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Drift, Then Spread: Learning One-Step Generative Policies for Online Reinforcement Learning
Generative policies offer expressive action distributions for online reinforcement learning (RL), but many diffusion- and flow-based policies require costly iterative sampling. We propose DriftSpread, a one-step generative policy based on Drifting for online maximum-entropy (MaxEnt) RL. To incorpora
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