9783030483050-3030483053-Stochastic Linear-Quadratic Optimal Control Theory: Differential Games and Mean-Field Problems (SpringerBriefs in Mathematics)

Stochastic Linear-Quadratic Optimal Control Theory: Differential Games and Mean-Field Problems (SpringerBriefs in Mathematics)

ISBN-13: 9783030483050
ISBN-10: 3030483053
Edition: 1st ed. 2020
Author: Jiongmin Yong, Jingrui Sun
Publication date: 2020
Publisher: Springer
Format: Paperback 142 pages
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Book details

ISBN-13: 9783030483050
ISBN-10: 3030483053
Edition: 1st ed. 2020
Author: Jiongmin Yong, Jingrui Sun
Publication date: 2020
Publisher: Springer
Format: Paperback 142 pages

Summary

Stochastic Linear-Quadratic Optimal Control Theory: Differential Games and Mean-Field Problems (SpringerBriefs in Mathematics) (ISBN-13: 9783030483050 and ISBN-10: 3030483053), written by authors Jiongmin Yong, Jingrui Sun, was published by Springer in 2020. With an overall rating of 4.4 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Stochastic Linear-Quadratic Optimal Control Theory: Differential Games and Mean-Field Problems (SpringerBriefs in Mathematics) (Paperback) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This book gathers the most essential results, including recent ones, on linear-quadratic optimal control problems, which represent an important aspect of stochastic control. It presents results for two-player differential games and mean-field optimal control problems in the context of finite and infinite horizon problems, and discusses a number of new and interesting issues. Further, the book identifies, for the first time, the interconnections between the existence of open-loop and closed-loop Nash equilibria, solvability of the optimality system, and solvability of the associated Riccati equation, and also explores the open-loop solvability of mean-filed linear-quadratic optimal control problems. Although the content is largely self-contained, readers should have a basic grasp of linear algebra, functional analysis and stochastic ordinary differential equations. The book is mainly intended for senior undergraduate and graduate students majoring in applied mathematics who are interested in stochastic control theory. However, it will also appeal to researchers in other related areas, such as engineering, management, finance/economics and the social sciences.

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