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You're reading from  Mastering Reinforcement Learning with Python

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Published inDec 2020
Reading LevelBeginner
PublisherPackt
ISBN-139781838644147
Edition1st Edition
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Enes Bilgin
Enes Bilgin
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Enes Bilgin

Enes Bilgin works as a senior AI engineer and a tech lead in Microsoft's Autonomous Systems division. He is a machine learning and operations research practitioner and researcher with experience in building production systems and models for top tech companies using Python, TensorFlow, and Ray/RLlib. He holds an M.S. and a Ph.D. in systems engineering from Boston University and a B.S. in industrial engineering from Bilkent University. In the past, he has worked as a research scientist at Amazon and as an operations research scientist at AMD. He also held adjunct faculty positions at the McCombs School of Business at the University of Texas at Austin and at the Ingram School of Engineering at Texas State University.
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From tabular Q-learning to deep Q-learning

When we covered the tabular Q-learning method in Chapter 5, Solving the Reinforcement Learning Problem, it should have been obvious that we cannot really extend those methods to most real-life scenarios. Think about an RL problem which uses images as input. A image with three 8-bit color channels would lead to possible images, a number that your calculator won't be able to calculate. For this very reason, we need to use function approximators to represent the value function. Given their success in supervised and unsupervised learning, neural networks / deep learning emerges as the clear choice here. On the other hand, as we mentioned in the introduction, the convergence guarantees of tabular Q-learning fall apart when function approximators come in. This section introduces two deep Q-learning algorithms, the Neural Fitted Q-iteration and online Q-learning, and then discusses what does not go so well with them. With that, we set the...

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Mastering Reinforcement Learning with Python
Published in: Dec 2020Publisher: PacktISBN-13: 9781838644147

Author (1)

author image
Enes Bilgin

Enes Bilgin works as a senior AI engineer and a tech lead in Microsoft's Autonomous Systems division. He is a machine learning and operations research practitioner and researcher with experience in building production systems and models for top tech companies using Python, TensorFlow, and Ray/RLlib. He holds an M.S. and a Ph.D. in systems engineering from Boston University and a B.S. in industrial engineering from Bilkent University. In the past, he has worked as a research scientist at Amazon and as an operations research scientist at AMD. He also held adjunct faculty positions at the McCombs School of Business at the University of Texas at Austin and at the Ingram School of Engineering at Texas State University.
Read more about Enes Bilgin