From Fly Detectors to Action Control: Representations in Reinforcement Learning

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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 languageEnglish
JournalPhilosophy of Science
Issue number5
Pages (from-to)1045-1054
Number of pages10
Publication statusPublished - Dec 2021
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 611 Philosophy
  • 615 History and Archaeology

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