dc.contributor.author |
Falas, T |
en |
dc.contributor.author |
Stafylopatis, A |
en |
dc.date.accessioned |
2014-03-01T02:49:11Z |
|
dc.date.available |
2014-03-01T02:49:11Z |
|
dc.date.issued |
2002 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/34386 |
|
dc.subject |
backpropagation |
en |
dc.subject |
Learning System |
en |
dc.subject |
Supervised Learning |
en |
dc.subject |
Temporal Difference Learning |
en |
dc.subject |
Time Series Prediction |
en |
dc.subject |
Training Algorithm |
en |
dc.subject |
Neural Network |
en |
dc.subject |
Scaled Conjugate Gradient |
en |
dc.subject |
Temporal Difference |
en |
dc.title |
Temporal differences learning with the scaled conjugate gradient algorithm |
en |
heal.type |
conferenceItem |
en |
heal.identifier.primary |
10.1109/ICONIP.2002.1201971 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1109/ICONIP.2002.1201971 |
en |
heal.publicationDate |
2002 |
en |
heal.abstract |
This paper investigates the use of the scaled conjugate gradient algorithm in temporal differences learning for time series prediction more than one time interval ahead. Although neural networks trained with the traditional backpropagation (BP) algorithm are successfully applied in this area, the temporal differences (TD) methodology is potentially more applicable for multi-step predictions. A combination of TD with advanced algorithms |
en |
heal.journalName |
International Conference on Neural Information Processing |
en |
dc.identifier.doi |
10.1109/ICONIP.2002.1201971 |
en |