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  1. Moving beyond content‐specific computation in artificial neural networks.Nicholas Shea - 2021 - Mind and Language 38 (1):156-177.
    A basic deep neural network (DNN) is trained to exhibit a large set of input–output dispositions. While being a good model of the way humans perform some tasks automatically, without deliberative reasoning, more is needed to approach human‐like artificial intelligence. Analysing recent additions brings to light a distinction between two fundamentally different styles of computation: content‐specific and non‐content‐specific computation (as first defined here). For example, deep episodic RL networks draw on both. So does human conceptual reasoning. Combining the two takes (...)
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  • Representation in Cognitive Science by Nicholas Shea: Reply by the Author.Nicholas Shea - 2022 - Studies in History and Philosophy of Science Part A 92 (C):270-273.
    It is a rare privilege to have such eminent and insightful reviewers. Their kind words about the book are much appreciated – perhaps more than they realise. And I'm grateful to all three for having read the book so constructively. Each has given me several things to think about. In the space available here I will focus on the objections that seem most critical. Robert Rupert argues that I rely on an overly narrow understanding of what the cognitive sciences explain (...)
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  • Model-free metacognition.Peter Carruthers & David M. Williams - 2022 - Cognition 225 (C):105117.
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