Hostname: page-component-cb9f654ff-hqlzj Total loading time: 0 Render date: 2025-08-23T04:02:37.822Z Has data issue: false hasContentIssue false
  • English
  • Français

Flexible features, connectionism, and computational learning theory

Published online by Cambridge University Press:  01 February 1998

Georg Dorffner
Georg Dorffner
Affiliation:
Department of Medical Cybernetics and Artificial Intelligence, University of Vienna, A-1010 Vienna, Austria georg@ai.univie.ac.at www.ai.univie.ac.at/oefai/nn/georg.html
Get access Rights & Permissions [Opens in a new window]

Abstract

This commentary is an elaboration on Schyns, Goldstone & Thibaut's proposal for flexible features in categorization in the light of three areas not explicitly discussed by the authors: connectionist models of categorization, computational learning theory, and constructivist theories of the mind. In general, the authors' proposal is strongly supported, paving the way for model extensions and for interesting novel cognitive research. Nor is the authors' proposal incompatible with theories positing some fixed set of features.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 21 , Issue 1 , February 1998 , pp. 24 - 25
Copyright
© 1998 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable