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Fine-Tuned Reinforcement Learning

Fine-Tuned Reinforcement Learning adapts a pre-trained policy or model to a new task or behavioral objective using reinforcement signals — including human feedback — rather than retraining from scratch. Popularized by RLHF, it is the core technique behind aligning large language models and adapting deep RL agents to specialized environments with minimal additional data.

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Fine-Tuned Reinforcement Learning (Policy Adaptation via Fine-Tuning)

Registro del método taxonómico · ml-model / deep-learning

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