Go to main content

Data mining for social robotics [electronic resource] : toward autonomously social robots / Yasser Mohammad, Toyoaki Nishida.

Mohammad, Yasser, author.; Nishida, T. (Toyoaki), author.
2015
QA76.9.D343
Available Online
Formats
Format
BibTeX
MARCXML
TextMARC
MARC
DublinCore
EndNote
NLM
RefWorks
RIS
Add to Basket
Cite
Citation

Linked e-resources

Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks

Details

Title
Data mining for social robotics [electronic resource] : toward autonomously social robots / Yasser Mohammad, Toyoaki Nishida.
Author
Mohammad, Yasser, author.
ISBN
9783319252322 electronic book
3319252321 electronic book
9783319252308
DOI
https://doi.org/10.1007/978-3-319-25232-2
Published
Cham : Springer, 2015.
Language
English
Description
1 online resource (xii, 328 pages) : color illustrations.
Item Number
10.1007/978-3-319-25232-2 doi
Call Number
QA76.9.D343
Dewey Decimal Classification
006.3/12
Summary
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. .
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 11, 2016).
Added Author
Nishida, T. (Toyoaki), author.
Series
Advanced information and knowledge processing.
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
Preface
Introduction
Part I: Time Series Mining
Mining Time-Series Data
Change Point Discovery
Motif Discovery
Causality Analysis
Part II: Autonomously Social Robots
Introduction to Social Robotics
Imitation and Social Robotics
Theoretical Foundations
The Embodied Interactive Control Architecture
Interacting Naturally
Interaction Learning through Imitation
Fluid Imitation
Learning through Demonstration
Conclusion
Index.

Browse Subjects

Show more subjects...

Statistics

from
to
Export