Reinforcement-Learning-with-Stable-Baselines3-LunarLander-and-Cart-Pole

Developed and trained reinforcement learning models using Stable Baselines3’s PPO and A2C algorithms on the LunarLander-v2 and CartPole environments. The project encompassed setting up training environments, managing model checkpoints, and evaluating performance over multiple episodes. Models were trained extensively, with progress monitored using TensorBoard, and later deployed for real-time gameplay with visual rendering.