Citations of work:

Nir Fresco (2012). The Explanatory Role of Computation in Cognitive Science.

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  1.  42
    Mechanistic and Non-Mechanistic Varieties of Dynamical Models in Cognitive Science: Explanatory Power, Understanding, and the ‘Mere Description’ Worry.Raoul Gervais - 2015 - Synthese 192 (1):43-66.
    In the literature on dynamical models in cognitive science, two issues have recently caused controversy. First, what is the relation between dynamical and mechanistic models? I will argue that dynamical models can be upgraded to be mechanistic as well, and that there are mechanistic and non-mechanistic dynamical models. Second, there is the issue of explanatory power. Since it is uncontested the mechanistic models can explain, I will focus on the non-mechanistic variety of dynamical models. It is often claimed by proponents (...)
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  2.  15
    The Systematicity Challenge to Anti-Representational Dynamicism.Víctor Verdejo - 2015 - Synthese 192 (3):701-722.
    After more than twenty years of representational debate in the cognitive sciences, anti-representational dynamicism may be seen as offering a rival and radically new kind of explanation of systematicity phenomena. In this paper, I argue that, on the contrary, anti-representational dynamicism must face a version of the old systematicity challenge: either it does not explain systematicity, or else, it is just an implementation of representational theories. To show this, I present a purely behavioral and representation-free account of systematicity. I then (...)
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  3.  59
    Distributed Cognition in Scientific Contexts.Hyundeuk Cheon - 2014 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 45 (1):23-33.
    Even though it has been argued that scientific cognition is distributed, there is no consensus on the exact nature of distributed cognition. This paper aims to characterize distributed cognition as appropriate for philosophical studies of science. I first classify competing characterizations into three types: the property approach, the task approach, and the system approach. It turns out that the property approach and the task approach are subject to criticism. I then argue that the most preferable way to understand distributed cognition (...)
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  4.  31
    Does Computation Reveal Machine Cognition?Prakash Mondal - 2014 - Biosemiotics 7 (1):97-110.
    This paper seeks to understand machine cognition. The nature of machine cognition has been shrouded in incomprehensibility. We have often encountered familiar arguments in cognitive science that human cognition is still faintly understood. This paper will argue that machine cognition is far less understood than even human cognition despite the fact that a lot about computer architecture and computational operations is known. Even if there have been putative claims about the transparency of the notion of machine computations, these claims do (...)
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    The Thermodynamic Cost of Fast Thought.Alexandre Castro - 2013 - Minds and Machines 23 (4):473-487.
  6.  22
    The Thermodynamic Cost of Fast Thought.Alexandre de Castro - 2013 - Minds and Machines 23 (4):473-487.