Accession Number:

ADA050416

Title:

Approximation Techniques and Optimal Decision Making for Stochastic Lanchester Models

Descriptive Note:

Technical rept.

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF STATISTICS

Personal Author(s):

Report Date:

1978-01-01

Pagination or Media Count:

156.0

Abstract:

This thesis extends the analysis of stochastic Lanchester models beyond the stage of mere modeling. To this end, a frame-work of statistical decision theory is superimposed on a simplified combat situation. The commander must make decisions about the amount of force he will commit to a combat in reference to a suitable cost and reward structure. Problems of both the one- stage and the multi-stage variety are studied. The one-stage decision problem requires knowledge of the probability of victory and the expected number of survivors. A complete solution to this problem is given, based on the use of a martingale central limit theorem. The multi-stage decision problem requires the distribution of the force level configuration as a function of time. These distributions are approximated through the use of diffusion approximations. A two-stage problem is solved using these approximations and backward induction.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE