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GEM-MPC: Balancing Exploration and Exploitation through Expert-Guided Planning
Effective exploration in high-dimensional continuous control remains a central challenge in reinforcement learning. Planning-based methods address this by combining online planning with learned policies and value functions, but their components can become misaligned during training: learned sampling
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