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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 Deep Learning
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    Chapter 2 Introduction to Reinforcement Learning
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    Chapter 3 Taxonomy of Reinforcement Learning Algorithms
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    Chapter 4 Deep Q-Networks
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    Chapter 5 Policy Gradient
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    Chapter 6 Combine Deep Q -Networks with Actor-Critic
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    Chapter 7 Challenges of Reinforcement Learning
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    Chapter 8 Imitation Learning
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    Chapter 9 Integrating Learning and Planning
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    Chapter 10 Hierarchical Reinforcement Learning
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    Chapter 11 Multi-Agent Reinforcement Learning
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    Chapter 12 Parallel Computing
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    Chapter 13 Learning to Run
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    Chapter 14 Robust Image Enhancement
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    Chapter 15 AlphaZero
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    Chapter 16 Robot Learning in Simulation
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    Chapter 17 Arena Platform for Multi-Agent Reinforcement Learning
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    Chapter 18 Tricks of Implementation
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    Chapter 19 Algorithm Table
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    Chapter 20 Algorithm Cheatsheet
Attention for Chapter 2: Introduction to Reinforcement Learning
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Citations

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Chapter title
Introduction to Reinforcement Learning
Chapter number 2
Book title
Deep Reinforcement Learning
Published by
Springer, Singapore, January 2020
DOI 10.1007/978-981-15-4095-0_2
Book ISBNs
978-9-81-154094-3, 978-9-81-154095-0
Authors

Zihan Ding, Yanhua Huang, Hang Yuan, Hao Dong, Ding, Zihan, Huang, Yanhua, Yuan, Hang, Dong, Hao

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 15 1%
United Kingdom 6 <1%
Germany 5 <1%
Netherlands 4 <1%
France 3 <1%
Japan 3 <1%
Spain 2 <1%
Mexico 2 <1%
Saudi Arabia 1 <1%
Other 5 <1%
Unknown 1092 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 294 26%
Student > Master 200 18%
Researcher 130 11%
Student > Bachelor 95 8%
Student > Doctoral Student 57 5%
Other 140 12%
Unknown 222 20%
Readers by discipline Count As %
Computer Science 360 32%
Engineering 220 19%
Psychology 67 6%
Neuroscience 40 4%
Agricultural and Biological Sciences 37 3%
Other 146 13%
Unknown 268 24%

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