Locally Weighted Learning
نویسنده
چکیده
Locally Weighted Learning is a class of function approximation techniques, where a prediction is done by using an approximated local model around the current point of interest. This paper gives an general overview on the topic and shows two different solution algorithms. Finally some successful applications of LWL in the field of Robot Learning are presented.
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