Studies in Systems, Decision and Control

Vamvoudakis, Kyriakos G.; Wan, Yan; Lewis, Frank L.; Cansever, Derya

This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology.

The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including:

• deep learning;
• artificial intelligence;
• applications of game theory;
• mixed modality learning; and
• multi-agent reinforcement learning.

Details

Published by: Springer

Publication Date: 2021-06-24

Format: Hardcover

ISBN-13: 9783030609894

DOI: 10.1007/978-3-030-60990-0

Dimensions: 235cm x155cm

Pages: 833