Data Mining for Social Robotics

Toward Autonomously Social Robots

  • Yasser Mohammad
  • Toyoaki Nishida

Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Yasser Mohammad, Toyoaki Nishida
    Pages 1-31
  3. Time Series Mining

    1. Front Matter
      Pages 33-33
    2. Yasser Mohammad, Toyoaki Nishida
      Pages 35-83
    3. Yasser Mohammad, Toyoaki Nishida
      Pages 85-108
    4. Yasser Mohammad, Toyoaki Nishida
      Pages 109-148
    5. Yasser Mohammad, Toyoaki Nishida
      Pages 149-167
  4. Autonomously Social Robots

    1. Front Matter
      Pages 169-169
    2. Yasser Mohammad, Toyoaki Nishida
      Pages 171-191
    3. Yasser Mohammad, Toyoaki Nishida
      Pages 193-206
    4. Yasser Mohammad, Toyoaki Nishida
      Pages 207-228
    5. Yasser Mohammad, Toyoaki Nishida
      Pages 229-244
    6. Yasser Mohammad, Toyoaki Nishida
      Pages 245-253
    7. Yasser Mohammad, Toyoaki Nishida
      Pages 255-273
    8. Yasser Mohammad, Toyoaki Nishida
      Pages 275-291
    9. Yasser Mohammad, Toyoaki Nishida
      Pages 293-317
    10. Yasser Mohammad, Toyoaki Nishida
      Pages 319-323
  5. Back Matter
    Pages 325-328

About this book

Introduction

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.  

Keywords

Change Point Discovery Constrained Motif Discovery Human Robot Interaction Imitation Learning Social Robotics Data Mining

Authors and affiliations

  • Yasser Mohammad
    • 1
  • Toyoaki Nishida
    • 2
  1. 1.Department of Electrical EngineeringAssiut UniversityKyotoJapan
  2. 2.Kyoto UniversityKyotoJapan

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-25232-2
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-25230-8
  • Online ISBN 978-3-319-25232-2
  • Series Print ISSN 1610-3947
  • Series Online ISSN 2197-8441
  • About this book