Robot Learning from Human Teachers. Sonia Chernova
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Robot Learning from Human Teachers
Synthesis Lectures on Artificial Intelligence and Machine Learning
Editor
Ronald J. Brachman, Yahoo!Labs
William W. Cohen, Carnegie Mellon University
Peter Stone, University of Texas at Austin
Robot Learning from Human Teachers
Sonia Chernova and Andrea L. Thomaz
2014
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Copyright © 2014 by Morgan & Claypool
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher.
Robot Learning from Human Teachers
Sonia Chernova and Andrea L. Thomaz
www.morganclaypool.com
ISBN: 9781627051996 paperback
ISBN: 9781627052009 ebook
DOI 10.2200/S00568ED1V01Y201402AIM028
A Publication in the Morgan & Claypool Publishers series
SYNTHESIS LECTURES ON ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Lecture #28
Series Editors: Ronald J. Brachman, Yahoo! Labs
William W. Cohen, Carnegie Mellon University
Peter Stone, University of Texas at Austin
Series ISSN
Print 1939-4608 Electronic 1939-4616
Robot Learning from Human Teachers
Sonia Chernova
Worchester Polytechnic Institute
Andrea L. Thomaz
Georgia Institute of Technology
SYNTHESIS LECTURES ON ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING #28
ABSTRACT
Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from nonexpert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus