DocumentCode :
1833005
Title :
Prediction-error driven learning: the engine of change in cognitive development
Author :
McClelland, James L.
Author_Institution :
Center for the Neural Basis of Cognition, Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
2002
fDate :
2002
Firstpage :
43
Abstract :
Summary form only given. Since the introduction of powerful connectionist learning procedures such as back propagation, our group has been studying the use of such procedures as a mechanism for cognitive development. The models can be viewed as capturing Piaget´s idea that development is essentially an experience driven process, dependent of the adjustment of schemas to assimilate disparities between expectations and observations. Among the issues that have been addressed with these models are the following: (1) Is an initial naive domain theory required to allow a learner to interpret experience in a given domain? (2) Why does learning appear to occur in stages, punctuated by plateaus? (3) what does it mean to be ´ready to learn´? (4) Is it necessary to start small in learning, and if so when and why? (5) Why are there critical or sensitive periods in learning; why is it sometimes easier to learn when a system is ´young´ or inexperienced?.
Keywords :
cognitive systems; learning (artificial intelligence); neural nets; back propagation; backpropagation; cognitive development; connectionist learning procedures; expectations; naive domain theory; observations; prediction-error driven learning; Animal structures; Cognition; Computer science; Context modeling; Distributed processing; Engines; Organizing; Predictive models; Psychology; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Development and Learning, 2002. Proceedings. The 2nd International Conference on
Print_ISBN :
0-7695-1459-6
Type :
conf
DOI :
10.1109/DEVLRN.2002.1011732
Filename :
1011732
Link To Document :
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