Rlhf

Reinforcement Learning from Human Feedback (RLHF) is a subfield of reinforcement learning (RL) in artificial intelligence that involves learning from human feedback instead of traditional reward signals. In RLHF, instead of providing a reward function that guides an agent's behavior, a human teacher provides feedback in the form of evaluations, suggestions, or corrections to the agent's actions. This feedback is used to improve the agent's decision-making and behavior.