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Stochastic Policy

Robot LearningRLPolicy

A policy that outputs a probability distribution over actions (rather than a single deterministic action), enabling exploration and handling of aleatoric uncertainty. Gaussian policies (mean + diagonal covariance) are standard in policy gradient RL. Diffusion policies and normalizing flow policies extend to more complex action distributions. Stochastic policies are necessary for maximum entropy RL (SAC).

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