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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 Reinforcement Learning and Markov Decision Processes
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    Chapter 2 Batch Reinforcement Learning
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    Chapter 3 Least-Squares Methods for Policy Iteration
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    Chapter 4 Learning and Using Models
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    Chapter 5 Transfer in Reinforcement Learning: A Framework and a Survey
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    Chapter 6 Sample Complexity Bounds of Exploration
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    Chapter 7 Reinforcement Learning in Continuous State and Action Spaces
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    Chapter 8 Solving Relational and First-Order Logical Markov Decision Processes: A Survey
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    Chapter 9 Hierarchical Approaches
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    Chapter 10 Evolutionary Computation for Reinforcement Learning
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    Chapter 11 Bayesian Reinforcement Learning
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    Chapter 12 Partially Observable Markov Decision Processes
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    Chapter 13 Predictively Defined Representations of State
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    Chapter 14 Game Theory and Multi-agent Reinforcement Learning
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    Chapter 15 Decentralized POMDPs
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    Chapter 16 Psychological and Neuroscientific Connections with Reinforcement Learning
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    Chapter 17 Reinforcement Learning in Games
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    Chapter 18 Reinforcement Learning in Robotics: A Survey
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    Chapter 19 Conclusions, Future Directions and Outlook
Attention for Chapter 11: Bayesian Reinforcement Learning
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Citations

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Summary Dimensions citations
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Chapter title
Bayesian Reinforcement Learning
Chapter number 11
Book title
Reinforcement Learning
Published by
Springer Berlin Heidelberg, January 2012
DOI 10.1007/978-3-642-27645-3_11
Book ISBNs
978-3-64-227644-6, 978-3-64-227645-3
Authors

Nikos Vlassis, Mohammad Ghavamzadeh, Shie Mannor, Pascal Poupart

Editors

Marco Wiering, Martijn van Otterlo

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 2 3%
Canada 2 3%
Brazil 1 1%
Unknown 75 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 21%
Researcher 14 18%
Student > Master 14 18%
Student > Doctoral Student 5 6%
Student > Bachelor 3 4%
Other 11 14%
Unknown 16 20%
Readers by discipline Count As %
Computer Science 26 33%
Engineering 11 14%
Psychology 9 11%
Social Sciences 3 4%
Mathematics 3 4%
Other 9 11%
Unknown 19 24%

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