Abstract: Reinforcement learning is an essential branch of machine learning, which continuously tries and errors to find the optimal strategy through the interaction between agents and environments. It emphasizes obtaining feedback in the environment and adjusting behavior based on feedback to maximize cumulative rewards. Reinforcement learning algorithms include Q-learning, SARSA, Deep Q Network (DQN), etc., which have achieved significant results in game AI, autonomous driving, robot control, and other fields.