Michael Kuperstein

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A theory and the prototype of a neural controller called INFANT that learns sensory-motor coordination from its own experience are presented. INFANT adapts unforeseen changes in the geometry of the physical motor system and to the location, orientation, shape, and size of objects. It can learn to accurately grasp an elongated object without any information(More)
A theory and computer simulation of a neural controller that learns to move and position a link carrying an unforeseen payload accurately are presented. The neural controller learns adaptive dynamic control from its own experience. It does not use information about link mass, link length, or direction of gravity, and it uses only indirect uncalibrated(More)
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