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» Policy Learning for Motor Skills
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NIPS
2003
13 years 9 months ago
Probabilistic Inference in Human Sensorimotor Processing
When we learn a new motor skill, we have to contend with both the variability inherent in our sensors and the task. The sensory uncertainty can be reduced by using information abo...
Konrad P. Körding, Daniel M. Wolpert
NEUROSCIENCE
2001
Springer
14 years 8 days ago
Role of the Cerebellum in Time-Critical Goal-Oriented Behaviour: Anatomical Basis and Control Principle
The Brain is a slow computer yet humans can skillfully play games such as tennis where very fast reactions are required. Of particular interest is the evidence for strategic thinki...
Guido Bugmann
ICRA
2009
IEEE
169views Robotics» more  ICRA 2009»
14 years 2 months ago
Task-level imitation learning using variance-based movement optimization
— Recent advances in the field of humanoid robotics increase the complexity of the tasks that such robots can perform. This makes it increasingly difficult and inconvenient to ...
Manuel Mühlig, Michael Gienger, Sven Hellbach...
CHI
2009
ACM
14 years 8 months ago
Saltate!: a sensor-based system to support dance beginners
We present Saltate!, a wireless prototype system to support beginners of ballroom dancing. Saltate! acquires data from force sensors mounted under the dancers' feet, detects ...
Dieter Drobny, Malte Weiss, Jan Borchers
DAGSTUHL
2003
13 years 9 months ago
Robot Bouncing: On the Synergy Between Neural and Body-Environment Dynamics
The study of how infants strapped in a Jolly Jumper learn to bounce can help clarify how they explore different ways of exploiting the dynamics of their movements. In this paper, ...
Max Lungarella, Luc Berthouze