Reinforcement learning is a type of machine learning that allows an agent to learn how to behave in an environment by interacting with it and receiving rewards or punishments for its actions. The agent learns to take actions that maximize its rewards and minimize its punishments, and it does this by updating its policy, which is a function that maps states of the environment to actions.
Reinforcement learning is a powerful tool that has been used to solve a wide variety of problems, including playing games, controlling robots, and managing financial portfolios. It is a relatively new field, but it has already had a major impact on many different areas of computer science and artificial intelligence.
