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Title: Descartes, the sheep, and the wolf : a study in the autonomy of Cartesian automata
Author: Kekedi, Balint
ISNI:       0000 0004 5914 4973
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2015
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My thesis is an analysis of classical problems in perceptual cognition as they appear in Descartes' mechanical philosophy. My primary focus will be on animals, as well as on the models and metaphors that Descartes used to explain how sense perception, information processing, self-regulation, and self-determination occur in natural automata. His models and metaphors typically include man-made devices of his age and a variety of natural processes taken from the inanimate part of nature, which will also be an integral part of my discussion. Throughout the analysis, I will approach these issues from the vantage point of the notion of physiological autonomy, a concept I develop to show how the inner mechanisms of organic bodies contribute to their autonomous functioning in the physical world in Descartes' conception. This is an important task because it allows us to have a better understanding of the mechanical approach to the living in the early modern period, but also because the approach I adopt here highlights the shortcomings of existing literature on the bête-machine theory which most often fail to appreciate Descartes' efforts to imagine a working cognitive system inside non-human living creatures. Even those commentators who direct their attention to Descartes' views about animals emphasise the limitations of natural automata resulting from what they are not, i.e. they are not mind-body unions as humans, whereas I shall maintain that if we understand correctly what the machinery of the body is capable of, we will understand better what Descartes has to say about human cognition as well, in particular, what he believes the body contributes to the cognitive economy of embodied minds.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Machine theory