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Robot learning from human teachers / (Record no. 562068)

000 -LEADER
fixed length control field 06631nam a2200721 i 4500
001 - CONTROL NUMBER
control field 6828193
003 - CONTROL NUMBER IDENTIFIER
control field IEEE
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200413152914.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m eo d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cn |||m|||a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140520s2014 caua foab 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781627052009
Qualifying information ebook
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781627051996
Qualifying information paperback
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.2200/S00568ED1V01Y201402AIM028
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number (CaBNVSL)swl00403381
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)880357617
040 ## - CATALOGING SOURCE
Original cataloging agency CaBNVSL
Language of cataloging eng
Description conventions rda
Transcribing agency CaBNVSL
Modifying agency CaBNVSL
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.5
Item number .C447 2014
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR)
Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) MoCl
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Chernova, Sonia.,
Relator term author.
245 10 - TITLE STATEMENT
Title Robot learning from human teachers /
Statement of responsibility, etc. Sonia Chernova, Andrea L. Thomaz.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) :
Name of producer, publisher, distributor, manufacturer Morgan & Claypool,
Date of production, publication, distribution, manufacture, or copyright notice 2014.
300 ## - PHYSICAL DESCRIPTION
Extent 1 PDF (xi, 109 pages) :
Other physical details illustrations.
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term electronic
Source isbdmedia
338 ## - CARRIER TYPE
Carrier type term online resource
Source rdacarrier
490 1# - SERIES STATEMENT
Series statement Synthesis lectures on artificial intelligence and machine learning,
International Standard Serial Number 1939-4616 ;
Volume/sequential designation # 28
538 ## - SYSTEM DETAILS NOTE
System details note Mode of access: World Wide Web.
538 ## - SYSTEM DETAILS NOTE
System details note System requirements: Adobe Acrobat Reader.
500 ## - GENERAL NOTE
General note Part of: Synthesis digital library of engineering and computer science.
500 ## - GENERAL NOTE
General note Series from website.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references (pages 83-107).
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction -- 1.1 Machine learning for end-users -- 1.2 The learning from demonstration pipeline -- 1.3 A note on terminology --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 2. Human social learning -- 2.1 Learning is a part of all activity -- 2.2 Teachers scaffold the learning process -- 2.2.1 Attention direction -- 2.2.2 Dynamic scaffolding -- 2.2.3 Externalizing and modeling metacognition -- 2.3 Role of communication in social learning -- 2.3.1 Expression provides feedback to guide a teacher -- 2.3.2 Asking questions -- 2.4 Implications for the design of robot learners --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3. Modes of interaction with a teacher -- 3.1 The correspondence problem -- 3.2 Learning by doing -- 3.3 Learning from observation -- 3.4 Learning from critique -- 3.5 Design implications --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 4. Learning low-level motion trajectories -- 4.1 State spaces for motion learning -- 4.2 Modeling an action with dynamic movement primitives -- 4.3 Modeling action with probabilistic models -- 4.4 Techniques for handling suboptimal demonstrations --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 5. Learning high-level tasks -- 5.1 State spaces for high-level learning -- 5.2 Learning a mapping function -- 5.3 Learning a task plan -- 5.4 Learning task objectives -- 5.5 Learning task features -- 5.6 Learning frame of reference -- 5.7 Learning object affordances -- 5.8 Techniques for handling suboptimal demonstrations -- 5.9 Discussion and open challenges --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 6. Refining a learned task -- 6.1 Batch vs. incremental learning -- 6.2 Reinforcement learning based methods -- 6.3 Corrective refinement from the teacher -- 6.4 Active learning -- 6.4.1 Label queries -- 6.4.2 Demonstration queries -- 6.4.3 Feature queries -- 6.5 Summary --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 7. Designing and evaluating an LfD study -- 7.1 Experimental design -- 7.2 Evaluating the algorithmic performance -- 7.3 Evaluating the interaction -- 7.3.1 Subjective measures -- 7.3.2 Objective measures -- 7.4 Experimental controls -- 7.5 Experimental protocol -- 7.6 Data analysis -- 7.6.1 Choosing the right statistical tool -- 7.6.2 Drawing conclusions -- 7.7 Additional resources --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 8. Future challenges and opportunities -- 8.1 Real users, real tasks -- 8.2 HRI considerations -- 8.3 Advancing learning through benchmarking and integration -- 8.4 Opportunities -- 8.5 Additional resources --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note Bibliography -- Authors' biographies.
506 1# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Abstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0# - CITATION/REFERENCES NOTE
Name of source Compendex
510 0# - CITATION/REFERENCES NOTE
Name of source INSPEC
510 0# - CITATION/REFERENCES NOTE
Name of source Google scholar
510 0# - CITATION/REFERENCES NOTE
Name of source Google book search
520 3# - SUMMARY, ETC.
Summary, etc. 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 on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Also available in print.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Title from PDF title page (viewed on May 20, 2014).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Robots
General subdivision Control systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Human-robot interaction.
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term Learning from Demonstration
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term imitation learning
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term Human-robot Interaction
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Thomaz, Andrea Lockerd.,
Relator term author.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
International Standard Book Number 9781627051996
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Synthesis digital library of engineering and computer science.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Synthesis lectures on artificial intelligence and machine learning ;
Volume/sequential designation # 28.
International Standard Serial Number 1939-4616
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified Abstract with links to resource
Uniform Resource Identifier http://ieeexplore.ieee.org/servlet/opac?bknumber=6828193
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Abstract with links to full text
Uniform Resource Identifier http://dx.doi.org/10.2200/S00568ED1V01Y201402AIM028
Holdings
Withdrawn status Lost status Damaged status Not for loan Permanent Location Current Location Date acquired Barcode Date last seen Price effective from Koha item type
        PK Kelkar Library, IIT Kanpur PK Kelkar Library, IIT Kanpur 2020-04-13 EBKE568 2020-04-13 2020-04-13 E books

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