Machine Learning with Robotics

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Project Title	Author / Institution
CSCI 4155/6505_ (Weblink)	Thomas Trappenberg / Dalhousie University, Halifax, Canada

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Course Description

This course discusses learning theories and demonstrates these strategies with robots. The topics include su- pervised learning, in particular maximum likelihood estimation in stochastic models and statistical learning theory including support vector machines, unsupervised learning which inclused generative models, expecta- tion maximization, and Bolzmann machines, and reinforcement learning including Markov decision processes and temporal difference learning. The course includes introductins to the MATLAB programming environ- ment, a refresher of basic probability theory, and the use of a robotics environment.

 Course material including an introduction to the RWTH - Mindstorms NXT Toolbox (chapter 4).