Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-13T09:03:56.486Z Has data issue: false hasContentIssue false

Taking the rationality out of probabilistic models

Published online by Cambridge University Press:  25 August 2011

Bob Rehder
Affiliation:
Department of Psychology, New York University, New York, NY 10003. bob.rehder@nyu.eduwww.psych.nyu.edu/rehder/

Abstract

Rational models vary in their goals and sources of justification. While the assumptions of some are grounded in the environment, those of others – which I label probabilistic models – are induced and so require more traditional sources of justification, such as generalizability to dissimilar tasks and making novel predictions. Their contribution to scientific understanding will remain uncertain until standards of evidence are clarified.

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

Card, S., Moran, T. & Newell, A. (1983) The psychology of human-computer interaction. Erlbaum.Google Scholar
Dupre, J. (1981) Natural kinds and biological taxa. Philosophical Review 90:6690.CrossRefGoogle Scholar
Genesereth, M. R. & Nilsson, N. J. (1987) Logical foundations of artificial intelligence. Morgan Kaufman.Google Scholar
Kemp, C. & Tenenbaum, J. B. (2009) Structured statistical models of inductive reasoning. Psychological Review 116:2058.CrossRefGoogle ScholarPubMed
Lakatos, I. (1970) Falsification and the methodology of scientific research programmes. In: Criticism and the growth of knowledge, ed. Lakatos, I. & Musgrave, A., pp. 91196. Cambridge University Press.CrossRefGoogle Scholar
Maloney, L. T. & Mamassian, P. (2009) Bayesian decision theory as a model of human visual perception: Testing Bayesian transfer. Visual Neuroscience 26:147–55.CrossRefGoogle Scholar
Maloney, L. T. & Zhang, H. (2010) Decision-theoretic models of visual perception and action. Vision Research 50:2362–74.CrossRefGoogle ScholarPubMed
Rehder, B. (2009) Causal-based property generalization. Cognitive Science 33:301–43.CrossRefGoogle ScholarPubMed
Rehder, B. & Burnett, R. (2005) Feature inference and the causal structure of categories. Cognitive Psychology 50:264314.CrossRefGoogle ScholarPubMed
Rehder, B. & Kim, S. (2010) Causal status and coherence in causal-based categorization. Journal of Experimental Psychology: Learning, Memory, and Cognition 36:1171–206.Google ScholarPubMed
Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton University Press.Google Scholar
Sanborn, A. N., Griffiths, T. L. & Navarro, D. J. (2010a) Rational approximations to rational models: Alternative algorithms for category learning. Psychological Review 117:1144–67.CrossRefGoogle ScholarPubMed