HIDI trains a GP-regularized conditional diffusion model to generate high-level subgoals and mixes GP mean selection with diffusion sampling, outperforming HRL baselines on continuous control benchmarks.
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Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals
HIDI trains a GP-regularized conditional diffusion model to generate high-level subgoals and mixes GP mean selection with diffusion sampling, outperforming HRL baselines on continuous control benchmarks.