Designed and implemented a reinforcement learning agent to play Pokémon FireRed using the PPO algorithm. Trained the agent using visual cues and reward signals derived from emulator RAM data such as battle outcomes, level-ups, and map exploration. Built the training environment using Gymnasium, Stable-Baselines3, and TensorFlow in WSL (Ubuntu). Integrated multi-environment training, reward management, and model checkpointing.