Knowledge- and ambiguity-aware robot learning from corrective and evaluative feedback
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In order to deploy robots that could be adapted by non-expert users, interactive imitation learning (IIL) methods must be flexible regarding the interaction preferences of the teacher and avoid assumptions of perfect teachers (oracles), while considering they ... ...
