Self-Organizing Maps
Modeling human learning as context dependent knowledge utility optimization
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
A Cognitive Model of Concept Learning with a Flexible Internal Representation System
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
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Cognitive models has been a main tool for quantitatively testing theories on human cognition. The results of previous cognitive modeling research collectively suggest the comparative advantage of exemplar over prototype accounts in human cognition. However, we hypothesized that unsuccessful outcomes by traditional prototype models may be the unforeseen consequences of the algorithmic constraints imposed on the models, but not of the implausibility of the theory itself. To test this hypothesis, a new cognitive model based on prototype theory with a more complex and realistic attention system is introduced and evaluated in the present study. A simulation study shows that a new model termed CASPRE resulted in a substantial improvement as compared with the traditional prototype model in replicating empirical findings and that it performed marginally better than an exemplar model, thus confirming our hypothesis.