Disagreement-Regularized Imitation Learning for Image-Based Continuous Control with Gaussian and Beta Policies
Purpose: Behavior cloning can accumulate errors when a learned controller visits states outside the demonstrated distribution. This study evaluates whether Disagreement-Regularized Imitation Learning (DRIL), which converts disagreement among cloned policies into a reinforcement-learning reward,…
By Irving Giovani Bronzatti Petrazzini, Eric Aislan AntoneloarXiv cs.LG
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Originally published by arXiv cs.LG on Oct 1, 2026.
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