Machine Learning of Parameter Control Doctrine for Sensor and Communication Systems

Abstract

Artificial intelligence approaches to learning were reviewed for their potential contributions to the construction of a system to learn parameter control doctrine. Separate learning tasks were isolated and several levels of related problems were distinguished. Formulas for providing the learning system with measures of its performance were derived for four kinds of targets.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1988
Accession Number
ADA200096

Entities

People

  • R. A. Dillard
  • R. B. Kamen

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Classification
  • Cognitive Science
  • Communication Systems
  • Computer Science
  • Computers
  • Detection
  • Detectors
  • Doctrine
  • Genetic Algorithms
  • Information Processing
  • Language
  • Machine Learning
  • Pattern Recognition
  • Psychology
  • Two Dimensional

Readers

  • Artificial Intelligence
  • Joint Military Operations and Doctrine.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks