Drifting MPC produces a unique distribution over trajectories that trades off data support against optimality and enables efficient receding-horizon planning under unknown dynamics.
A survey on offline reinforcement learning: Taxonomy, review, and open prob- lems
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Receding-Horizon Control via Drifting Models
Drifting MPC produces a unique distribution over trajectories that trades off data support against optimality and enables efficient receding-horizon planning under unknown dynamics.