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  1. The benefits of prototypes: The case of medical concepts.Cristina Amoretti, Marcello Frixione & Antonio Lieto - 2017 - Reti, Saperi E Linguaggi, The Italian Journal of Cognitive Sciences, 2017 3.
    In the present paper, we shall discuss the notion of prototype and show its benefits. First, we shall argue that the prototypes of common-sense concepts are necessary for making prompt and reliable categorisations and inferences. However, the features constituting the prototype of a particular concept are neither necessary nor sufficient conditions for determining category membership; in this sense, the prototype might lead to conclusions regarded as wrong from a theoretical perspective. That being said, the prototype remains essential to handling most (...)
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  • Two Problems of Direct Inference.Paul D. Thorn - 2012 - Erkenntnis 76 (3):299-318.
    The article begins by describing two longstanding problems associated with direct inference. One problem concerns the role of uninformative frequency statements in inferring probabilities by direct inference. A second problem concerns the role of frequency statements with gerrymandered reference classes. I show that past approaches to the problem associated with uninformative frequency statements yield the wrong conclusions in some cases. I propose a modification of Kyburg’s approach to the problem that yields the right conclusions. Past theories of direct inference have (...)
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  • GORGIAS: Applying argumentation.Federico Cerutti & Richard Booth - 2018 - Argument and Computation 10 (1):55-81.
    This paper presents the past and present efforts of developing real-life applications of argumentation with the Gorgias preference-based structured argumentation framework of Logic Programming with...
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  • On Floating Conclusions.Daniela Schuster, Jan Broersen & Henry Prakken - 2023 - Deontic Logic and Normative Systems, 16Th International Conference, Deon 2023.
    When there are two lines of argument that contradict each other but still end up with the same conclusion, this conclusion is called a floating conclusion. It is an open topic in skeptical defeasible reasoning if floating conclusions ought to be accepted. Inter- estingly, the answer seems to be changing for different examples. In this paper, we propose a solution for explaining the different treatments of the floating conclusion in the various examples from the literature. We collect the examples from (...)
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  • Menalar Skeptis Adopsi Artificial Intelegence (AI) di Indonesia: ‘Sebuah Tinjauan Filsafat Ilmu Komunikasi’.Felisianus Efrem Jelahut, Herman Yosep Utang, Yosep Emanuel Jelahut & Lasarus Jehamat - 2021 - Jurnal Filsafat Indonesia 4 (2):172-178.
    This research was conducted on the basis of research references from Microsoft Indonesia regarding the adoption of artificial intelligence in Indonesia which obtained research results that there were 14% of employees and leaders of technology-based companies in Indonesia who were still skeptical of the adoption of artificial intelligence. This study aims to provide a theoretical overview from the point of view of the philosophy of communication science in responding to considerations about the good and bad 'doubt' or skepticism of 14% (...)
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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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  • Artificial nonmonotonic neural networks.B. Boutsinas & M. N. Vrahatis - 2001 - Artificial Intelligence 132 (1):1-38.
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  • Inheritance comes of age: applying nonmonotonic techniques to problems in industry.Leora Morgenstern - 1998 - Artificial Intelligence 103 (1-2):237-271.
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  • Must Good Reasoning Satisfy Cumulative Transitivity?Shyam Nair - 2017 - Philosophy and Phenomenological Research 98 (1):123-146.
    There is consensus among computer scientists, logicians, and philosophers that good reasoning with qualitative beliefs must have the structural property of cumulative transitivity or, for short, cut. This consensus is typically explicitly argued for partially on the basis of practical and mathematical considerations. But the consensus is also implicit in the approach philosophers take to almost every puzzle about reasoning that involves multiple steps: philosophers typically assume that if each step in reasoning is acceptable considered on its own, the whole (...)
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  • A dialectical model of assessing conflicting arguments in legal reasoning.H. Prakken & G. Sartor - 1996 - Artificial Intelligence and Law 4 (3-4):331-368.
    Inspired by legal reasoning, this paper presents a formal framework for assessing conflicting arguments. Its use is illustrated with applications to realistic legal examples, and the potential for implementation is discussed. The framework has the form of a logical system for defeasible argumentation. Its language, which is of a logic-programming-like nature, has both weak and explicit negation, and conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is that these priorities (...)
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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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  • Floating conclusions and zombie paths: Two deep difficulties in the “directly skeptical” approach to defeasible inheritance nets.David Makinson & Karl Schlechta - 1991 - Artificial Intelligence 48 (2):199-209.
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  • On Stein's paper: resolving ambiguity in nonmonotonic inheritance hierarchies.Geneviève Simonet & Roland Ducournau - 1994 - Artificial Intelligence 71 (1):183-193.
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  • (1 other version)Skepticism and floating conclusions.John F. Horty - 2002 - Artificial Intelligence 135 (1-2):55-72.
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  • Gödel’s Master Argument: what is it, and what can it do?David Makinson - 2015 - IfCoLog Journal of Logics and Their Applications 2 (2):1-16.
