Reinforcement Learning (RL)

Reinforcement learning (RL) is a type of machine learning in which a software agent works in a specific environment to maximise rewards. The agent, which makes decisions and executes actions, learns by interacting with the environment and receives feedback in the form of rewards or penalties. Through trial and error, the agent develops strategies to select the best actions and maximise rewards. RL is used in various fields such as robotics, game development and business process optimisation to learn adaptive and intelligent behaviours.