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Flow policies are a powerful policy class for continuous-control RL: they represent expressive, multi-modal action distributions, and they train by simple supervised regression — sample improved target actions, then distill.But in online MaxEnt-RL, one question decides everything:🎯 Where should the supervision come from?The usual answer is global importance sampling: sample from the policy, reweight by Q-values, distill. It works only when the proposal can reach high-value regions. In high-dime
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