I’ve implemented an agent using deep reinforcement learning (with Q-Learning) that plays Tetris (not sure if it plays forever, but it seems to). It makes a decision based on the state that is expected to provide a higher reward in the future (i.e. it’s not greedy, so it will, for example, wait to clear multiple lines instead of a single one).

Here’s a demo

Here’s the source code (made in Python with Keras + Tensorflow)

I appreciate any feedback.