Description

GTP addresses the tension between efficient inference and long-horizon reasoning by using a generative diffusion model as a proposal distribution for action sequences. It samples candidate trajectories and refines them using learned dynamics, reward, and value models, achieving state-of-the-art results in continuous control and robotic manipulation tasks.

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