Abstract
A conceptual tool with which to assess the learning ability of neural networks is proposed. What is desired is a general-purpose tool with which to appraise the representations of knowledge of a system that are formed over time and experience. The authors suggest that such a tool should not be limited to any one neural simulation paradigm. The requirements of such an approach are examined, and a metric for this purpose is proposed.
Original language | English (US) |
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Title of host publication | Unknown Host Publication Title |
Editors | Maureen Caudill, Charles T. Butler, San Diego Adaptics |
Place of Publication | San Diego, CA, USA |
Publisher | SOS Printing |
State | Published - 1987 |
ASJC Scopus subject areas
- General Engineering