2048 Reinforcement Learning

Let's play 2048 with reinforcement learning!

Current status: not better than the random agent

Requirements

Install Python 3 and all its dependencies:

pip3 install -t requirements.txt

1. numpy
2. tensorflow
3. keras
4. h5py

Train and Test

python3 --agent=[TYPE] --model_path=[MODEL] --train --test

Environment

from gym2048 import Gym2048
gym = Gym2048()
env = gym.make()

env.reset()
while True:
    action = env.action_space.sample()
    obervation, reward, done, info = env.step(action)
    env.render()
    if done: break

Play in Console

You can play 2048 with arrow keys:

python3 play.py

from py2048 import Console
console = Console()
console.start()

TODO

• Build a 2048 game with Python
• Wrap 2048 into an OpenAI Gym like environment
• Perform reinforcement learning methods on 2048
• Improve the existing RL methods
• Analyse the training progress of each method