Hostname: page-component-8448b6f56d-dnltx Total loading time: 0 Render date: 2024-04-20T15:13:16.326Z Has data issue: false hasContentIssue false

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

Published online by Cambridge University Press:  25 August 2011

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/

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
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Geisler, W. S. & Ringach, D. (2009) Natural systems analysis. Visual Neuroscience 26:13.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