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Proceedings Paper

Adaptive Decoder For An Adaptive Learning Controller
Author(s): D. Politis; W. Licata
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Paper Abstract

This paper discusses the implementation of an Adaptive Decoder (AD) in the Adaptive Learning Controller (ALC) algorithms developed by Barto, based on the neuron modeling work of Klopf. It is shown that using an Adaptive Decoder that shifts from coarse to fine space partition at a chosen instant improves ALC performance significantly, by decreasing the required learning time and reducing the operating bounds of the control variables.

Paper Details

Date Published: 26 March 1986
PDF: 7 pages
Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); doi: 10.1117/12.964177
Show Author Affiliations
D. Politis, Environmental Research Institute of Michigan (United States)
W. Licata, Environmental Research Institute of Michigan (United States)


Published in SPIE Proceedings Vol. 0635:
Applications of Artificial Intelligence III
John F. Gilmore, Editor(s)

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