Weinberger, Naftali and Allen, Colin (2021) Static-Dynamic Hybridity in Dynamical Models of Cognition. [Preprint]

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Abstract

Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static or purely dynamic, but rather using a hybrid approach. This hybridity reveals why dynamical models should not be understood as providing unstructured descriptions of a system's dynamics, and is important for understanding the relationship between dynamical and non-dynamical representations of a system.

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Item Type:	Preprint
Creators:	Creators Email ORCID Weinberger, Naftali naftali.weinberger@gmail.com Allen, Colin colin.allen@pitt.edu
Keywords:	dynamical systems, cognitive science, computation, models
Subjects:	General Issues > Causation Specific Sciences > Cognitive Science Specific Sciences > Cognitive Science > Computation General Issues > Models and Idealization
Depositing User:	Mr. Naftali Weinberger
Date Deposited:	19 Feb 2021 16:17
Last Modified:	19 Feb 2021 16:17
Item ID:	18730
Subjects:	General Issues > Causation Specific Sciences > Cognitive Science Specific Sciences > Cognitive Science > Computation General Issues > Models and Idealization
Date:	6 January 2021
URI:	https://philsci-archive.pitt.edu/id/eprint/18730

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• Static-Dynamic Hybridity in Dynamical Models of Cognition. (deposited 07 Jan 2021 20:14)

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