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Towards a Cognitive Robotics

Author(s): Andy Clark , Rick Grush

Publication date Created: July 26 2016

Publication date (Print): July 26 2016

Journal: Adaptive Behavior

Publisher: SAGE Publications

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Most cited references 11

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Learning and development in neural networks: the importance of starting small.

Jeffrey Elman (1993)

It is a striking fact that in humans the greatest learning occurs precisely at that point in time--childhood--when the most dramatic maturational changes also occur. This report describes possible synergistic interactions between maturational change and the ability to learn a complex domain (language), as investigated in connectionist networks. The networks are trained to process complex sentences involving relative clauses, number agreement, and several types of verb argument structure. Training fails in the case of networks which are fully formed and 'adultlike' in their capacity. Training succeeds only when networks begin with limited working memory and gradually 'mature' to the adult state. This result suggests that rather than being a limitation, developmental restrictions on resources may constitute a necessary prerequisite for mastering certain complex domains. Specifically, successful learning may depend on starting small.

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On the proper treatment of connectionism

Paul Smolensky (1988)

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What Might Cognition Be, If Not Computation?

Tim Van Gelder, John Smylie (1995)

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Author and article information

Journal

Title: Adaptive Behavior

Abbreviated Title: Adaptive Behavior

Publisher: SAGE Publications

ISSN (Print): 1059-7123

ISSN (Electronic): 1741-2633

Publication date Created: July 26 2016

Publication date (Print): July 26 2016

Volume: 7

Issue: 1

Pages: 5-16

Article

DOI: 10.1177/105971239900700101

SO-VID: 8e66f986-ab8c-4f4b-b1d4-4aa4e230d270

Copyright © © 2016

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