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Reinforcement Learning

Overview of attention for book
Cover of 'Reinforcement Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: The Challenge of Reinforcement Learning
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    Chapter 2 Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
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    Chapter 3 Practical Issues in Temporal Difference Learning
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    Chapter 4 Technical Note
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    Chapter 5 Self-Improving Reactive Agents Based on Reinforcement Learning, Planning and Teaching
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    Chapter 6 Transfer of Learning by Composing Solutions of Elemental Sequential Tasks
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    Chapter 7 The Convergence of TD(λ) for General λ
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    Chapter 8 A Reinforcement Connectionist Approach to Robot Path Finding in Non-Maze-Like Environments
Attention for Chapter 2: Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
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Chapter title
Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
Chapter number 2
Book title
Reinforcement Learning
Published by
Springer, Boston, MA, January 1992
DOI 10.1007/978-1-4615-3618-5_2
Book ISBNs
978-1-4613-6608-9, 978-1-4615-3618-5
Authors

Ronald J. Williams, Williams, Ronald J.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 20%
Student > Master 12 18%
Researcher 5 8%
Student > Doctoral Student 4 6%
Student > Bachelor 2 3%
Other 9 14%
Unknown 21 32%
Readers by discipline Count As %
Computer Science 24 36%
Engineering 14 21%
Physics and Astronomy 2 3%
Mathematics 1 2%
Decision Sciences 1 2%
Other 3 5%
Unknown 21 32%

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