Reinforcement Learning Algorithms Analysis and Applications is popular PDF and ePub book, written by Boris Belousov in 2021-01-02, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Reinforcement Learning Algorithms Analysis and Applications can be Read Online from any device for your convenience.
Reinforcement Learning Algorithms Analysis and Applications Book PDF Summary
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.
Detail Book of Reinforcement Learning Algorithms Analysis and Applications PDF
- Author : Boris Belousov
- Release : 02 January 2021
- Publisher : Springer Nature
- ISBN : 9783030411886
- Genre : Technology & Engineering
- Total Page : 197 pages
- Language : English
- PDF File Size : 17,8 Mb
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