Abstract
According to radical enactivists, cognitive sciences should abandon the representational framework. Perceptuomotor cognition and action control are often provided as paradigmatic examples of nonrepresentational cognitive phenomena. In this article, we illustrate how motor and action control are studied in research that uses reinforcement learning algorithms. Crucially, this approach can be given a representational interpretation. Hence, reinforcement learning provides a way to explicate action-oriented views of cognitive systems in a representational way.
Original language | English |
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Journal | Philosophy of Science |
Volume | 88 |
Issue number | 5 |
Pages (from-to) | 1045-1054 |
Number of pages | 10 |
ISSN | 0031-8248 |
DOIs | |
Publication status | Published - Dec 2021 |
MoE publication type | A1 Journal article-refereed |
Fields of Science
- 611 Philosophy
- 615 History and Archaeology