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Feature learning, multiresolution analysis, and symbol grounding

Published online by Cambridge University Press:  01 February 1998

Karl F. MacDorman
Karl F. MacDorman
Affiliation:
Department of Mechanical Engineering, Osaka University, Toyonaka, Osaka 560, [email protected] www.cl.cam.ac.uk/~kfm11
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Abstract

Cognitive theories based on a fixed feature set suffer from frame and symbol grounding problems. Flexible features and other empirically acquired constraints (e.g., analog-to-analog mappings) provide a framework for letting extrinsic relations influence symbol manipulation. By offering a biologically plausible basis for feature learning, nonorthogonal multiresolution analysis and dimensionality reduction, informed by functional constraints, may contribute to a solution to the symbol grounding problem.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 21 , Issue 1 , February 1998 , pp. 32
Copyright
© 1998 Cambridge University Press

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