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Repeatability of Real World Training Experiments: A Case Study
Authors:Dean F. Hougen  Paul E. Rybski  Maria Gini
Affiliation:(1) Department of Computer Science and Engineering, University of Minnesota, 200 Union St. S.E., Minneapolis, MN, 55455-0159
Abstract:We present a case study of reinforcement learning on a real robot that learns how to back up a trailer and discuss the lessons learned about the importance of proper experimental procedure and design. We identify areas of particular concern to the experimental robotics community at large. In particular, we address concerns pertinent to robotics simulation research, implementing learning algorithms on real robotic hardware, and the difficulties involved with transferring research between the two.
Keywords:mobile robotics  reinforcement learning  artificial neural networks  simulation  real world
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