    This text is expository. We explain Gödel’s ‘Master Argument’ for incompleteness as distinguished from the 'official' proof of his 1931 paper, highlight its attractions and limitations, and explain how some of the limitations may be transcended by putting it in a more abstract form that makes no reference to truth.
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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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  • Legal concepts as inferential nodes and ontological categories.Giovanni Sartor - 2009 - Artificial Intelligence and Law 17 (3):217-251.
    I shall compare two views of legal concepts: as nodes in inferential nets and as categories in an ontology (a conceptual architecture). Firstly, I shall introduce the inferential approach, consider its implications, and distinguish the mere possession of an inferentially defined concept from the belief in the concept’s applicability, which also involves the acceptance of the concept’s constitutive inferences. For making this distinction, the inferential and eliminative analysis of legal concepts proposed by Alf Ross will be connected to the views (...)
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  • (1 other version)Skepticism and floating conclusions.John Horty - manuscript
    The purpose of this paper is to question some commonly accepted patterns of reasoning involving nonmonotonic logics that generate multiple extensions. In particular, I argue that the phenomenon of floating conclusions indicates a problem with the view that the skeptical consequences of such theories should be identified with the statements that are supported by each of their various extensions.
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  • The case for connectionism.William Bechtel - 1993 - Philosophical Studies 71 (2):119-54.
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  • Defeasible inheritance with doubt index and its axiomatic characterization.Erik Sandewall - 2010 - Artificial Intelligence 174 (18):1431-1459.
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  • Resolving ambiguity in nonmonotonic inheritance hierarchies.Lynn Andrea Stein - 1992 - Artificial Intelligence 55 (2-3):259-310.
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  • The Computational Origin of Representation.Steven T. Piantadosi - 2020 - Minds and Machines 31 (1):1-58.
    Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic, dynamical, emergentist, sub-symbolic, and grounded approaches to cognition attest. Mental representations—whatever they are—must share many features with each of our theories of representation, and yet there are few hypotheses about how a synthesis could be possible. Here, I develop a theory of the underpinnings of symbolic cognition that shows how sub-symbolic dynamics may give rise (...)
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  • Defaults with Priorities.John Horty - 2007 - Journal of Philosophical Logic 36 (4):367-413.
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  • A Formalism for Nonmonotonic Reasoning Encoded Generics.Yi Mao - 2003 - Dissertation, The University of Texas at Austin
    This dissertation is intended to provide a formalism for those generics that trigger nonmonotonic inferences. The formalism is to reflect intentionality and exception-tolerating features of generics, and has an emphasis on the axiomatization of generic reasoning that encodes nonmonotonicity. ;A modal conditional approach is taken to formalize the nonmonotonic reasoning in general at the level of object language. A serial of logic systems---MN, NID, NCUM, N STCUM---are constructed in an increasing strength of the characterized nonmonotonic inference relation. In these systems, (...)
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  • An appreciation of John Pollock's work on the computational study of argument.Henry Prakken & John Horty - 2012 - Argument and Computation 3 (1):1 - 19.
    John Pollock (1940?2009) was an influential American philosopher who made important contributions to various fields, including epistemology and cognitive science. In the last 25 years of his life, he also contributed to the computational study of defeasible reasoning and practical cognition in artificial intelligence. He developed one of the first formal systems for argumentation-based inference and he put many issues on the research agenda that are still relevant for the argumentation community today. This paper presents an appreciation of Pollock's work (...)
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  • The current status of research on concept combination.Lance J. Rips - 1995 - Mind and Language 10 (1-2):72-104.
    Understanding novel phrases (e.g. upside‐down daisy) and classifying objects in categories named by phrases ought to have common properties, but you'd never know it from current theories. The best candidate for both jobs is the Theory Theory, but it faces difficulties when theories are impoverished. A potential solution is a dual approach that couples theories (representations‐about categories) with fixed mentalese expressions (representations‐of categories). Both representations combine information in parallel when understanding phrases. Although there are objections to the notion that theories (...)
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  • How to reason defeasibly.John L. Pollock - 1992 - Artificial Intelligence 57 (1):1-42.
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  • Two aggregation paradoxes in social decision making: the Ostrogorski paradox and the discursive dilemma.Gabriella Pigozzi - 2006 - Episteme 2 (2):119-128.
    The Ostrogorski paradox and the discursive dilemma are seemingly unrelated paradoxes of aggregation. The former is discussed in traditional social choice theory, while the latter is at the core of the new literature on judgment aggregation. Both paradoxes arise when, in a group, each individual consistently makes a judgment, or expresses a preference, (in the form of yes or no) over specific propositions, and the collective outcome is in some respect inconsistent. While the result is logically inconsistent in the case (...)
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  • On Sandewall's paper: Nonmonotonic inference rules for multiple inheritance with exceptions.Geneviève Simonet - 1996 - Artificial Intelligence 86 (2):359-374.
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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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  • Explaining default intuitions using maximum entropy.Rachel A. Bourne - 2003 - Journal of Applied Logic 1 (3-4):255-271.
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  • Argumentos Máximamente Específicos en Argumentación Rebatible.Cláudio Andrés Alessio - 2016 - Manuscrito 39 (2):5-58.
