Data Mining for Social Robots: Toward Autonomously Social Robots - Rilegato

Libro 49 di 66: Advanced Information and Knowledge Processing

Mohammad, Yasser; Nishida, Toyoaki

 
9783319252308: Data Mining for Social Robots: Toward Autonomously Social Robots

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Dalla quarta di copertina

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.  

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Altre edizioni note dello stesso titolo

9783319797557: Data Mining for Social Robotics: Toward Autonomously Social Robots

Edizione in evidenza

ISBN 10:  3319797557 ISBN 13:  9783319797557
Casa editrice: Springer, 2018
Brossura