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Introduction
Reinforcement Learning from Human Feedback (RLHF) is a powerful technique that has become instrumental in aligning large language models (LLMs) and other AI agents with human preferences, values, and instructions. While traditional reinforcement learning relies on carefully engineered reward functions or simulated environments, RLHF addresses the challenge of specifying complex, subjective objectives programmatically by directly incorporating human judgment into the
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