DocumentCode
352977
Title
Dynamics of the generalised lotto-type competitive learning
Author
Luk, Andrew ; Lien, Sandra
Author_Institution
St B&P Neural Investments Pty Ltd., Australia
Volume
4
fYear
2000
fDate
2000
Firstpage
597
Abstract
In the generalised lotto-type competitive learning algorithm more than one winner exist, and the winners are divided into tiers, with each tier being rewarded differently. All the losers are penalised equally. It is possible to formulate a set of equations which is useful in studying the various dynamic aspects of the generalised lotto-type competitive learning
Keywords
differential equations; dynamics; generalisation (artificial intelligence); neural nets; unsupervised learning; competitive learning; differential equations; dynamics; lotto-type learning; neural nets; short term memory; Australia; Convergence; Counting circuits; Equations; Frequency; Investments; Neural networks; Neurons; Prototypes;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location
Como
ISSN
1098-7576
Print_ISBN
0-7695-0619-4
Type
conf
DOI
10.1109/IJCNN.2000.860836
Filename
860836
Link To Document