In reinforcement learning, an agent learns how to interact with an environment to maximize rewards. The agent takes action and receives feedback in the form of rewards or penalties. [[semi-supervised learning]] < [[Hands-on LLMs]]/[[1 Machine Learning Basics]] > [[reinforcement learning from human feedback]]