ADG uses an ambient DDPM to flag corrupted RL transitions, trains a standard DDPM only on the clean subset, then refines the flagged transitions to produce a recovered dataset that improves offline RL policies.
Is conditional generative modeling all you need for decision making? In The Eleventh International Conference on Learning Representations, 2023
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ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning
ADG uses an ambient DDPM to flag corrupted RL transitions, trains a standard DDPM only on the clean subset, then refines the flagged transitions to produce a recovered dataset that improves offline RL policies.