%0 Journal Article %A Toshihiko Matsuka %D 2007 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 4, 2007 %T Generalized Exploratory Model of Human Category Learning %U https://publications.waset.org/pdf/11367 %V 4 %X 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. %P 1146 - 1154