Editors:
Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 233)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (8 chapters)
-
Front Matter
-
Back Matter
About this book
Although its roots can be traced back to the late fifties, the area of robot learning has lately seen a resurgence of interest. The flurry of interest in robot learning has partly been fueled by exciting new work in the areas of reinforcement earning, behavior-based architectures, genetic algorithms, neural networks and the study of artificial life. Robot Learning gives an overview of some of the current research projects in robot learning being carried out at leading universities and research laboratories in the United States. The main research directions in robot learning covered in this book include: reinforcement learning, behavior-based architectures, neural networks, map learning, action models, navigation and guided exploration.
Editors and Affiliations
-
T.J. Watson Research Center, International Business Machines, USA
Jonathan H. Connell, Sridhar Mahadevan
Bibliographic Information
Book Title: Robot Learning
Editors: Jonathan H. Connell, Sridhar Mahadevan
Series Title: The Springer International Series in Engineering and Computer Science
DOI: https://doi.org/10.1007/978-1-4615-3184-5
Publisher: Springer New York, NY
-
eBook Packages: Springer Book Archive
Copyright Information: Kluwer Academic Publishers 1993
Hardcover ISBN: 978-0-7923-9365-8Published: 30 June 1993
Softcover ISBN: 978-1-4613-6396-5Published: 27 September 2012
eBook ISBN: 978-1-4615-3184-5Published: 06 December 2012
Series ISSN: 0893-3405
Edition Number: 1
Number of Pages: XIII, 240
Topics: Robotics and Automation, Control, Robotics, Mechatronics, Artificial Intelligence