Handbook of Reinforcement Learning and Control (1st ed. 2021) (Studies in Systems, Decision and Control #325)
By: and and and
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- Synopsis
- 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; andmulti-agent reinforcement learning.Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.
- Copyright:
- 2021
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783030609900
- Related ISBNs:
- 9783030609894
- Publisher:
- Springer International Publishing
- Date of Addition:
- 07/28/21
- Copyrighted By:
- Springer Nature Switzerland AG
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Technology
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
- Edited by:
- Kyriakos G. Vamvoudakis
- Edited by:
- Yan Wan
- Edited by:
- Frank L. Lewis
- Edited by:
- Derya Cansever
Reviews
Other Books
- by Frank L. Lewis
- by Kyriakos G. Vamvoudakis
- by Yan Wan
- by Derya Cansever
- in Nonfiction
- in Computers and Internet
- in Technology