Title :
Dynamics of the generalised lotto-type competitive learning
Author :
Luk, Andrew ; Lien, Sandra
Author_Institution :
St B&P Neural Investments Pty Ltd., Australia
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;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.860836
