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  1. Pragmatic a Priori Knowledge: A Pragmatic Approach to the Nature and Object of What Can Be Known Independently of Experience.Lauri Järvilehto - 2011 - Jyväskylä University Printing House.
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  • Discrete Thoughts: Why Cognition Must Use Discrete Representations.Eric Dietrich & Arthur B. Markman - 2003 - Mind and Language 18 (1):95-119.
    Advocates of dynamic systems have suggested that higher mental processes are based on continuous representations. In order to evaluate this claim, we first define the concept of representation, and rigorously distinguish between discrete representations and continuous representations. We also explore two important bases of representational content. Then, we present seven arguments that discrete representations are necessary for any system that must discriminate between two or more states. It follows that higher mental processes require discrete representations. We also argue that discrete (...)
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  • Frameworks, Models, and Case Studies: A New Methodology for Studying Conceptual Change in Science and Philosophy.Matteo De Benedetto - 2022 - Dissertation, Ludwig Maximilians Universität, München
    This thesis focuses on models of conceptual change in science and philosophy. In particular, I developed a new bootstrapping methodology for studying conceptual change, centered around the formalization of several popular models of conceptual change and the collective assessment of their improved formal versions via nine evaluative dimensions. Among the models of conceptual change treated in the thesis are Carnap’s explication, Lakatos’ concept-stretching, Toulmin’s conceptual populations, Waismann’s open texture, Mark Wilson’s patches and facades, Sneed’s structuralism, and Paul Thagard’s conceptual revolutions. (...)
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  • Combining Social Concepts: The Role of Causal Reasoning.Ziva Kunda, Dale T. Miller & Theresa Claire - 1990 - Cognitive Science 14 (4):551-577.
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  • Combining Prototypes: A Selective Modification Model.Edward E. Smith, Daniel N. Osherson, Lance J. Rips & Margaret Keane - 1988 - Cognitive Science 12 (4):485-527.
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  • Comprehending Complex Concepts.Gregory L. Murphy - 1988 - Cognitive Science 12 (4):529-562.
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  • The AHA! Experience: Creativity Through Emergent Binding in Neural Networks.Paul Thagard & Terrence C. Stewart - 2011 - Cognitive Science 35 (1):1-33.
    Many kinds of creativity result from combination of mental representations. This paper provides a computational account of how creative thinking can arise from combining neural patterns into ones that are potentially novel and useful. We defend the hypothesis that such combinations arise from mechanisms that bind together neural activity by a process of convolution, a mathematical operation that interweaves structures. We describe computer simulations that show the feasibility of using convolution to produce emergent patterns of neural activity that can support (...)
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  • The Current Status of Research on Concept Combination.Lance J. Rips - 1995 - Mind and Language 10 (1-2):72-104.
  • Polysemy and Thought: Toward a Generative Theory of Concepts.Jake Quilty-Dunn - 2021 - Mind and Language 36 (1):158-185.
    Most theories of concepts take concepts to be structured bodies of information used in categorization and inference. This paper argues for a version of atomism, on which concepts are unstructured symbols. However, traditional Fodorian atomism is falsified by polysemy and fails to provide an account of how concepts figure in cognition. This paper argues that concepts are generative pointers, that is, unstructured symbols that point to memory locations where cognitively useful bodies of information are stored and can be deployed to (...)
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  • Thinking May Be More Than Computing.Peter Kugel - 1986 - Cognition 22 (2):137-198.
  • Concepts and Nativism.Nicholas Adamson - unknown
    Jerry Fodor has argued that virtually all lexical concepts are innate. I argue against this position, but not, as other have done, on the grounds that the arguments against lexical decomposition upon which Fodor relies are flawed. Rather, I argue that even if lexical concepts cannot be decomposed, the possession conditions for having lexical concepts are nonetheless not innately satisfied.
     
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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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  • A Multiple Definitions Model of Classification Into Fuzzy Categories.Thomas M. Gruenenfelder - 2019 - Frontiers in Psychology 10.
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  • On the Nature and Scope of Featural Representations of Word Meaning.Ken McRae, Virginia R. de Sa & Mark S. Seidenberg - 1997 - Journal of Experimental Psychology 126 (2):99-130.
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  • Many Reasons or Just One: How Response Mode Affects Reasoning in the Conjunction Problem.Ralph Hertwig Valerie M. Chase - 1998 - Thinking and Reasoning 4 (4):319 – 352.
    Forty years of experimentation on class inclusion and its probabilistic relatives have led to inconsistent results and conclusions about human reasoning. Recent research on the conjunction "fallacy" recapitulates this history. In contrast to previous results, we found that a majority of participants adhere to class inclusion in the classic Linda problem. We outline a theoretical framework that attributes the contradictory results to differences in statistical sophistication and to differences in response mode-whether participants are asked for probability estimates or ranks-and propose (...)
