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Goal-Conditioned Policy

Robot LearningPolicy

A policy trained to reach arbitrary goal states, where the goal is provided as an input alongside the current observation. Goals can be specified as target images, coordinates, object configurations, or language descriptions. Goal-conditioned policies enable a single model to execute many tasks by varying the goal, rather than training separate policies per task.

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