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  1. Can Multiple Realisation be Explained?Alexander Franklin - 2021 - Philosophy 96 (1):27-48.
    Multiple realisation prompts the question: how is it that multiple systems all exhibit the same phenomena despite their different underlying properties? In this paper I develop a framework for addressing that question and argue that multiple realisation can be reductively explained. I illustrate this position by applying the framework to a simple example – the multiple realisation of electrical conductivity. I defend my account by addressing potential objections:contra Polger and Shapiro, Batterman, and Sober, I claim that multiple realisation is commonplace, (...)
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  • Explanations in cognitive science: unification versus pluralism.Marcin Miłkowski & Mateusz Hohol - 2020 - Synthese 199 (Suppl 1):1-17.
    The debate between the defenders of explanatory unification and explanatory pluralism has been ongoing from the beginning of cognitive science and is one of the central themes of its philosophy. Does cognitive science need a grand unifying theory? Should explanatory pluralism be embraced instead? Or maybe local integrative efforts are needed? What are the advantages of explanatory unification as compared to the benefits of explanatory pluralism? These questions, among others, are addressed in this Synthese’s special issue. In the introductory paper, (...)
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  • Some reflections on Robert Batterman's a middle way.James Woodward - 2024 - Studies in History and Philosophy of Science Part A 106 (C):21-30.
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  • Energy Requirements Undermine Substrate Independence and Mind-Body Functionalism.Paul Thagard - 2022 - Philosophy of Science 89 (1):70-88.
    Substrate independence and mind-body functionalism claim that thinking does not depend on any particular kind of physical implementation. But real-world information processing depends on energy, and energy depends on material substrates. Biological evidence for these claims comes from ecology and neuroscience, while computational evidence comes from neuromorphic computing and deep learning. Attention to energy requirements undermines the use of substrate independence to support claims about the feasibility of artificial intelligence, the moral standing of robots, the possibility that we may be (...)
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