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  • Conceptual Complexity and the Bias/Variance Tradeoff.Erica Briscoe & Jacob Feldman - 2011 - Cognition 118 (1):2-16.
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  • “Prototypes” and “Fuzziness” in the Logic of Concepts.Gy Fuhrmann - 1988 - Synthese 75 (3):317 - 347.
    Prototypes and fuzziness are regarded in this paper as fundamental phenomena in the inherent logic of concepts whose relationship, however, has not been sufficiently clarified. Therefore, modifications are proposed in the definition of both. Prototypes are defined as the elements possessing maximal degree of membership in the given category such thatthis membership has maximal cognitive efficiency in representing theelement. A modified fuzzy set (m-fuzzy set) is defined on aclass (possibly self-contradictory collection) such that its core (the collection of elements with (...)
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  • Note on the Integration of Prototype Theory and Fuzzy-Set Theory.Gy Fuhrmann - 1991 - Synthese 86 (1):1 - 27.
    Many criticisms of prototype theory and/or fuzzy-set theory are based on the assumption that category representativeness (or typicality) is identical with fuzzy membership. These criticisms also assume that conceptual combination and logical rules (all in the Aristotelian sense) are the appropriate criteria for the adequacy of the above “fuzzy typicality”. The present paper discusses these assumptions following the line of their most explicit and most influential expression by Osheron and Smith (1981). Several arguments are made against the above identification, the (...)
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  • A Description Logic Framework for Commonsense Conceptual Combination Integrating Typicality, Probabilities and Cognitive Heuristics.Antonio Lieto & Gian Luca Pozzato - 2019 - Journal of Experimental and Theoretical Artificial Intelligence:1-39.
    We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of the combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC + TR, whose semantics is based on the notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and is equipped with a cognitive heuristic used by humans for concept composition. We first extend the logic of typicality ALC + TR by typicality inclusions of the (...)
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  • Beyond Subgoaling: A Dynamic Knowledge Generation Framework for Creative Problem Solving in Cognitive Architectures.Antonio Lieto - 2019 - Cognitive Systems Research 58:305-316.
    In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for the (...)
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  • Hierarchical Conceptual Spaces for Concept Combination.Martha Lewis & Jonathan Lawry - 2016 - Artificial Intelligence 237:204-227.
  • Compounding as Abstract Operation in Semantic Space: Investigating Relational Effects Through a Large-Scale, Data-Driven Computational Model.Marco Marelli, Christina L. Gagné & Thomas L. Spalding - 2017 - Cognition 166:207-224.
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  • On Typicality and Vagueness.Daniel Osherson & Edward E. Smith - 1997 - Cognition 64 (2):189-206.
  • Some Origins of Belief.Daniel N. Osherson, Edward E. Smith & Eldar B. Shafir - 1986 - Cognition 24 (3):197-224.
  • Do health professionals have a prototype concept of disease? The answer is no.Bjørn Hofmann - 2017 - Philosophy, Ethics, and Humanities in Medicine 2017 12:1 12 (1):6.
    Health and disease are core concepts in health care and have attracted substantial interest and controversy. In recent and interesting contributions to the debate it has been argued that the challenges with the concept of disease can be resolved by a prototype concept of disease. As a robin is a more prototypical of a bird than a penguin, some diseases are more prototypical than others. If disease is a prototype concept, it would change nosology, but also health care and the (...)
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  • Fuzziness of Concepts and Concepts of Fuzziness.Gy Fuhrmann - 1988 - Synthese 75 (3):349 - 372.
    It has been a vexing question in recent years whether concepts are fuzzy. In this paper several views on the fuzziness of concepts are pointed out to have stemmed from dubious concepts of fuzziness. The underlying notions of the roles feasibly played byprototype, set, andprobability in modeling concepts strongly suggest that the controversy originates from a vague relation between intuitive and mathematical ideas in the cognitive sciences. It is argued that the application of fuzzy sets cannot resolve this vagueness since (...)
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  • The Red Herring and the Pet Fish: Why Concepts Still Can't Be Prototypes.Jerry A. Fodor & Ernest Lepore - 1996 - Cognition 58 (2):253-70.
    1 There is a Standard Objection to the idea that concepts might be prototypes (or exemplars, or stereotypes): Because they are productive, concepts must be compositional. Prototypes aren't compositional, so concepts can't be prototypes (see, e.g., Margolis, 1994).2 However, two recent papers (Osherson and Smith, 1988; Kamp and Partee, 1995) reconsider this consensus. They suggest that, although the Standard Objection is probably right in the long run, the cases where prototypes fail to exhibit compositionality are relatively exotic and involve phenomena (...)
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