Timothy L. Molloy,Jairo Inga Charaja,Soeren Hohmann,Tristan Perez
Inverse Optimal Control and Inverse Noncooperative Dynamic Game Theory: A Minimum-Principle Approach
Inverse Optimal Control and Inverse Noncooperative Dynamic Game Theory: A Minimum-Principle Approach
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- More about Inverse Optimal Control and Inverse Noncooperative Dynamic Game Theory: A Minimum-Principle Approach
This book provides a novel unified treatment of inverse problems in optimal control and noncooperative dynamic game theory, with applications in control, robotics, biology, and economics. It emphasizes the application of Pontryagin's minimum principle and proposes algorithms based on dynamic optimization theory. The insights into information requirements for solving inverse problems have practical consequences in the design of technologies seeking to exploit inverse techniques.
Format: Paperback / softback
Length: 266 pages
Publication date: 21 February 2023
Publisher: Springer Nature Switzerland AG
This groundbreaking book offers a novel and comprehensive treatment of inverse problems in optimal control and noncooperative dynamic game theory. It equips readers with essential tools to develop practical algorithms for solving diverse inverse problems across control, robotics, biology, and economics. The treatment employs Pontryagin's minimum principle to address a wide range of inverse problems and proposes algorithms rooted in the elegant principles of dynamic optimization theory. A balanced emphasis is placed on fundamental theoretical inquiries and practical applications.
The text begins by providing an introduction and background to its topics, including discrete-time and continuous-time inverse optimal control. It then delves into differential and dynamic games, culminating in a discussion of relevant applications.
The algorithms and theoretical results developed in this book provide valuable insights into the information requirements for solving inverse problems. These insights have profound practical implications in the design of technologies that leverage inverse techniques, such as collaborative robots, driver-assistance systems, and autonomous systems. Consequently, the book appeals to researchers, engineers, and postgraduate students across various disciplines within the realm of control and robotics.
Weight: 438g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030933197
Edition number: 1st ed. 2022
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