Handbook Of Reinforcement Learning And Control 325 Studies In Systems Decision And Control 325 1st Ed 2021 Kyriakos G Vamvoudakis Editor by Kyriakos G. Vamvoudakis (editor), Yan Wan (editor), Frank L. Lewis (editor), Derya Cansever (editor) 9783030609894, 3030609898 instant download after payment.

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.