Model-Based Approaches to Active Perception and Control
G. Pezzulo, Francesco Donnarumma, P. Iodice, D. Maisto, Ivilin Peev Stoianov
Entropy June 9, 2017 DOI: 10.3390/e19060266 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Argues that an explicitly inferential framework, such as predictive processing with internal generative models, can capture key aspects of embodied and enactive theories of cognition; that computational and dynamical accounts can be reconciled rather than seen as alternative explanations; and that phenomena like planning and imagination, which can be puzzling for enactive and non-representational perspectives, are captured well by internal generative models and predictive processing. |
Abstract
There is an on-going debate in cognitive (neuro) science and philosophy between classical cognitive theory and embodied, embedded, extended, and enactive (“4-Es”) views of cognition—a family of theories that emphasize the role of the body in cognition and the importance of brain-body-environment interaction over and above internal representation. This debate touches foundational issues, such as whether the brain internally represents the external environment, and “infers” or “computes” something. Here we focus on two (4-Es-based) criticisms to traditional cognitive theories—to the notions of passive perception and of serial information processing—and discuss alternative ways to address them, by appealing to frameworks that use, or do not use, notions of internal modelling and inference. Our analysis illustrates that: an explicitly inferential framework can capture some key aspects of embodied and enactive theories of cognition; some claims of computational and dynamical theories can be reconciled rather than seen as alternative explanations of cognitive phenomena; and some aspects of cognitive processing (e.g., detached cognitive operations, such as planning and imagination) that are sometimes puzzling to explain from enactive and non-representational perspectives can, instead, be captured nicely from the perspective that internal generative models and predictive processing mediate adaptive control loops.
Citations in the library
Cited by 2
Cites 9
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