A normalizing-flow sampling distribution, trained with entropy-regularized reward maximization, improves domain coverage and sim-to-real transfer over Gaussian, beta, and interval-based learned domain randomization.
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Flow-based Domain Randomization for Learning and Sequencing Robotic Skills
A normalizing-flow sampling distribution, trained with entropy-regularized reward maximization, improves domain coverage and sim-to-real transfer over Gaussian, beta, and interval-based learned domain randomization.