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Proceedings Paper

Predictive models of battle dynamics
Author(s): Jan Jelinek
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Paper Abstract

The application of control and game theories to improve battle planning and execution requires models, which allow military strategists and commanders to reliably predict the expected outcomes of various alternatives over a long horizon into the future. We have developed probabilistic battle dynamics models, whose building blocks in the form of Markov chains are derived from the first principles, and applied them successfully in the design of the Model Predictive Task Commander package. This paper introduces basic concepts of our modeling approach and explains the probability distributions needed to compute the transition probabilities of the Markov chains.

Paper Details

Date Published: 19 September 2001
PDF: 14 pages
Proc. SPIE 4367, Enabling Technology for Simulation Science V, (19 September 2001); doi: 10.1117/12.440040
Show Author Affiliations
Jan Jelinek, Honeywell Labs. (United States)

Published in SPIE Proceedings Vol. 4367:
Enabling Technology for Simulation Science V
Alex F. Sisti; Dawn A. Trevisani, Editor(s)

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