Reinforcement Learning (RL)

Reinforcement Learning (RL) is a method for training agents to take actions by interacting with an environment to maximize a cumulative reward signal. The agent adjusts its behavior strategy based on feedback in the form of rewards or penalties, aiming to find the optimal policy that can achieve the maximum long-term reward. RL has significant application value in autonomous decision-making systems and can be widely applied in areas such as robot control, game strategy optimization, and resource management.