An Algorithm for Detecting Changes in Battle Scenaria.

Abstract

In distributed tactical decision making, commanders make decisions based on data generated by their local territory as well as on decisions and information communicated th them by other commanders. The timely aspect of the decisions is controlled by the rate with which the commanders receive data, which is in turn controlled by the deployed transmission algorithms. The accuracy of the decisions, on the other hand, depends heavily on the way that the decision makers perceive their environment. This perception corresponds to a number of alternative models, where the latter are a priori developed based on the various battle scenaria. Each such model is associated with an appropriate decision mode. Furthermore, a model (or battle scenario) may shift to another such model, at a random time. In the event of such a shift, it is thus crucial that the commander be alerted, for adaptation to the appropriate decision mode. In this paper, we describe an algorithm which can be deployed in an automatic fashion to alert the commanders about changes in battle scenaria.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1987
Accession Number
ADA187605

Entities

People

  • P. P. Kazakos
  • R. K. Bansal

Organizations

  • University of Virginia

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Business Administration
  • Classification
  • Computations
  • Computer Science
  • Electrical Engineering
  • Engineering
  • False Alarms
  • Materials
  • Materials Science
  • Mathematics
  • Military Research
  • Probability
  • Schools
  • Stochastic Processes
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Quantum spin resonance or Electron Paramagnetic Resonance spectroscopy.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.