Data Mining for Social Robotics: Toward Autonomously Social Robots

✍ Scribed by Yasser Mohammad, Toyoaki Nishida (auth.)

• Publisher: Springer International Publishing
• Year: 2015
• Tongue: English
• Leaves: 330
• Series: Advanced Information and Knowledge Processing
• Edition: 1
• Category: Library

✦ 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.

✦ Table of Contents

Front Matter....Pages i-xii
Introduction....Pages 1-31
Front Matter....Pages 33-33
Mining Time-Series Data....Pages 35-83
Change Point Discovery....Pages 85-108
Motif Discovery....Pages 109-148
Causality Analysis....Pages 149-167
Front Matter....Pages 169-169
Introduction to Social Robotics....Pages 171-191
Imitation and Social Robotics....Pages 193-206
Theoretical Foundations....Pages 207-228
The Embodied Interactive Control Architecture....Pages 229-244
Interacting Naturally....Pages 245-253
Interaction Learning Through Imitation....Pages 255-273
Fluid Imitation....Pages 275-291
Learning from Demonstration....Pages 293-317
Conclusion....Pages 319-323
Back Matter....Pages 325-328

✦ Subjects

Data Mining and Knowledge Discovery; Artificial Intelligence (incl. Robotics)