Active Imitation Learning via Reduction to I

@inproceedings{Judah2012ActiveIL,
  title={Active Imitation Learning via Reduction to I},
  author={Kshitij Judah and Alan Fern},
  year={2012}
}
In standard passive imitation learning, the goal is to learn a target policy by passively observing full execution trajectories of it. Unfortunately, generating such trajectories can require substantial expert effort and be impractical in some cases. In this paper, we consider active imitation learning with the goal of reducing this effort by querying the expert about the desired action at individual states, which are selected based on answers to past queries and the learner’s interactions with… CONTINUE READING