Analysis and Design of Machine Learning Techniques

Evolutionary Solutions for Regression, Prediction, and Control Problems

  • Patrick Stalph

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Patrick Stalph
    Pages 1-8
  3. Background

    1. Front Matter
      Pages 9-9
    2. Patrick Stalph
      Pages 41-53
  4. Analysis and Enhancements of XCSF

    1. Front Matter
      Pages 55-55
    2. Patrick Stalph
      Pages 57-62
    3. Patrick Stalph
      Pages 63-83
  5. Control Applications in Robotics

    1. Front Matter
      Pages 85-85
    2. Patrick Stalph
      Pages 87-100
    3. Patrick Stalph
      Pages 125-135
    4. Patrick Stalph
      Pages 137-143
  6. Back Matter
    Pages 145-155

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.




  • How do humans learn their motor skills
  • Evolutionarymachinelearningalgorithms
  • Applicationtosimulatedrobots


Target Groups

  • Researchers interested in artificial intelligence, cognitive sciences or robotics
  • Roboticists interested in integrating machine learning


About the Author

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


Human Motor Skill Learning Machine Learning Robotics

Authors and affiliations

  • Patrick Stalph
    • 1
  1. 1.Lehrstuhl für kognitive ModellierungUniversität TübingenTübingenGermany

Bibliographic information

  • DOI
  • Copyright Information Springer Fachmedien Wiesbaden 2014
  • Publisher Name Springer Vieweg, Wiesbaden
  • eBook Packages Engineering
  • Print ISBN 978-3-658-04936-2
  • Online ISBN 978-3-658-04937-9
  • Buy this book on publisher's site
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