Deep Reinforcement Learning
Mohit Sewak
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Naturwissenschaften, Medizin, Informatik, Technik / Informatik
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.
Kundenbewertungen
Alpha-Go, Actor-Critic, Monte Carlo, A3C, Dynamic Programming, TD Lambda, algorithm analysis and problem complexity, AI Agents, Reinforcement Learning, Temporal Difference Learning, Artificial Intelligence, Deep Learning, Hard Attention, SARSA, Deep Q Learning, Recurrent Attention Model, Attention Mechanism, Deep Mind