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A neural-network interpretation of selection in learning and behavior

Published online by Cambridge University Press:  06 November 2001

José E Burgos
Affiliation:
University of Guadalajara, Col. Chapalita, Guadalajara, Jalisco 45030, Mexicojburgos@cucba.udg.mx www.udgserv.cencar.udg.mx/~ceip/

Abstract

In their account of learning and behavior, the authors define an interactor as emitted behavior that operates on the environment, which excludes Pavlovian learning. A unified neural-network account of the operant-Pavlovian dichotomy favors interpreting neurons as interactors and synaptic efficacies as replicators. The latter interpretation implies that single-synapse change is inherently Lamarckian.

Type
Brief Report
Copyright
© 2001 Cambridge University Press

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