The article introduces a novel method, DORAEMON, to address sim-to-real transfer in reinforcement learning. DORAEMON is a constrained optimization problem that maximizes the entropy of the training distribution while retaining…
Continue readingThe research proposes Adaptive Bayesian Domain Randomization via Strategic Fine-tuning (BayRnTune), a method to significantly speed up the learning processes in domain randomization by fine-tuning from previously learned policy. The…
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