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Reinforcement Learning Algorithms: Analysis and Applications | 1:a upplagan
- Danskt band, Engelska, 2021
- Författare: Boris Belousov, Hany Abdulsamad
- Betyg:
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Beskrivning
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.
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.
Om denna bok
Reinforcement Learning Algorithms: Analysis and Applications av Boris Belousov och Hany Abdulsamad är en Danskt band bok med 206 sidor på Engelska. Detta är den 1:a upplagan som utgavs 2021 av Springer Nature.
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Produktinformation
Kategori:
Okänd
Bandtyp:
Danskt band
Språk:
Engelska
ISBN:
9783030411879
Upplaga:
1
Utgiven:
2021-01-03
Förlag:
Springer Nature
Sidantal:
206