A pulse-based reinforcement algorithm for learning continuous functions

An algorithm is presented which allows continuous functions to be learned by a neural network using spike-based reinforcement learning. Both the mean and the variance of the weights are changed during training; the latter is accomplished by manipulating the lengths of the spike trains used to repres...

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Veröffentlicht in:	Neurocomputing (Amsterdam) 1997-01, Vol.14 (4), p.319-344
Hauptverfasser:	Gorse, D., Romano-Critchley, D.A., Taylor, J.G.
Format:	Artikel
Sprache:	eng
Schlagworte:	Continuous-output reinforcement pRAM Pulse-coding Stochastic computing
Online-Zugang:	Volltext
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