Learning from Limited Demonstrations

  title={Learning from Limited Demonstrations},
  author={Beomjoon Kim and Amir-massoud Farahmand and Joelle Pineau and Doina Precup},
We propose a Learning from Demonstration (LfD) algorithm which leverages expert data, even if they are very few or inaccurate. We achieve this by using both expert data, as well as reinforcement signals gathered through trial-and-error interactions with the environment. The key idea of our approach, Approximate Policy Iteration with Demonstration (APID), is that expert’s suggestions are used to define linear constraints which guide the optimization performed by Approximate Policy Iteration. We… CONTINUE READING
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