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Model comparison, not model falsification

Published online by Cambridge University Press:  10 January 2019

Bradley C. Love Open the ORCID record for Bradley C. Love [Opens in a new window]
Bradley C. Love*
Affiliation:
Experimental Psychology, University College London, London WC1H 0AP, United Kingdom. b.love@ucl.ac.ukhttp://bradlove.org
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Abstract

Systematically comparing models that vary across components can be more informative and explanatory than determining whether behaviour is optimal, however defined. The process of model comparison has a number of benefits, including the possibility of integrating seemingly disparate empirical findings, understanding individual and group differences, and drawing theoretical connections between model proposals.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 41 , 2018 , e233
Copyright
Copyright © Cambridge University Press 2018 

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References

Jones, M. & Love, B. C. (2011) Bayesian fundamentalism or enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition. Behavioral and Brain Sciences 34(4):169–88. Available at: http://www.journals.cambridge.org/abstract_S0140525X10003134.Google Scholar
Love, B. C., Medin, D. L. & Gureckis, T. M. (2004) SUSTAIN: A network model of category learning. Psychological Review 111:309–32.Google Scholar
Mack, M. L., Preston, A. R. & Love, B. C. (2013) Decoding the brain's algorithm for categorization from its neural implementation. Current Biology 23:2023–27.Google Scholar