PSA2016: The 25th Biennial Meeting of the Philosophy of Science Association

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Mechanistic Bayesian cognitive science?

Bayesian models of cognition are typically offered as computational models that made (almost) no mechanistic commitments. Recently, however, a number of Bayesian models have been proposed that aim to be mechanistic. In this talk, I argue that these theories are much less mechanistic than is usually claimed, as they almost all have significant computational-level “components.” Proper understanding of the explanatory power of these theories requires moving beyond the standard (Marr) levels of explanation in cognitive science. I thus propose a more complex, multidimensional space of theoretical commitments, which yields a corresponding complex space of explanatory power(s).

Author Information:

David Danks    
Philosophy
Carnegie Mellon University

 

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