Knowledge-Based Functions in Aerospace Systems (Systemes de Guidage et de Pilotage Aerospatiaux a Base de Systemes Experts),

Abstract

In aerospace systems classical control technology has enabled the transfer of functions of the human operator to machines which need not be based on the explicit evaluation of knowledge. Symbolic data processing, neural networks and the techniques of artificial intelligence now permit the design of automatic systems which can explicity make use of knowledge stored in computers. The Lecture Series presents a conceptual framework for the automation of knowledge-based control and management functions in aerospace systems which are usually carried out by human operators. It describes the structure of these functions, discusses successful examples of application and gives recommendations for further studies. The detailed discussion of the application examples. together with the experiences and lessons learned from these implementations will help potential builders of knowledge-based systems for aerospace applications to learn from the experts in this field. This Lecture Series, sponsored by the Mission Systems Panel of AGARD, has been implemented by the Consultant and Exchange Programme.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1995
Accession Number
ADA302292

Entities

People

  • Gilles Champigneux
  • Heinz Winter
  • Mark T. Maybury
  • Milton B. Adams

Organizations

  • AGARD

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • C4I
  • Electronic Warfare
  • Engineered Resilient Systems
  • Ground and Sea Platforms
  • Space

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognitive Science
  • Cognitive Systems Engineering
  • Collision Avoidance
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computers
  • Contingency Operations (Military)
  • Control Systems
  • Human Factors Engineering
  • Human-Machine Interfaces
  • Information Systems
  • Military Science
  • Network Science
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Small Business Innovation Research Program (SBIR) EDI Research and Innovation.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Space