A collection of concise implementations of classic reinforcement learning algorithms including REINFORCE, Actor-Critic, DQN, PPO, DDPG, A3C, ACER, and SAC. Each algorithm is contained in a single file under 150 lines and can be trained on CartPole-v1 without GPU. The repository serves as a learning resource for understanding RL algorithm mechanics by providing readable, self-contained code.