An OpenAI gym compatible environment for training agents to play Wordle.
User-input demo of the environment
My goal is for a minimalist package that lets you install quickly and get on
with your research. Installation is just a simple call to pip:
$ pip install gym_wordle
In keeping with my desire to have a minimalist package, there are only three major requirements:
numpygymsty, a lovely little package for stylizing text in terminals
The basic flow for training agents with the Wordle-v0 environment is the same
as with gym environments generally:
import gym
import gym_wordle
eng = gym.make("Wordle-v0")
done = False
while not done:
action = ... # RL magic
state, reward, done, info = env.step(action)If you're like millions of other people, you're a Wordle-obsessive in your own
right. I have good news for you! The Wordle-v0 environment currently has an
implemented render method, which allows you to see a human-friendly version
of the game. And it isn't so hard to set up the environment to play for
yourself. Here's an example script:
from gym_wordle.utils import play
play()Coming soon!
Coming soon!
If you decide to use this project in your work, please consider a citation!
@misc{gym_wordle,
author = {Kraemer, David},
title = {An Environment for Reinforcement Learning with Wordle},
year = {2022},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/DavidNKraemer/Gym-Wordle}},
}