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Semantic Action RL

Adapting Generalist Robot Policies with Semantic Reinforcement Learning

Semantic Action RL (SARL) is a UC Berkeley research software/algorithmic tool for adapting generalist robot policies by running reinforcement learning over a vision-language-action model’s language prompts rather than low-level robot actions.

Screenshot of Semantic Action RL website

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