Human Category Learning in Reversal Tasks: Dynamic Learning Rates Help Overcome Catastrophic Interference in Connectionist Networks

During category learning tasks participants often group together, i.e., “commonly code,” within-category exemplars. In two experiments, human participants learned to classify fractal exemplars into two arbitrarily-defined categories. After an initial learning phase, we reversed the exemplar-category