Learning on Real Robots from Experience and Simple User feedback

  title={Learning on Real Robots from Experience and Simple User feedback},
  author={P. Quintı́a and Roberto Iglesias and M. A. Rodrı́guez and Carlos V. Regueiro},
In this article we describe a novel algorithm that allows fast and continuous learning on a physical robot working in a real environment. The learning process is never stopped and new knowledge gained from robot-environment interactions can be incorporated into the controller at any time. Our algorithm lets a human observer control the reward given to the robot, hence avoiding the burden of defining a reward function. Despite the highly-non-deterministic reinforcement, through the experimental… CONTINUE READING
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