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  1. Reasoning with Concepts: A Unifying Framework.Peter Gärdenfors & Matías Osta-Vélez - 2023 - Minds and Machines 1 (3):451-485.
    Over the past few decades, cognitive science has identified several forms of reasoning that make essential use of conceptual knowledge. Despite significant theoretical and empirical progress, there is still no unified framework for understanding how concepts are used in reasoning. This paper argues that the theory of conceptual spaces is capable of filling this gap. Our strategy is to demonstrate how various inference mechanisms which clearly rely on conceptual information—including similarity, typicality, and diagnosticity-based reasoning—can be modeled using principles derived from (...)
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  • Reasoning with Expectations About Causal Relations.Peter Gärdenfors - 2022 - Studies in Logic, Grammar and Rhetoric 67 (1):201-217.
    Reasoning is not just following logical rules, but a large part of human reasoning depends on our expectations about the world. To some extent, non-monotonic logic has been developed to account for the role of expectations. In this article, the focus is on expectations based on actions and their consequences. The analysis is based on a two-vector model of events where an event is represented in terms of two main components – the force of an action that drives the event, (...)
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  • Categories and induction in young children.Susan A. Gelman & Ellen M. Markman - 1986 - Cognition 23 (3):183-209.
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  • Incremental Bayesian Category Learning From Natural Language.Lea Frermann & Mirella Lapata - 2016 - Cognitive Science 40 (6):1333-1381.
    Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words. We present a Bayesian model that, unlike previous work, learns both categories and their features in a single process. We model category induction as two interrelated subproblems: the acquisition of features that discriminate among categories, and the grouping of concepts into categories based on those features. (...)
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  • Developmental Changes in Strategies for Gathering Evidence About Biological Kinds.Emily Foster-Hanson, Kelsey Moty, Amanda Cardarelli, John Daryl Ocampo & Marjorie Rhodes - 2020 - Cognitive Science 44 (5):e12837.
    How do people gather samples of evidence to learn about the world? Adults often prefer to sample evidence from diverse sources—for example, choosing to test a robin and a turkey to find out if something is true of birds in general. Children below age 9, however, often do not consider sample diversity, instead treating non‐diverse samples (e.g., two robins) and diverse samples as equivalently informative. The current study (N = 247) found that this discontinuity stems from developmental changes in standards (...)
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  • Meaning and reference from a probabilistic point of view.Jacob Feldman & Lee-Sun Choi - 2022 - Cognition 223 (C):105058.
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  • On seeing human: A three-factor theory of anthropomorphism.Nicholas Epley, Adam Waytz & John T. Cacioppo - 2007 - Psychological Review 114 (4):864-886.
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  • A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge.Darren J. Edwards, Ciara McEnteggart & Yvonne Barnes-Holmes - 2022 - Frontiers in Psychology 13.
    Psychology has benefited from an enormous wealth of knowledge about processes of cognition in relation to how the brain organizes information. Within the categorization literature, this behavior is often explained through theories of memory construction called exemplar theory and prototype theory which are typically based on similarity or rule functions as explanations of how categories emerge. Although these theories work well at modeling highly controlled stimuli in laboratory settings, they often perform less well outside of these settings, such as explaining (...)
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  • The Logic of Plausible Reasoning: A Core Theory.Allan Collins & Ryszard Michalski - 1989 - Cognitive Science 13 (1):1-49.
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  • Does rank have its privilege? Inductive inferences within folkbiological taxonomies.John D. Coley, Douglas L. Medin & Scott Atran - 1997 - Cognition 64 (1):73-112.
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  • Generic Statements Require Little Evidence for Acceptance but Have Powerful Implications.Andrei Cimpian, Amanda C. Brandone & Susan A. Gelman - 2010 - Cognitive Science 34 (8):1452-1482.
    Generic statements (e.g., “Birds lay eggs”) express generalizations about categories. In this paper, we hypothesized that there is a paradoxical asymmetry at the core of generic meaning, such that these sentences have extremely strong implications but require little evidence to be judged true. Four experiments confirmed the hypothesized asymmetry: Participants interpreted novel generics such as “Lorches have purple feathers” as referring to nearly all lorches, but they judged the same novel generics to be true given a wide range of prevalence (...)
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  • Metaphoric structuring: understanding time through spatial metaphors.Lera Boroditsky - 2000 - Cognition 75 (1):1-28.
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  • Access and inference in categorization.Lawrence W. Barsalou - 1990 - Bulletin of the Psychonomic Society 28 (3):268-271.
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  • A Mammal That Is Not an Animal? Naming and the Animal Concept in English and Indonesian Speakers.Florencia K. Anggoro - 2012 - Journal of Cognition and Culture 12 (1-2):31-48.
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  • Inference and the structure of concepts.Matías Osta Vélez - 2020 - Dissertation, Ludwig Maximilians Universität, München
    This thesis studies the role of conceptual content in inference and reasoning. The first two chapters offer a theoretical and historical overview of the relation between inference and meaning in philosophy and psychology. In particular, a critical analysis of the formality thesis, i.e., the idea that rational inference is a rule-based and topic-neutral mechanism, is advanced. The origins of this idea in logic and its influence in philosophy and cognitive psychology are discussed. Chapter 3 consists of an analysis of the (...)
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  • Category-based induction in conceptual spaces.Matías Osta-Vélez & Peter Gärdenfors - 2020 - Journal of Mathematical Psychology 96.
    Category-based induction is an inferential mechanism that uses knowledge of conceptual relations in order to estimate how likely is for a property to be projected from one category to another. During the last decades, psychologists have identified several features of this mechanism, and they have proposed different formal models of it. In this article; we propose a new mathematical model for category-based induction based on distances on conceptual spaces. We show how this model can predict most of the properties of (...)
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  • The Oxford Handbook of Causal Reasoning.Michael Waldmann (ed.) - 2017 - Oxford, England: Oxford University Press.
    Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...)
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  • Intuitive And Reflective Responses In Philosophy.Nick Byrd - 2014 - Dissertation, University of Colorado
    Cognitive scientists have revealed systematic errors in human reasoning. There is disagreement about what these errors indicate about human rationality, but one upshot seems clear: human reasoning does not seem to fit traditional views of human rationality. This concern about rationality has made its way through various fields and has recently caught the attention of philosophers. The concern is that if philosophers are prone to systematic errors in reasoning, then the integrity of philosophy would be threatened. In this paper, I (...)
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  • The Epistemology of Geometry I: the Problem of Exactness.Anne Newstead & Franklin James - 2010 - Proceedings of the Australasian Society for Cognitive Science 2009.
    We show how an epistemology informed by cognitive science promises to shed light on an ancient problem in the philosophy of mathematics: the problem of exactness. The problem of exactness arises because geometrical knowledge is thought to concern perfect geometrical forms, whereas the embodiment of such forms in the natural world may be imperfect. There thus arises an apparent mismatch between mathematical concepts and physical reality. We propose that the problem can be solved by emphasizing the ways in which the (...)
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  • Can similarity-based models of induction handle negative evidence.Daniel Heussen, Wouter Voorspoels & Gert Storms - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 2033--2038.
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  • From similarity to chance.Daniel Osherson - manuscript
    “In reality, all arguments from experience are founded on the similarity which we discover among natural objects, and by which we are induced to expect effects similar to those which we have found to follow from such objects. ... From causes which appear similar we expect similar effects.”.
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