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How Do Simple Connectionist Networks Achieve a Shift From "Featural" to "Correlational" Processing in Categorization? Export

Infancy, Vol. 5, No. 2. (2004), pp. 199-208.

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4 categorization model_comparison neural_network progressive_development

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Three developmental connectionist models simulate a purported shift from "featural" to "correlational" processing in infant categorization (models: Gureckis & Love, 2004/this issue; Shultz & Cohen, 2004/this issue; Westermann & Mareschal, 2004/this issue; empirical data: Cohen & Arthur, 2003; Younger, 1985; Younger & Cohen, 1986). In this article, the way in which the models are able to simulate the behavioral data is revealed, and their respective theoretical commitments are evaluated. Together the models argue that the shift from featural to correlational processing in infant categorization might be illusory, as these models are able to replicate the key behavioral features while processing correlations right from the start. As such, they claim the behavioral description of a shift is not reflected at the level of mechanism.


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