Analysis and Design of Machine Learning Techniques

Evolutionary Solutions for Regression, Prediction, and Control Problems

Authors: Stalph, Patrick

  • Publication in the field of technical sciences

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About this book

Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills? The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain – at least to some extent. Therefore three suitable machine learning algorithms are selected – algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the applicability of the approach, while the biological plausibility is discussed in retrospect.

About the authors

Patrick Stalph was a Ph.D. student at the chair of Cognitive Modeling, which is led by Prof. Butz at the University of Tübingen.

Table of contents (10 chapters)

  • Introduction and Motivation

    Stalph, Patrick

    Pages 1-8

  • Introduction to Function Approximation and Regression

    Stalph, Patrick

    Pages 11-28

  • Elementary Features of Local Learning Algorithms

    Stalph, Patrick

    Pages 29-39

  • Algorithmic Description of XCSF

    Stalph, Patrick

    Pages 41-53

  • How and Why XCSF works

    Stalph, Patrick

    Pages 57-62

Buy this book

eBook $74.99
price for USA (gross)
  • ISBN 978-3-658-04937-9
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $99.00
price for USA
  • ISBN 978-3-658-04936-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Analysis and Design of Machine Learning Techniques
Book Subtitle
Evolutionary Solutions for Regression, Prediction, and Control Problems
Authors
Copyright
2014
Publisher
Springer Vieweg
Copyright Holder
Springer Fachmedien Wiesbaden
eBook ISBN
978-3-658-04937-9
DOI
10.1007/978-3-658-04937-9
Softcover ISBN
978-3-658-04936-2
Edition Number
1
Number of Pages
XIX, 155
Number of Illustrations and Tables
62 b/w illustrations
Topics