Data Mining for Social Robotics: Toward Autonomously Social Robots (Advanced Information and Knowledge Processing) - Hardcover

Book 49 of 66: Advanced Information and Knowledge Processing

Mohammad, Yasser; Nishida, Toyoaki

 
9783319252308: Data Mining for Social Robotics: Toward Autonomously Social Robots (Advanced Information and Knowledge Processing)
Hardcover
ISBN 10: 3319252305 ISBN 13: 9783319252308
Publisher: Springer, 2016

Synopsis

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.

"synopsis" may belong to another edition of this title.

From the Back Cover

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.  

"About this title" may belong to another edition of this title.

Publisher
Springer
Publication date
2016
Language
English
ISBN 10 
3319252305
ISBN 13 
9783319252308
Binding
Hardcover
Edition number
1
Number of pages
340

Other Popular Editions of the Same Title

9783319797557: Data Mining for Social Robotics: Toward Autonomously Social Robots (Advanced Information and Knowledge Processing)

Featured Edition

ISBN 10:  3319797557 ISBN 13:  9783319797557
Publisher: Springer, 2018
Softcover