Abstract
The third part of this work is devoted to simulated robot devices, learning models of their kinematic structure, and using these models for simple directional control tasks such as reaching for objects. Learning is realized by algorithms that mimic brain function at least to some degree. Therefore the framework developed herein could explain how the brain learns motor control. Of course, there is no proof because a concrete implementation in one or the other programming language is far from being comparable to brain imaging results that merely highlight activity in certain regions for certain tasks. Nonetheless, this work tries to make a connection from neuron level (neurobiology) to the functional, cognitive level (psychology).
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© 2014 Springer Fachmedien Wiesbaden
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Stalph, P. (2014). Basics of Kinematic Robot Control. In: Analysis and Design of Machine Learning Techniques. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-04937-9_7
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DOI: https://doi.org/10.1007/978-3-658-04937-9_7
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Publisher Name: Springer Vieweg, Wiesbaden
Print ISBN: 978-3-658-04936-2
Online ISBN: 978-3-658-04937-9
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