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ICRA
2005
IEEE

Auto-supervised learning in the Bayesian Programming Framework

10 years 3 months ago
Auto-supervised learning in the Bayesian Programming Framework
Domestic and real world robotics requires continuous learning of new skills and behaviors to interact with humans. Auto-supervised learning, a compromise between supervised and completely unsupervised learning, consist in relying on previous knowledge to acquire new skills. We propose here to realize auto-supervised learning by exploiting statistical regularities in the sensorimotor space of a robot. In our context, it corresponds to achieve feature selection in a Bayesian programming framework. We compare several feature selection algorithms and validate them on a real robotic experiment.
Pierre Dangauthier, Pierre Bessière, Anne S
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where ICRA
Authors Pierre Dangauthier, Pierre Bessière, Anne Spalanzani
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