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The myth of computational level theory and the vacuity of rational analysis

Published online by Cambridge University Press:  25 August 2011

Barton L. Anderson
Barton L. Anderson
Affiliation:
School of Psychology, University of Sydney, Sydney, NSW 2006, Australia. barta@psych.usyd.edu.auhttp://www.psych.usyd.edu.au/staff/barta/
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Abstract

I extend Jones & Love's (J&L's) critique of Bayesian models and evaluate the conceptual foundations on which they are built. I argue that: (1) the “Bayesian” part of Bayesian models is scientifically trivial; (2) “computational level” theory is a fiction that arises from an inappropriate programming metaphor; and (3) the real scientific problems lie outside Bayesian theorizing.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 34 , Issue 4 , August 2011 , pp. 189 - 190
Copyright
Copyright © Cambridge University Press 2011

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References

Geisler, W. S. & Ringach, D. (2009) Natural systems analysis. Visual Neuroscience 26:1–3.CrossRefGoogle ScholarPubMed
Marr, D. (1982) Vision: A computational investigation into the human representation and processing of visual information. W. H. Freeman.Google Scholar
Rosen, R. (1991) Life itself. Columbia University Press.Google Scholar
Tenenbaum, J. B., Kemp, C., Griffiths, T. L. & Goodman, N. D. (2011) How to grow a mind: Statistics, structure, and abstraction. Science 331(6022):1279–85.CrossRefGoogle Scholar