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  1. Bootstrapping Concepts via Hybridization: A Step-by-step Guide.Matteo De Benedetto & Nina Poth - forthcoming - Review of Philosophy and Psychology.
    Carey’s (2009) account of bootstrapping in developmental psychology has been criticized out of a lack of theoretical precision and because of its alleged circularity (Rips et al. 2013, Cognition 128 (3): 320–330; Fodor 2010, Times Literary Supplement, 7–8; Rey 2014, Mind & Language 29 (2): 109–132). In this paper, we respond to these criticisms by connecting the debate on bootstrapping with recent accounts of conceptual creativity in philosophy of science. Specifically, we build on Nersessian’s (2010) hybrid-models-based theory of scientific conceptual (...)
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  • Deep Learning Applied to Scientific Discovery: A Hot Interface with Philosophy of Science.Louis Vervoort, Henry Shevlin, Alexey A. Melnikov & Alexander Alodjants - 2023 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 54 (2):339-351.
    We review publications in automated scientific discovery using deep learning, with the aim of shedding light on problems with strong connections to philosophy of science, of physics in particular. We show that core issues of philosophy of science, related, notably, to the nature of scientific theories; the nature of unification; and of causation loom large in scientific deep learning. Therefore, advances in deep learning could, and ideally should, have impact on philosophy of science, and vice versa. We suggest lines of (...)
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  • Criteria for naturalness in conceptual spaces.Corina Strößner - 2022 - Synthese 200 (2):1-36.
    Conceptual spaces are a frequently applied framework for representing concepts. One of its central aims is to find criteria for what makes a concept natural. A prominent demand is that natural concepts cover convex regions in conceptual spaces. The first aim of this paper is to analyse the convexity thesis and the arguments that have been advanced in its favour or against it. Based on this, I argue that most supporting arguments focus on single-domain concepts (e.g., colours, smells, shapes). Unfortunately, (...)
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