Reinforcement Learning Algorithms: Analysis and Applications (1st ed. 2021) (Studies in Computational Intelligence #883)
By: and and and and
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- Synopsis
- This book reviews research developments in diverse areas of reinforcement learning such as model-free actor-critic methods, model-based learning and control, information geometry of policy searches, reward design, and exploration in biology and the behavioral sciences. Special emphasis is placed on advanced ideas, algorithms, methods, and applications. The contributed papers gathered here grew out of a lecture course on reinforcement learning held by Prof. Jan Peters in the winter semester 2018/2019 at Technische Universität Darmstadt. The book is intended for reinforcement learning students and researchers with a firm grasp of linear algebra, statistics, and optimization. Nevertheless, all key concepts are introduced in each chapter, making the content self-contained and accessible to a broader audience.
- Copyright:
- 2021
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783030411886
- Related ISBNs:
- 9783030411879
- Publisher:
- Springer International Publishing
- Date of Addition:
- 01/04/21
- Copyrighted By:
- Springer
- 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:
- Boris Belousov
- Edited by:
- Hany Abdulsamad
- Edited by:
- Pascal Klink
- Edited by:
- Simone Parisi
- Edited by:
- Jan Peters
Reviews
Other Books
- by Boris Belousov
- by Hany Abdulsamad
- by Pascal Klink
- by Simone Parisi
- by Jan Peters
- in Nonfiction
- in Computers and Internet
- in Technology