Data Mining for Social Robotics (Record no. 57556)

000 -LEADER
fixed length control field 03497nam a22005055i 4500
001 - CONTROL NUMBER
control field 978-3-319-25232-2
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112224.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160108s2015 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319252322
-- 978-3-319-25232-2
082 04 - CLASSIFICATION NUMBER
Call Number 006.312
100 1# - AUTHOR NAME
Author Mohammad, Yasser.
245 10 - TITLE STATEMENT
Title Data Mining for Social Robotics
Sub Title Toward Autonomously Social Robots /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2015.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XII, 328 p. 74 illus. in color.
490 1# - SERIES STATEMENT
Series statement Advanced Information and Knowledge Processing,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Preface -- Introduction -- Part I: Time Series Mining -- Mining Time-Series Data -- Change Point Discovery -- Motif Discovery -- Causality Analysis -- Part II: Autonomously Social Robots -- Introduction to Social Robotics -- Imitation and Social Robotics -- Theoretical Foundations -- The Embodied Interactive Control Architecture -- Interacting Naturally -- Interaction Learning through Imitation -- Fluid Imitation -- Learning through Demonstration -- Conclusion -- Index.
520 ## - SUMMARY, ETC.
Summary, etc This book explores an approach to social robotics based solely on autonomous unsupervised techniques and positions it within a structured exposition of related research in psychology, neuroscience, HRI, and data mining. The authors present an autonomous and developmental approach that allows the robot to learn interactive behavior by imitating humans using algorithms from time-series analysis and machine learning. The first part provides a comprehensive and structured introduction to time-series analysis, change point discovery, motif discovery and causality analysis focusing on possible applicability to HRI problems. Detailed explanations of all the algorithms involved are provided with open-source implementations in MATLAB enabling the reader to experiment with them. Imitation and simulation are the key technologies used to attain social behavior autonomously in the proposed approach. Part two gives the reader a wide overview of research in these areas in psychology, and ethology. Based on this background, the authors discuss approaches to endow robots with the ability to autonomously learn how to be social. Data Mining for Social Robots will be essential reading for graduate students and practitioners interested in social and developmental robotics. .
700 1# - AUTHOR 2
Author 2 Nishida, Toyoaki.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-25232-2
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2015.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data mining.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1610-3947
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-- ZDB-2-SCS

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