Accession Number:

ADA440391

Title:

Robust Action Strategies to Induce Desired Effects

Descriptive Note:

Research rept.

Corporate Author:

CONNECTICUT UNIV STORRS DEPT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE

Report Date:

2002-01-01

Pagination or Media Count:

23.0

Abstract:

This paper provides a new methodology for obtaining a near-optimal strategy i.e., specification of courses of action over time for achieving the desired effects in a mission environment that also is robust to environmental perturbations i.e., unexpected events andor parameter uncertainties. A dynamic Bayesian network DBN-based stochastic mission model is employed to represent the dynamic and uncertain nature of the environment. Genetic algorithms are applied to search for a near-optimal strategy with DBN serving as a fitness evaluator. The probability of achieving the desired effects namely, the probability of success at a specified terminal time is a random variable due to uncertainties in the environment. Consequently, the authors focus on signal-to-noise ratio SNR, a measure of mean and variance of the probability of success, to gauge the goodness of a strategy. The resulting strategy will not only have a relatively high probability of inducing the desired effects, but also be robust to environmental uncertainties.

Subject Categories:

  • Administration and Management
  • Statistics and Probability
  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE