Yasser Mohammad

(Author)

Data Mining for Social Robotics: Toward Autonomously Social RobotsHardcover, 10 February 2016

Data Mining for Social Robotics: Toward Autonomously Social Robots
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Part of Series
Advanced Information and Knowledge Processing
Print Length
328 pages
Language
English
Publisher
Springer
Date Published
10 Feb 2016
ISBN-10
3319252305
ISBN-13
9783319252308

Description

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.

Product Details

Authors:
Yasser MohammadToyoaki Nishida
Book Format:
Hardcover
Country of Origin:
NL
Date Published:
10 February 2016
Dimensions:
23.39 x 15.6 x 2.06 cm
ISBN-10:
3319252305
ISBN-13:
9783319252308
Language:
English
Location:
Cham
Pages:
328
Publisher:
Weight:
653.17 gm

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