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Reducing problem complexity by analogical transfer

Published online by Cambridge University Press:  01 March 1997

Peter F. Dominey
Affiliation:
INSERM U94 69500 Bron; CNRS EP-100 69008 Lyon, Francedominey@lyon151.inserm.fr

Abstract

Analogical transfer in sequence learning is presented as an example of how the type-2 problem of learning an unbounded number of isomorphic sequences is reduced to the type-1 problem of learning a small finite set of sequences. The commentary illustrates how the difficult problem of appropriate analogical filter creation and selection is addressed while avoiding the trap of strong nativism, and it provides theoretical and experimental evidence for the existence of dissociable mechanisms for type-1 learning and type-2 recoding.

Type
Open Peer Commentary
Copyright
© 1997 Cambridge University Press

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