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, impr