Philosophy Compass 7 (2):127-138 (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 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
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References found in this work BETA
Representations: Philosophical Essays on the Foundations of Cognitive Science.Jerry A. Fodor - 1981 - MIT Press.
Probabilistic Models of Cognition: Exploring Representations and Inductive Biases.Thomas L. Griffiths, Nick Chater, Charles Kemp, Amy Perfors & Joshua B. Tenenbaum - 2010 - Trends in Cognitive Sciences 14 (8):357-364.
Bayesian Fundamentalism or Enlightenment? On the Explanatory Status and Theoretical Contributions of Bayesian Models of Cognition.Matt Jones & Bradley C. Love - 2011 - Behavioral and Brain Sciences 34 (4):169-188.
Citations of this work BETA
Subjective Probability as Sampling Propensity.Thomas Icard - 2016 - Review of Philosophy and Psychology 7 (4):863-903.
A Unified Account of General Learning Mechanisms and Theory‐of‐Mind Development.Theodore Bach - 2014 - Mind and Language 29 (3):351-381.
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