Recent Advances in Reinforcement Learning

Editors: Kaelbling, Leslie Pack (Ed.)

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About this book

Recent Advances in Reinforcement Learning addresses current research in an exciting area that is gaining a great deal of popularity in the Artificial Intelligence and Neural Network communities.
Reinforcement learning has become a primary paradigm of machine learning. It applies to problems in which an agent (such as a robot, a process controller, or an information-retrieval engine) has to learn how to behave given only information about the success of its current actions. This book is a collection of important papers that address topics including the theoretical foundations of dynamic programming approaches, the role of prior knowledge, and methods for improving performance of reinforcement-learning techniques. These papers build on previous work and will form an important resource for students and researchers in the area.
Recent Advances in Reinforcement Learning is an edited volume of peer-reviewed original research comprising twelve invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 22, Numbers 1, 2 and 3).

Table of contents (12 chapters)

Table of contents (12 chapters)

Buy this book

eBook $129.00
price for USA in USD
  • ISBN 978-0-585-33656-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • Immediate eBook download after purchase and usable on all devices
  • Bulk discounts available
Hardcover $169.00
price for USA in USD
Softcover $169.00
price for USA in USD
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Bibliographic Information

Bibliographic Information
Book Title
Recent Advances in Reinforcement Learning
Editors
  • Leslie Pack Kaelbling
Copyright
1996
Publisher
Springer US
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-0-585-33656-5
DOI
10.1007/b102434
Hardcover ISBN
978-0-7923-9705-2
Softcover ISBN
978-1-4419-5160-1
Edition Number
1
Number of Pages
IV, 292
Topics