Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-11T04:05:09.192Z Has data issue: false hasContentIssue false

Mechanistic curiosity will not kill the Bayesian cat

Published online by Cambridge University Press:  25 August 2011

Denny Borsboom
Affiliation:
Department of Psychology, University of Amsterdam, 1018 WB Amsterdam, The Netherlands. dennyborsboom@gmail.comej.wagenmakers@gmail.comhttp://sites.google.com/site/borsboomdenny/dennyborsboomhttp://www.ejwagenmakers.com/
Eric-Jan Wagenmakers
Affiliation:
Department of Psychology, University of Amsterdam, 1018 WB Amsterdam, The Netherlands. dennyborsboom@gmail.comej.wagenmakers@gmail.comhttp://sites.google.com/site/borsboomdenny/dennyborsboomhttp://www.ejwagenmakers.com/
Jan-Willem Romeijn
Affiliation:
Department of Philosophy, University of Groningen, 9712 GL Groningen, The Netherlands. j.w.romeijn@rug.nlhttp://www.philos.rug.nl/~romeyn

Abstract

Jones & Love (J&L) suggest that Bayesian approaches to the explanation of human behavior should be constrained by mechanistic theories. We argue that their proposal misconstrues the relation between process models, such as the Bayesian model, and mechanisms. While mechanistic theories can answer specific issues that arise from the study of processes, one cannot expect them to provide constraints in general.

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

Albert, M. (2001) Bayesian learning and expectations formation: Anything goes. In: Foundations of Bayesianism, ed. Corfield, D. & Williamson, J., pp. 341–62. Kluwer.CrossRefGoogle Scholar
Brown, S. D., Wagenmakers, E.-J. & Steyvers, M. (2009) Observing evidence accumulation during multi-alternative decisions. Journal of Mathematical Psychology 53:453–62.CrossRefGoogle Scholar
Ma, W. J., Beck, J. M., Latham, P. E. & Pouget, A. (2006) Bayesian inference with probabilistic population codes. Nature Neuroscience 9:1432–38.CrossRefGoogle ScholarPubMed
Oaksford, M. & Chater, N. (2007) Bayesian rationality: The probabilistic approach to human reasoning. Oxford University Press.CrossRefGoogle Scholar
Pearl, J. (2000) Causality: Models, reasoning, and inference. Cambridge University Press.Google Scholar