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Teleosemantics, Structural Resemblance and Predictive Processing

Pain, Ross and Mann, Stephen Francis (2024) Teleosemantics, Structural Resemblance and Predictive Processing. [Preprint]

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Abstract

We propose a pluralist account of content for predictive processing systems. Our pluralism combines Millikan’s teleosemantics with existing structural resemblance
accounts. The paper has two goals. First, we outline how a teleosemantic treatment of signal passing in predictive processing systems would work, and how it integrates with
structural resemblance accounts. We show that the core explanatory motivations and conceptual machinery of teleosemantics and predictive processing mesh together well.
Second, we argue this pluralist approach expands the range of empirical cases to which the predictive processing framework might be successfully applied. This
because our pluralism is practice-oriented. A range of different notions of content are used in the cognitive sciences to explain behaviour, and some of these cases look to employ teleosemantic notions. As a result, our pluralism gives predictive processing the scope to cover these cases.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Pain, Ross0000-0002-5354-6301
Mann, Stephen Francisstephenfmann@gmail.com0000-0002-4136-8595
Keywords: Predictive processing; representation; teleosemantics; structural resemblance; pluralism
Subjects: Specific Sciences > Cognitive Science > Action
Specific Sciences > Neuroscience > Cognitive Neuroscience
Specific Sciences > Cognitive Science > Concepts and Representations
Specific Sciences > Cognitive Science > Perception
Depositing User: Dr Ross Pain
Date Deposited: 16 May 2024 10:54
Last Modified: 16 May 2024 10:54
Item ID: 23440
Subjects: Specific Sciences > Cognitive Science > Action
Specific Sciences > Neuroscience > Cognitive Neuroscience
Specific Sciences > Cognitive Science > Concepts and Representations
Specific Sciences > Cognitive Science > Perception
Date: 2024
URI: https://philsci-archive.pitt.edu/id/eprint/23440

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