In this project, we chose to train a Q-learning agent to play the Atari Breakout game without using Deep Q Network (DQN). The input comes as video frames representing the game screen at an instant t. We implemented a technique to encode the frames into a much lower dimensional array, so that the agent could be trained on a resource-constrained system. Feel free to read the full report for more details.