EAN: 9783658049362

ANALYSIS AND DESIGN OF MACHINE LEARNING TECHNIQ...

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.

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