Reinforcement Learning RL Reinforcement Learning (RL) is a subset of machine learning that enables an artificial system, or agent, to optimize its behavior in a given environment by learning from feedback signals, such as rewards or punishments. The goal is to maximize the cumulative reward received, which is determined by a reward function representing the system's objectives (e.g., answering legal questions, drafting legal documents).