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Predictive coding and representationalism

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dc.contributor.author Gładziejewski, Paweł
dc.date.accessioned 2018-11-06T10:04:08Z
dc.date.available 2018-11-06T10:04:08Z
dc.date.issued 2016-02
dc.identifier.citation Synthese vol. 193, issue 2, 2016, pp. 559 - 582
dc.identifier.other DOI:10.1007/s11229-015-0762-9
dc.identifier.uri http://repozytorium.umk.pl/handle/item/5468
dc.description.abstract According to the predictive coding theory of cognition (PCT), brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, in the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system.
dc.language.iso eng
dc.publisher Springer
dc.rights info:eu-repo/semantics/openAccess
dc.subject generative models
dc.subject representationalism
dc.subject structural representation
dc.subject predictive coding
dc.subject predictive processing
dc.subject mental representation
dc.title Predictive coding and representationalism
dc.type info:eu-repo/semantics/article


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