DocumentCode :
274197
Title :
Automatic learning of efficient behaviour
Author :
Watkins, C.J.C.H.
Author_Institution :
Philips Res. Lab., Redhill, UK
fYear :
1989
fDate :
16-18 Oct 1989
Firstpage :
395
Lastpage :
398
Abstract :
Many of the artificial neural network models so far proposed `learn´ nonlinear functional mappings from training examples. For example, the multilayer perceptron of D.E. Rumelhart and J.L. McClelland (1984) and the CMAC of J.A. Albus (1981) are both devices of this type. Neural networks are not the only function approximation methods available, and there is interest in other methods; a number of types of function learning module have been reviewed by S. Omohundro (1987). The paper describes how to use such function learning modules as components of larger learning systems that learn efficient strategies for performing multistage tasks, a method by which machines could acquire skill through experience
Keywords :
function approximation; learning systems; neural nets; artificial neural network models; automatic learning; function approximation; multilayer perceptron; nonlinear functional mappings;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Artificial Neural Networks, 1989., First IEE International Conference on (Conf. Publ. No. 313)
Conference_Location :
London
Type :
conf
Filename :
52001
Link To Document :
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