ii) These procedures can be explicated and implemented using standard higher-order logic combined with epistemic assumptions about the system of beliefs. The procedures mentioned in (i) depend on the explication in (ii), which is largely described in terms of a Prolog program, EVID, which implements a system (...)
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  • On Nonmonotonic Reasoning with the Method of Sweeping Presumptions.Steven O. Kimbrough & Hua Hua - 1991 - Minds and Machines 1 (4):393-416.
    Reasoning almost always occurs in the face of incomplete information. Such reasoning is nonmonotonic in the sense that conclusions drawn may later be withdrawn when additional information is obtained. There is an active literature on the problem of modeling such nonmonotonic reasoning, yet no category of method-let alone a single method-has been broadly accepted as the right approach. This paper introduces a new method, called sweeping presumptions, for modeling nonmonotonic reasoning. The main goal of the paper is to provide an (...)
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  • Well-Founded Semantics for Defeasible Logic.Frederick Maier & Donald Nute - 2010 - Synthese 176 (2):243 - 274.
    Fixpoint semantics are provided for ambiguity blocking and propagating variants of Nute's defeasible logic. The semantics are based upon the well-founded semantics for logic programs. It is shown that the logics are sound with respect to their counterpart semantics and complete for locally finite theories. Unlike some other nonmonotonic reasoning formalisms such as Reiter's default logic, the two defeasible logics are directly skeptical and so reject floating conclusions. For defeasible theories with transitive priorities on defeasible rules, the logics are shown (...)
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  • Reasoning with Conditionals.Guy Politzer - 2007 - Topoi 26 (1):79-95.
    This paper reviews the psychological investigation of reasoning with conditionals, putting an emphasis on recent work. In the first part, a few methodological remarks are presented. In the second part, the main theories of deductive reasoning (mental rules, mental models, and the probabilistic approach) are considered in turn; their content is summarised and the semantics they assume for if and the way they explain formal conditional reasoning are discussed, in particular in the light of experimental work on the probability of (...)
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  • How to Get Certain Knowledge From Fallible Justification.Peter D. Klein - 2019 - Episteme 16 (4):395-412.
    “Real knowledge,” as I use the term, is the most highly prized form of true belief sought by an epistemic agent. This paper argues that defeasible infinitism provides a good way to characterize real knowledge and it shows how real knowledge can arise from fallible justification. Then, I argue that there are two ways of interpreting Ernest Sosa's account of real knowledge as belief that is aptly formed and capable of being fully defended. On the one hand, if beliefs are (...)
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  • Do Psychological Defeaters Undermine Foundationalism in Moral Epistemology? - a Critique of Sinnott-Armstrong’s Argument Against Ethical Intuitionism.Philipp Schwind - 2019 - Ethical Theory and Moral Practice 22 (4):941-952.
    Foundationalism in moral epistemology is a core tenet of ethical intuitionism. According to foundationalism, some moral beliefs can be known without inferential justification; instead, all that is required is a proper understanding of the beliefs in question. In an influential criticism against this view, Walter Sinnott-Armstrong has argued that certain psychological facts undermine the reliability of moral intuitions. He claims that foundationalists would have to show that non-inferentially justified beliefs are not subject to those defeaters, but this would already constitute (...)
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  • Evaluating Dialectical Structures with Bayesian Methods.Gregor Betz - 2008 - Synthese 163 (1):25-44.
    This paper shows how complex argumentation, analyzed as dialectical structures, can be evaluated within a Bayesian framework by interpreting them as coherence constraints on subjective degrees of belief. A dialectical structure is a set of arguments (premiss-conclusion structure) among which support- and attack-relations hold. This approach addresses the observation that some theses in a debate can be better justified than others and thus fixes a shortcoming of a theory of defeasible reasoning which applies the bivalence principle to argument evaluations by (...)
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  • Dialectical Argumentation with Argumentation Schemes: An Approach to Legal Logic. [REVIEW]Bart Verheij - 2003 - Artificial Intelligence and Law 11 (2-3):167-195.
    This paper describes an approach to legal logic based on the formal analysis of argumentation schemes. Argumentation schemes a notion borrowed from the .eld of argumentation theory - are a kind of generalized rules of inference, in the sense that they express that given certain premises a particular conclusion can be drawn. However, argumentation schemes need not concern strict, abstract, necessarily valid patterns of reasoning, but can be defeasible, concrete and contingently valid, i.e., valid in certain contexts or under certain (...)
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  • Local Logics, Non-Monotonicity and Defeasible Argumentation.Gustavo A. Bodanza & Fernando A. Tohmé - 2005 - Journal of Logic, Language and Information 14 (1):1-12.
