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Proceedings Paper

Model abstraction results using state-space system identifications
Author(s): Douglas A. Popken
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Paper Abstract

In this paper we report on state-space system identification approaches to dynamic behavioral abstraction of military simulation models. Two stochastic simulation models were identified under a variety of scenarios. The `Attrition Simulation' is a model of two opposing forces with multiple weapon system types. The `Mission Simulation' is a model of a squadron of aircraft performing battlefield air interdiction. Four system identification techniques: Maximum Entropy, Compartmental Models, Canonical State-Space Models, and Hidden Markov Models (HMM), were applied to these simulation models. The system identification techniques were evaluated on how well their resulting abstractions replicated the distributions of the simulation states as well as the decision outputs. Encouraging results were achieved by the HMM technique applied to the Attrition Simulation--and by the Maximum Entropy technique applied to the Mission Simulation.

Paper Details

Date Published: 23 June 2000
PDF: 12 pages
Proc. SPIE 4026, Enabling Technology for Simulation Science IV, (23 June 2000); doi: 10.1117/12.389369
Show Author Affiliations
Douglas A. Popken, Systems View (United States)

Published in SPIE Proceedings Vol. 4026:
Enabling Technology for Simulation Science IV
Alex F. Sisti, Editor(s)

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