Repository URL:
http://philsci-archive.pitt.edu/id/eprint/12568
Author(s):
Samuli Poyhonen
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conference paper description
Probabilistic modeling is a highly influential method of theorizing in cognitive science. Rational analysis is an account of how probabilistic modeling can be used to construct non-mechanistic but self-standing explanatory models of the mind. In this article, I disentangle and assess several possible explanatory contributions which could be attributed to rational analysis. Although existing models suffer from evidential problems that question their explanatory power, I argue that rational analysis modeling can complement mechanistic theorizing by providing models of environmental affordances.

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