Notes by Lex Toumbourou

Reinforcement Learning (RL) is a branch of machine learning where software agents learn to perform goal-oriented actions through a process of trial and error. They interact with an environment that provides feedback in the form of rewards or penalties based on their actions, shaping their behavior (known as a "policy") to achieve the desired objective.