%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