Deep Reinforcement Learning
Frontiers of Artificial Intelligence
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Beschreibung
This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in a number of applications. The book not only equips readers with an understanding of multiple advanced and innovative algorithms, but also prepares them to implement systems such as those created by Google Deep Mind in actual code.
This book is intended for readers who want to both understand and apply advanced concepts in a field that combines the best of two worlds – deep learning and reinforcement learning – to tap the potential of ‘advanced artificial intelligence’ for creating real-world applications and game-winning algorithms.
This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in a number of applications. The book not only equips readers with an understanding of multiple advanced and innovative algorithms, but also prepares them to implement systems such as those created by Google Deep Mind in actual code.
This book is intended for readers who want to both understand and apply advanced concepts in a field that combines the best of two worlds – deep learning and reinforcement learning – to tap the potential of ‘advanced artificial intelligence’ for creating real-world applications and game-winning algorithms.
Presents comprehensive insights into advanced deep learning concepts like the ‘hard attention mechanism’ Introduces algorithms that are slated to become the future of artificial intelligence Allows readers to gain an understanding of algorithms such as TD Learning and Deep Q Learning, and Asynchronous Advantage Actor-Critic Models
Autor*in
Mohit Sewak
Themen in »Deep Reinforcement Learning«
Reinforcement Learning Deep Learning Deep Q Learning A3C Actor-Critic Deep Mind AI Agents Alpha-Go Attention Mechanism Temporal Difference Learning TD Lambda SARSA Hard Attention Recurrent Attention Model Dynamic Programming