    Resumen DeLP is a defeasible argumentation system that captures common sense reasoning features. Examples proposed in the literature show that DeLP gets counterintuitive results. We suggest a possible cause of this problem and we propose an approach to neutralize it. The approach is based on the pre-selection criterion of arguments, called maximal specificity. The criterion establishes that an argument will be considered like maximally specific only if, for every argument based on more specific evidence which does not explain the same (...)
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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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  • GORGIAS: Applying argumentation.Antonis C. Kakas, Pavlos Moraitis & Nikolaos I. Spanoudakis - 2018 - Argument and Computation 10 (1):55-81.
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  • An argument-based approach to reasoning with specificity.Phan Minh Dung & Tran Cao Son - 2001 - Artificial Intelligence 133 (1-2):35-85.
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  • Making the right exceptions.Harald Bastiaanse & Frank Veltman - 2016 - Artificial Intelligence 238:96-118.
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  • A sceptical theory of inheritance in nonmonotonic semantic networks.John F. Horty, Richmond H. Thomason & David S. Touretzky - 1990 - Artificial Intelligence 42 (2-3):311-348.
    inheritance reasoning in semantic networks allowing for multiple inheritance with exceptions. The approach leads to a definition of iaheritance that is..
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  • Is default logic a reinvention of inductive-statistical reasoning?Yao-Hua Tan - 1997 - Synthese 110 (3):357-379.
    Currently there is hardly any connection between philosophy of science and Artificial Intelligence research. We argue that both fields can benefit from each other. As an example of this mutual benefit we discuss the relation between Inductive-Statistical Reasoning and Default Logic. One of the main topics in AI research is the study of common-sense reasoning with incomplete information. Default logic is especially developed to formalise this type of reasoning. We show that there is a striking resemblance between inductive-statistical reasoning and (...)
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  • Currents in connectionism.William Bechtel - 1993 - Minds and Machines 3 (2):125-153.
    This paper reviews four significant advances on the feedforward architecture that has dominated discussions of connectionism. The first involves introducing modularity into networks by employing procedures whereby different networks learn to perform different components of a task, and a Gating Network determines which network is best equiped to respond to a given input. The second consists in the use of recurrent inputs whereby information from a previous cycle of processing is made available on later cycles. The third development involves developing (...)
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  • A theory of nonmonotonic inheritance based on annotated logic.Krishnaprasad Thirunarayan & Michael Kifer - 1993 - Artificial Intelligence 60 (1):23-50.
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  • Impediments to universal preference-based default theories.Jon Doyle & Michael P. Wellman - 1991 - Artificial Intelligence 49 (1-3):97-128.
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  • Defeasible inheritance systems and reactive diagrams.Dov Gabbay - 2008 - Logic Journal of the IGPL 17 (1):1-54.
    Inheritance diagrams are directed acyclic graphs with two types of connections between nodes: x → y and x ↛ y . Given a diagram D, one can ask the formal question of “is there a valid path between node x and node y?” Depending on the existence of a valid path we can answer the question “x is a y” or “x is not a y”. The answer to the above question is determined through a complex inductive algorithm on paths (...)
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  • Dynamic reasoning with qualified syllogisms.Daniel G. Schwartz - 1997 - Artificial Intelligence 93 (1-2):103-167.
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  • How Category Selection Impacts Inference Reliability: Inheritance Inference From an Ecological Perspective.Paul D. Thorn & Gerhard Schurz - 2021 - Cognitive Science 45 (4):e12971.
    This article presents results from a simulation‐based study of inheritance inference, that is, inference from the typicality of a property among a “base” class to its typicality among a subclass of the class. The study aims to ascertain which kinds of inheritance inferences are reliable, with attention to the dependence of their reliability upon the type of environment in which inferences are made. For example, the study addresses whether inheritance inference is reliable in the case of “exceptional subclasses” (i.e., subclasses (...)
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  • Which are the true defeasible logics?Michael J. Maher - forthcoming - Journal of Applied Non-Classical Logics:1-29.
    The class of defeasible logics is only vaguely defined – it is defined by a few exemplars and the general idea of efficient reasoning with defeasible rules. The recent definition of the defeasible logic DL(∂||) introduced new features to such logics, which have repercussions that we explore. In particular, we define a class of logics that accommodates the new logic while retaining the traditional properties of defeasible logics.
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  • Nonmonotonic Inconsistency.Charles B. Cross - 2003 - Artificial Intelligence 149 (2):161-178.
    Nonmonotonic consequence is the subject of a vast literature, but the idea of a nonmonotonic counterpart of logical inconsistency—the idea of a defeasible property representing internal conflict of an inductive or evidential nature—has been entirely neglected. After considering and dismissing two possible analyses relating nonmonotonic consequence and a nonmonotonic counterpart of logical inconsistency, this paper offers a set of postulates for nonmonotonic inconsistency, an analysis of nonmonotonic inconsistency in terms of nonmonotonic consequence, and a series of results showing that nonmonotonic (...)
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  • Defeasible inheritance on cyclic networks.Gian Aldo Antonelli - 1997 - Artificial Intelligence 92 (1-2):1-23.
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