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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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