This project trains an AI agent using deep reinforcement learning to play Street Fighter II Champion Edition. The agent receives raw RGB pixel data from the game screen as input and learns decision-making policies through interaction with the OpenAI Gym Retro environment. It uses Stable-Baselines3 for training and achieves a 100% win rate against the final boss after overfitting on a save state.