ContraDICE learns policies that imitate expert behavior while repelling undesirable demonstrations via a difference-of-KL objective that is convex when the expert weight dominates.
Ls-iq: Implicit reward regularization for inverse reinforcement learning
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Learning What to Do and What Not To Do: Offline Imitation from Expert and Undesirable Demonstrations
ContraDICE learns policies that imitate expert behavior while repelling undesirable demonstrations via a difference-of-KL objective that is convex when the expert weight dominates.