Presents a theoretical account of human shift learning with the use of neural network tools. Details how simulations using the cascade-correlation algorithm which show that networks can capture the regularities of the discrimination shift literature better than existing psychological theories. Suggests that human developmental differences in shift learning arise from spontaneous overtraining by older participants, consistent with overtraining literature. (LBT)