The power law is predominantly describing the ways humans learn, especially in psychophysics, in skill acquisition, and in retention. Yet a few researchers claim that this law is applicable only on the aggregate level and that exponential law should be considered when describing a single learning process. The question which law should be used on aggregate or single learner level has not yet been answered in the artificial learning community. This work is shedding some light towards the answers. We conducted an experiment with three artificial learners using 109 training cases. The statistical tests have shown that power law and exponential law are describing the learning curves equally well. However, in quite many cases neither of laws is applicable. Additionally, there are significant differences among artificial learners.