U.S.-Italy Cooperative Research: Statistical Learning for Optimal Approximate Control Theory

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

0098009 Chen This one-year award, which supports U.S.-Italy cooperative research on the development of new methodology in the area of optimal approximate control theory, involves Victoria Chen of the Georgia Institute of Technology and Ricardo Zoppoli, University of Genoa, Italy. The objective of their research is to expand the role of statistics in operations research. The U. S. principal investigator brings to this collaboration her expertise in the application of statistical learning to stochastic optimization. This work is complemented by the Italian investigator's experience in control theory problems that violate the classical LQG (linear dynamic systems, quadratic cost functions, and Gaussian random variables). The results of this research are expected to reduce the computational effort required to solve problems in approximate optimal control theory.