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  1. Naturalising Representational Content.Nicholas Shea - 2013 - Philosophy Compass 8 (5):496-509.
    This paper sets out a view about the explanatory role of representational content and advocates one approach to naturalising content – to giving a naturalistic account of what makes an entity a representation and in virtue of what it has the content it does. It argues for pluralism about the metaphysics of content and suggests that a good strategy is to ask the content question with respect to a variety of predictively successful information processing models in experimental psychology and cognitive (...)
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  • The Philosophy of Generative Linguistics.Peter Ludlow - 2011 - Oxford, GB: Oxford University Press.
    Peter Ludlow presents the first book on the philosophy of generative linguistics, including both Chomsky's government and binding theory and his minimalist ...
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  • Semantic externalism and the mechanics of thought.Carrie Figdor - 2009 - Minds and Machines 19 (1):1-24.
    I review a widely accepted argument to the conclusion that the contents of our beliefs, desires and other mental states cannot be causally efficacious in a classical computational model of the mind. I reply that this argument rests essentially on an assumption about the nature of neural structure that we have no good scientific reason to accept. I conclude that computationalism is compatible with wide semantic causal efficacy, and suggest how the computational model might be modified to accommodate this possibility.
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  • Computational modeling vs. computational explanation: Is everything a Turing machine, and does it matter to the philosophy of mind?Gualtiero Piccinini - 2007 - Australasian Journal of Philosophy 85 (1):93 – 115.
    According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.
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  • Computers.Gualtiero Piccinini - 2008 - Pacific Philosophical Quarterly 89 (1):32–73.
    I offer an explication of the notion of computer, grounded in the practices of computability theorists and computer scientists. I begin by explaining what distinguishes computers from calculators. Then, I offer a systematic taxonomy of kinds of computer, including hard-wired versus programmable, general-purpose versus special-purpose, analog versus digital, and serial versus parallel, giving explicit criteria for each kind. My account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system's mechanistic (...)
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  • Computation without representation.Gualtiero Piccinini - 2008 - Philosophical Studies 137 (2):205-241.
    The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...)
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  • The computational theory of mind.Steven Horst - 2005 - Stanford Encyclopedia of Philosophy.
    Over the past thirty years, it is been common to hear the mind likened to a digital computer. This essay is concerned with a particular philosophical view that holds that the mind literally is a digital computer (in a specific sense of “computer” to be developed), and that thought literally is a kind of computation. This view—which will be called the “Computational Theory of Mind” (CTM)—is thus to be distinguished from other and broader attempts to connect the mind with computation, (...)
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  • How to Explain Miscomputation.Chris Tucker - 2018 - Philosophers' Imprint 18:1-17.
    Just as theory of representation is deficient if it can’t explain how misrepresentation is possible, a theory of computation is deficient if it can’t explain how miscomputation is possible. Nonetheless, philosophers have generally ignored miscomputation. My primary goal in this paper is to clarify both what miscomputation is and how to adequately explain it. Miscomputation is a special kind of malfunction: a system miscomputes when it computes in a way that it shouldn’t. To explain miscomputation, you must provide accounts of (...)
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  • In defense of the semantic view of computation.Oron Shagrir - 2020 - Synthese 197 (9):4083-4108.
    The semantic view of computation is the claim that semantic properties play an essential role in the individuation of physical computing systems such as laptops and brains. The main argument for the semantic view rests on the fact that some physical systems simultaneously implement different automata at the same time, in the same space, and even in the very same physical properties. Recently, several authors have challenged this argument. They accept the premise of simultaneous implementation but reject the semantic conclusion. (...)
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  • Representation in Cognitive Science.Nicholas Shea - 2018 - Oxford University Press.
    How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.
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  • Extensive enactivism: why keep it all in?Daniel D. Hutto, Michael D. Kirchhoff & Erik Myin - 2014 - Frontiers in Human Neuroscience 8 (706):102178.
    Radical enactive and embodied approaches to cognitive science oppose the received view in the sciences of the mind in denying that cognition fundamentally involves contentful mental representation. This paper argues that the fate of representationalism in cognitive science matters significantly to how best to understand the extent of cognition. It seeks to establish that any move away from representationalism toward pure, empirical functionalism fails to provide a substantive “mark of the cognitive” and is bereft of other adequate means for individuating (...)
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  • (1 other version)1. Marr on Computational-Level Theories Marr on Computational-Level Theories (pp. 477-500).Oron Shagrir, John D. Norton, Holger Andreas, Jouni-Matti Kuukkanen, Aris Spanos, Eckhart Arnold, Elliott Sober, Peter Gildenhuys & Adela Helena Roszkowski - 2010 - Philosophy of Science 77 (4):477-500.
    According to Marr, a computational-level theory consists of two elements, the what and the why. This article highlights the distinct role of the Why element in the computational analysis of vision. Three theses are advanced: that the Why element plays an explanatory role in computational-level theories, that its goal is to explain why the computed function is appropriate for a given visual task, and that the explanation consists in showing that the functional relations between the representing cells are similar to (...)
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  • Against Structuralist Theories of Computational Implementation.Michael Rescorla - 2013 - British Journal for the Philosophy of Science 64 (4):681-707.
    Under what conditions does a physical system implement or realize a computation? Structuralism about computational implementation, espoused by Chalmers and others, holds that a physical system realizes a computation just in case the system instantiates a pattern of causal organization isomorphic to the computation’s formal structure. I argue against structuralism through counter-examples drawn from computer science. On my opposing view, computational implementation sometimes requires instantiating semantic properties that outstrip any relevant pattern of causal organization. In developing my argument, I defend (...)
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  • Alternative individualism.Denis M. Walsh - 1999 - Philosophy of Science 66 (4):628-648.
    Psychological individualism is motivated by two taxonomic principles: (i) that psychological states are individuated by their causal powers, and (ii) that causal powers supervene upon intrinsic physiological state. I distinguish two interpretations of individualism--the 'orthodox' and the 'alternative'--each of which is consistent with these motivating principles. I argue that the alternative interpretation is legitimately individualistic on the grounds that it accurately reflects the actual taxonomic practices of bona fide individualistic sciences. The classification of homeobox genes in developmental genetics provides an (...)
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  • Computation in physical systems.Gualtiero Piccinini - 2010 - Stanford Encyclopedia of Philosophy.
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  • Content, Computation and Externalism.Christopher Peacocke - 1995 - Philosophical Issues 6:227-264.
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  • The Mind as Neural Software? Understanding Functionalism, Computationalism, and Computational Functionalism.Gualtiero Piccinini - 2010 - Philosophy and Phenomenological Research 81 (2):269-311.
    Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...)
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