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Model comparison, not model falsification

  • Bradley C. Love (a1)

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.

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References

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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.
Love, B. C., Medin, D. L. & Gureckis, T. M. (2004) SUSTAIN: A network model of category learning. Psychological Review 111:309–32.
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.
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Behavioral and Brain Sciences
  • ISSN: 0140-525X
  • EISSN: 1469-1825
  • URL: /core/journals/behavioral-and-brain-sciences
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