This project implements AI agents trained via deep reinforcement learning to play the Snake game automatically. It includes two model architectures: a Multi-Layer Perceptron (MLP) agent and a Convolution Neural Network (CNN) agent, with the CNN version achieving higher average scores. Training uses Stable-Baselines3 and PyTorch, with progress tracked via Tensorboard. Pre-trained model weights are provided for testing.