Reinforcement Learning 1

Reinforcement Learning (RL) is a method for training an agent to maximize a cumulative reward signal through interaction with its environment. The agent learns an optimal policy or decision-making mechanism by receiving feedback in the form of rewards or penalties, with the goal of maximizing long-term rewards. RL has significant applications in automatic control, robotics, gaming, and resource management.