A hybrid model approach to generalization in sequence learning
Rainer Spiegel, I.P.L. McLaren · 2002
Both recurrent neural networks and humans are able to learn sequential information and generalize to sequences they have not experienced in training. However, they sometimes seem to differ in the way they perform generalization. A new hybrid model is introduced that relies on both a recurrent neural network and rules typically applied by human subjects.