Reinforcement learning is a type of machine learning that involves an agent learning from its environment through trial and error. The agent receives feedback in the form of rewards or punishments for its actions, and over time, it learns to choose actions that maximise its reward. [[Basic Implementation of Reinforcement Learning]]
[[Improvements in Reinforcement Learning]]