• 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