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Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 29284


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11367
Generalized Exploratory Model of Human Category Learning
Abstract:
One problem in evaluating recent computational models of human category learning is that there is no standardized method for systematically comparing the models' assumptions or hypotheses. In the present study, a flexible general model (called GECLE) is introduced that can be used as a framework to systematically manipulate and compare the effects and descriptive validities of a limited number of assumptions at a time. Two example simulation studies are presented to show how the GECLE framework can be useful in the field of human high-order cognition research.
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References:

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