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

美意合作研究：最优近似控制理论的统计学习

• 批准号: 0098009
• 负责人: Victoria Chen
• 金额: $ 0.5万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-08-01 至 2002-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0098009&HistoricalAwards=false
• 关键词: U.S.; Italy; Cooperative; Research; Statistical

0098009ChenThis 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.

0098009Chen 这个为期一年的奖项支持美国-意大利在最优近似控制理论领域开发新方法的合作研究，涉及乔治亚理工学院的维多利亚·陈和意大利热那亚大学的里卡多·佐波利。 他们研究的目标是扩大统计学在运筹学中的作用。美国首席研究员将她在统计学习应用于随机优化方面的专业知识带到了这次合作中。 这项工作得到了意大利研究者在违反经典 LQG（线性动态系统、二次成本函数和高斯随机变量）的控制理论问题方面的经验的补充。 这项研究的结果预计将减少解决近似最优控制理论问题所需的计算量。