VPFlow: Value-Predictive Planning with Imperfect World Models for Offline Goal Reaching
This work presents VPFlow, a value-predictive planner that pairs the world models with a one-step flow policy and plans in its noise space via evolutionary search, and demonstrates that value-predictive representations, not exact state prediction, are what offline planning requires.
Yun-Zhe Hu, Dong Xu
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