Studies in Computational Intelligence

TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains

Authors: Hester, Todd

  • Latest research on Temporal Difference Reinforcement Learning for Robots
  • Focuses on applying Reinforcement Learning to real-world problems, particularly learning on robots
  • Presents the model-based Reinforcement Learning algorithm developed by the authors group
  • Written by an expert in the field
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About this book

This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time.

Robots have the potential to solve many problems in society, because of their ability to work in dangerous places doing necessary jobs that no one wants or is able to do. One barrier to their widespread deployment is that they are mainly limited to tasks where it is possible to hand-program behaviors for every situation that may be encountered. For robots to meet their potential, they need methods that enable them to learn and adapt to novel situations that they were not programmed for. Reinforcement learning (RL) is a paradigm for learning sequential decision making processes and could solve the problems of learning and adaptation on robots. This book identifies four key challenges that must be addressed for an RL algorithm to be practical for robotic control tasks. These RL for Robotics Challenges are: 1) it must learn in very few samples; 2) it must learn in domains with continuous state features; 3) it must handle sensor and/or actuator delays; and 4) it should continually select actions in real time. This book focuses on addressing all four of these challenges. In particular, this book is focused on time-constrained domains where the first challenge is critically important. In these domains, the agent’s lifetime is not long enough for it to explore the domains thoroughly, and it must learn in very few samples.

Table of contents (8 chapters)

Buy this book

eBook $99.00
price for USA (gross)
  • ISBN 978-3-319-01168-4
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA
  • ISBN 978-3-319-01167-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover n/a
  • ISBN 978-3-319-37510-6
  • Free shipping for individuals worldwide
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains
Authors
Series Title
Studies in Computational Intelligence
Series Volume
503
Copyright
2013
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-01168-4
DOI
10.1007/978-3-319-01168-4
Hardcover ISBN
978-3-319-01167-7
Softcover ISBN
978-3-319-37510-6
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XIV, 165
Number of Illustrations and Tables
55 illustrations in colour
Topics