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Deep Reinforcement Learning

Overview of attention for book
Cover of 'Deep Reinforcement Learning'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction to Reinforcement Learning
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    Chapter 2 Mathematical and Algorithmic Understanding of Reinforcement Learning
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    Chapter 3 Coding the Environment and MDP Solution
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    Chapter 4 Temporal Difference Learning, SARSA, and Q-Learning
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    Chapter 5 Q-Learning in Code
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    Chapter 6 Introduction to Deep Learning
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    Chapter 7 Implementation Resources
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    Chapter 8 Deep Q Network (DQN), Double DQN, and Dueling DQN
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    Chapter 9 Double DQN in Code
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    Chapter 10 Policy-Based Reinforcement Learning Approaches
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    Chapter 11 Actor-Critic Models and the A3C
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    Chapter 12 A3C in Code
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    Chapter 13 Deterministic Policy Gradient and the DDPG
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    Chapter 14 DDPG in Code
Attention for Chapter 1: Introduction to Reinforcement Learning
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Citations

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183 Dimensions

Readers on

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118 Mendeley
Summary Dimensions citations
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Chapter title
Introduction to Reinforcement Learning
Chapter number 1
Book title
Deep Reinforcement Learning
Published by
Springer, Singapore, January 2019
DOI 10.1007/978-981-13-8285-7_1
Book ISBNs
978-9-81-138284-0, 978-9-81-138285-7
Authors

Mohit Sewak

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 118 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 21%
Student > Master 16 14%
Researcher 14 12%
Student > Bachelor 12 10%
Student > Doctoral Student 6 5%
Other 10 8%
Unknown 35 30%
Readers by discipline Count As %
Computer Science 35 30%
Engineering 20 17%
Psychology 4 3%
Neuroscience 3 3%
Business, Management and Accounting 3 3%
Other 15 13%
Unknown 38 32%

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