Data & IT
Reinforcement Learning Algorithms: Analysis and Applications
Boris Belousov • Hany Abdulsamad • Pascal Klink • Simone Parisi • Jan Peters
Inbunden
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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 Universitt 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.
- Format: Inbunden
- ISBN: 9783030411879
- Språk: Engelska
- Antal sidor: 206
- Utgivningsdatum: 2021-01-03
- Förlag: Springer Nature Switzerland AG