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Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation
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Deep Reinforcement Learning - Fundamentals, Research and Applications (Paperback, 1st ed. 2020)
Loot Price: R4,344
Discovery Miles 43 440
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Deep Reinforcement Learning - Fundamentals, Research and Applications (Paperback, 1st ed. 2020)
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Deep reinforcement learning (DRL) is the combination of
reinforcement learning (RL) and deep learning. It has been able to
solve a wide range of complex decision-making tasks that were
previously out of reach for a machine, and famously contributed to
the success of AlphaGo. Furthermore, it opens up numerous new
applications in domains such as healthcare, robotics, smart grids
and finance. Divided into three main parts, this book provides a
comprehensive and self-contained introduction to DRL. The first
part introduces the foundations of deep learning, reinforcement
learning (RL) and widely used deep RL methods and discusses their
implementation. The second part covers selected DRL research
topics, which are useful for those wanting to specialize in DRL
research. To help readers gain a deep understanding of DRL and
quickly apply the techniques in practice, the third part presents
mass applications, such as the intelligent transportation system
and learning to run, with detailed explanations. The book is
intended for computer science students, both undergraduate and
postgraduate, who would like to learn DRL from scratch, practice
its implementation, and explore the research topics. It also
appeals to engineers and practitioners who do not have strong
machine learning background, but want to quickly understand how DRL
works and use the techniques in their applications.
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