Bayesian Models of Cognition: What's Built in After All?
Version of Record online: 2 FEB 2012
© 2012 The Author. Philosophy Compass © 2012 Blackwell Publishing Ltd
Volume 7, Issue 2, pages 127–138, February 2012
How to Cite
Perfors, A. (2012), Bayesian Models of Cognition: What's Built in After All?. Philosophy Compass, 7: 127–138. doi: 10.1111/j.1747-9991.2011.00467.x
- Issue online: 2 FEB 2012
- Version of Record online: 2 FEB 2012
This article explores some of the philosophical implications of the Bayesian modeling paradigm. In particular, it focuses on the ramifications of the fact that Bayesian models pre-specify an inbuilt hypothesis space. To what extent does this pre-specification correspond to simply ‘‘building the solution in''? I argue that any learner (whether computer or human) must have a built-in hypothesis space in precisely the same sense that Bayesian models have one. This has implications for the nature of learning, Fodor's puzzle of concept acquisition, and the role of modeling in cognitive science.