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Transfer in Reinforcement Learning Domains (Paperback, Softcover reprint of hardcover 1st ed. 2009)
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Transfer in Reinforcement Learning Domains (Paperback, Softcover reprint of hardcover 1st ed. 2009)
Series: Studies in Computational Intelligence, 216
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In reinforcement learning (RL) problems, learning agents
sequentially execute actions with the goal of maximizing a reward
signal. The RL framework has gained popularity with the development
of algorithms capable of mastering increasingly complex problems,
but learning difficult tasks is often slow or infeasible when RL
agents begin with no prior knowledge. The key insight behind
"transfer learning" is that generalization may occur not only
within tasks, but also across tasks. While transfer has been
studied in the psychological literature for many years, the RL
community has only recently begun to investigate the benefits of
transferring knowledge. This book provides an introduction to the
RL transfer problem and discusses methods which demonstrate the
promise of this exciting area of research. The key contributions of
this book are: Definition of the transfer problem in RL domains
Background on RL, sufficient to allow a wide audience to understand
discussed transfer concepts Taxonomy for transfer methods in RL
Survey of existing approaches In-depth presentation of selected
transfer methods Discussion of key open questions By way of the
research presented in this book, the author has established himself
as the pre-eminent worldwide expert on transfer learning in
sequential decision making tasks. A particular strength of the
research is its very thorough and methodical empirical evaluation,
which Matthew presents, motivates, and analyzes clearly in prose
throughout the book. Whether this is your initial introduction to
the concept of transfer learning, or whether you are a practitioner
in the field looking for nuanced details, I trust that you will
find this book to be an enjoyable and enlightening read. Peter
Stone, Associate Professor of Computer Science
General
Imprint: |
Springer-Verlag
|
Country of origin: |
Germany |
Series: |
Studies in Computational Intelligence, 216 |
Release date: |
October 2010 |
First published: |
2009 |
Authors: |
Matthew Taylor
|
Dimensions: |
235 x 155 x 13mm (L x W x T) |
Format: |
Paperback
|
Pages: |
230 |
Edition: |
Softcover reprint of hardcover 1st ed. 2009 |
ISBN-13: |
978-3-642-10186-1 |
Categories: |
Books >
Computing & IT >
Applications of computing >
Artificial intelligence >
General
|
LSN: |
3-642-10186-0 |
Barcode: |
9783642101861 |
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