    In this paper we present an embedding of abstract argumentation systems into the framework of Barwise and Seligmans logic of information flow. We show that, taking P.M. Dungs characterization of argument systems, a local logic over states of a deliberation may be constructed. In this structure, the key feature of non-monotonicity of commonsense reasoning obtains as the transition from one local logic to another, due to a change in certain background conditions. Each of Dungs extensions of argument systems leads to (...)
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  • The Case for Psychologism in Default and Inheritance Reasoning.Francis Jeffry Pelletier & Renée Elio - 2005 - Synthese 146 (1-2):7-35.
    Default reasoning occurs whenever the truth of the evidence available to the reasoner does not guarantee the truth of the conclusion being drawn. Despite this, one is entitled to draw the conclusion “by default” on the grounds that we have no information which would make us doubt that the inference should be drawn. It is the type of conclusion we draw in the ordinary world and ordinary situations in which we find ourselves. Formally speaking, ‘nonmonotonic reasoning’ refers to argumentation in (...)
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  • Deliberative Discourse and Reasoning From Generic Argument Structures.John L. Yearwood & Andrew Stranieri - 2009 - AI and Society 23 (3):353-377.
    In this article a dialectical model for practical reasoning within a community, based on the Generic/Actual Argument Model (GAAM) is advanced and its application to deliberative dialogue discussed. The GAAM, offers a dynamic template for structuring knowledge within a domain of discourse that is connected to and regulated by a community. The paper demonstrates how the community accepted generic argument structure acts to normatively influence both admissible reasoning and the progression of dialectical reasoning between participants. It is further demonstrated that (...)
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  • An Activity-Centric Argumentation Framework for Assistive Technology Aimed at Improving Health.Esteban Guerrero, Juan Carlos Nieves & Helena Lindgren - 2016 - Argument and Computation 7 (1):5-33.
  • Elementos para una teoría de los grados de justificación.Carlos Andrés Garzón- Rodríguez - 2018 - Ideas Y Valores 67:77-92.
    En este escrito se presentan las bases de una estrategia pragmática, contextualista e inferencialista para articular una teoría que dé cuenta de los grados de justificación de nuestras aserciones. Se arguye que hay contextos de emisión de aserciones configurados con ciertos criterios inferenciales, los cuales responden a propósitos prácticos o teóricos, y conforman, en consecuencia, diferentes estándares de justificación en esos contextos. Finalmente, a partir de una caracterización de tipos de proposiciones, inferencias, compromisos asertivos y esquemas de justificación, se muestra (...)
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  • An Analysis of Critical-Link Semantics with Variable Degrees of Justification.Bin Wei & Henry Prakken - 2016 - Argument and Computation 7 (1):35-53.
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  • Finding Enthymemes in Real-World Texts: A Feasibility Study.Olesya Razuvayevskaya & Simone Teufel - 2017 - Argument and Computation 8 (2):113-129.
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  • The Reasoning View and Defeasible Practical Reasoning.Samuel Asarnow - 2017 - Philosophy and Phenomenological Research 95 (3):614-636.
    According to the Reasoning View about normative reasons, facts about normative reasons for action can be understood in terms of facts about the norms of practical reasoning. I argue that this view is subject to an overlooked class of counterexamples, familiar from debates about Subjectivist theories of normative reasons. Strikingly, the standard strategy Subjectivists have used to respond to this problem cannot be adapted to the Reasoning View. I think there is a solution to this problem, however. I argue that (...)
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  • Defeasible Logic Programming: DeLP-Servers, Contextual Queries, and Explanations for Answers.Alejandro J. García & Guillermo R. Simari - 2014 - Argument and Computation 5 (1):63-88.
    Argumentation represents a way of reasoning over a knowledge base containing possibly incomplete and/or inconsistent information, to obtain useful conclusions. As a reasoning mechanism, the way an argumentation reasoning engine reaches these conclusions resembles the cognitive process that humans follow to analyze their beliefs; thus, unlike other computationally reasoning systems, argumentation offers an intellectually friendly alternative to other defeasible reasoning systems. LogicProgrammingisacomputationalparadigmthathasproducedcompu- tationallyattractivesystemswithremarkablesuccessinmanyapplications. Merging ideas from both areas, Defeasible Logic Programming offers a computational reasoning system that uses an argumentation engine (...)
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  • Religious Disagreement.Helen De Cruz - 2019 - Cambridge: Cambridge University Press.
    This Element examines what we can learn from religious disagreement, focusing on disagreement with possible selves and former selves, the epistemic significance of religious agreement, the problem of disagreements between religious experts, and the significance of philosophy of religion. Helen De Cruz shows how religious beliefs of others constitute significant higher-order evidence. At the same time, she advises that we should not necessarily become agnostic about all religious matters, because our cognitive background colors the way we evaluate evidence. This allows (...)
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  • Defaulting on Reasons.Daniel Bonevac - 2018 - Noûs:229-259.
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