Enaction, Embodiment, Evolutionary Robotics: Simulation Models for a Post-Cognitivist Science of Mind
March 10, 2010 DOI: 10.2991/978-94-91216-34-3 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper |
|---|---|
| Citations | 15 |
| Key points | Argues that Evolutionary Robotics simulations, as methodological minimalism, can help solve problems in cognitive science and that minimalism is a merit rather than a shortcoming. Endorses an enactive and constructivist view of the mind against the traditional information-processing view, and proposes a new interdisciplinary framework for studying perception combining simulation modeling, experimental methods, and accounts of subjective experience. |
Abstract
The book Enaction, Embodiment, Evolutionary Robotics proposes how a particular kind of simulation model, i.e. Evolutionary Robotics simulations, can help to solve several problems in Cognitive Science. Examples discussed in the book ranges from motor control, neuroscientific theory, social contingency and time perception. It is argued that methodological minimalism can be a merit, not a shortcoming, even when studying something as complex as the human mind. The book concludes by proposing a new minimalist interdisciplinary framework for the study of perception, combining simulation modeling, experimental methods and accounts of subjective experience.\nThis book endorses an enactive and constructivist view on the human mind, in opposition to the traditional information-processing view. Furthermore, the book discusses and presents the enactive approach, clarifies the assets of this view and how it differs from other proposed alternatives to the computationalist paradigm in AI and Cognitive Science, crucial and missing in the ongoing embodied turn. The book also presents new experimental results on a number of topics and points out connections between them. Finally, the book proposes a novel framework for the study of perception that combines a number of methods, including computational modeling, in a previously unseen and promising way.