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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
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    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 4: Temporal Difference Learning, SARSA, and Q-Learning
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Citations

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Chapter title
Temporal Difference Learning, SARSA, and Q-Learning
Chapter number 4
Book title
Deep Reinforcement Learning
Published by
Springer, Singapore, January 2019
DOI 10.1007/978-981-13-8285-7_4
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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 40%
Lecturer > Senior Lecturer 1 20%
Student > Ph. D. Student 1 20%
Unknown 1 20%
Readers by discipline Count As %
Computer Science 2 40%
Economics, Econometrics and Finance 1 20%
Engineering 1 20%
Unknown 1 20%

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