DocumentCode
3044666
Title
Analogous memory utilization-a necessary characteristic for large, adaptive neural net
Author
Fortune, James A.
Author_Institution
Oakland Univ., Rochester, MI, USA
fYear
1989
fDate
14-17 Nov 1989
Firstpage
1268
Abstract
When confronted with new knowledge structured in a familiar way humans often rely on analogy to make a one-to-one correspondence to the familiar structure. The author notes that efficient adaptive neural nets also have that characteristic. In fact, the absence of analogous memory utilization from a system will be obvious because the resulting uncontrolled redundancy will quickly fill new memory with an exponential explosion of redundant information. The resulting decrease in performance is rapid and dramatic. A discussion is presented of why proper use of available memory will produce analogous memory utilization automatically
Keywords
knowledge engineering; memory architecture; neural nets; adaptive neural net; analogous memory utilization; redundancy; Artificial intelligence; Biological neural networks; Entropy; Explosions; Hardware; Humans; Natural languages; Neural networks; Robot motion; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 1989. Conference Proceedings., IEEE International Conference on
Conference_Location
Cambridge, MA
Type
conf
DOI
10.1109/ICSMC.1989.71507
Filename
71507
Link To Document