A unified collection of clean, robust PyTorch implementations of popular deep reinforcement learning algorithms. The repository covers value-based methods (Q-learning, Duel DDQN, PER, C51, Noisy DQN), policy gradient methods (PPO for discrete and continuous spaces), and actor-critic algorithms (DDPG, TD3, SAC, ASL). Each algorithm is organized in separate folders with gymnasium-based training examples.