DocumentCode :
2300931
Title :
The importance of implicit and explicit knowledge in a pilot´s associate system
Author :
Perschbacher, David L. ; Levi, Keith R. ; Hoffman, Mark
Author_Institution :
Honeywell Syst. & Res. Center, Minneapolis, MN, USA
fYear :
1991
fDate :
20-24 May 1991
Firstpage :
1158
Abstract :
It is pointed out that fielding an operational pilot´s associate (PA) will require both implicit and explicit representations of knowledge. Speed and memory performance requirements for PA will be aided by the use of implicit representations of knowledge. Acquiring and maintaining the large knowledge bases for PA will, by contrast, be aided by having explicit knowledge representations. Such explicit representations are being investigated in a 10 person-year research project sponsored by the Wright Research and Development Center. A critical contribution of this research has been to develop concepts that make machine learning applicable to real-time control and execution systems such as pilot´s associate. The authors describe how machine learning techniques can automatically transform explicit representations into the implicit representations required by PA
Keywords :
aerospace computing; knowledge representation; learning systems; military computing; US Air Force; execution systems; explicit knowledge; explicit representations; implicit representations; machine learning; operational pilot´s associate; real-time control; Aerospace electronics; Aircraft; Artificial intelligence; Contracts; Control systems; Knowledge representation; Machine learning; Monitoring; Real time systems; Research and development;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Aerospace and Electronics Conference, 1991. NAECON 1991., Proceedings of the IEEE 1991 National
Conference_Location :
Dayton, OH
Print_ISBN :
0-7803-0085-8
Type :
conf
DOI :
10.1109/NAECON.1991.165905
Filename :
165905
Link To Document :
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