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You're reading from  Mastering Reinforcement Learning with Python

Product typeBook
Published inDec 2020
Reading LevelBeginner
PublisherPackt
ISBN-139781838644147
Edition1st Edition
Languages
Python
Tools
PyTorch
Concepts
Reinforcement Learning
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Author (1)
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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Extensions to DQN: Rainbow

The Rainbow improvements bring in significant performance boost over the vanilla DQN and they have become standard in most Q-learning implementations. In this section, we discuss what those improvements are, how they help, and what their relative importance are. At the end, we talk how DQN and these extensions collectively overcome the deadly triad.

The extensions

There are six extensions to DQN included in the Rainbow algorithm. These are: i) double Q-learning, ii) prioritized replay, iii) dueling networks, iv) multi-step learning, v) distributional RL, and iv) noisy nets. Let's start describing them with double Q-learning.

Double Q-learning

One of the well-known issues in Q-learning is that the Q-value estimates we obtain during learning is higher than the true Q-values because of the maximization operation . This phenomenon is called maximization bias, and the reason we run into it is that we do a maximization operation over noisy observations...

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Mastering Reinforcement Learning with Python
Published in: Dec 2020Publisher: PacktISBN-13: 9781838644147
© 2020 Packt Publishing Limited All Rights Reserved

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

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