Title :
A hybrid model approach to generalization in sequence learning
Author :
Spiegel, Rainer ; McLaren, IPL
Author_Institution :
Dept. of Exp. Psychol., Cambridge Univ., UK
Abstract :
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
Keywords :
generalisation (artificial intelligence); learning (artificial intelligence); recurrent neural nets; generalization; hybrid model; recurrent neural networks; sequence learning; Artificial intelligence; Backpropagation algorithms; Context modeling; Humans; Intelligent networks; Neural networks; Predictive models; Psychology; Recurrent neural networks; Testing;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.938741
