Wanted to try out reinforcement learning for a few years. Decided to apply this to https://play2048.co as a warm up problem
What it does
A neural network attempts to optimize it's high score at 2048
How I built it
Forked a university assignment codebase that had 2048 in python. Essentially rewrote the entire thing. Wrapped this in an OpenAI gym environment. Used a blog post that applies reinforcement learning to a different OpenAI gym.
Challenges I ran into
Original codebase was more confusing than helpful. Reinforcement learning seems to converge much slower than supervised learning.
Accomplishments that I'm proud of
Getting a clean codebase up. Catching bugs with unit tests. Will be proud if I can get good performance from the neural net.
What I learned
Training difficulty is nontrivial, even for such a simple game / state place.
What's next for RL-asmus
Try using RL to tune bicycle wheels (in real world)