Tetris using Deep Q Learning (Reinforcement Learning)

This project is an implementation of a Tetris agent that plays the game using Reinforcement Learning.
The agent uses a Deep Q Network to learn the optimal policy for playing the game and was trained using the OpenAI Gym environment for Tetris, training code is available on Github

Checkout a little demo below of the agent playing the game. Tetris AI