OpenAI gym environment for training agents on Wordle
Project description
gym-wordle
A wordle environment for openai/gym
Installation
Install openai-gym
then install this package with
pip install -e .
Usage
import gym
import gym_wordle
env = gym.make('Wordle-v0')
See the docs for more info
Environment details
This environment simulates a game of wordle using a wordle python clone from https://github.com/bellerb/wordle_solver
The action space is a discrete space of 12972 numbers which corresponds to a word from a list of all allowed wordle guesses and answers
The observation space is a dict with the guesses and colors for the current game.
Guesses is an array of shape(5,6) #5 letters and 6 rows
where each element is a number from 0-26 where 0 is ''
and 26 is z
Colors is an array of the same shape, only each element is a number from 0-2 where 0 is a blank (or black or grey) square, 1 is a yellow square, and 2 is a green square
The reward calculation is as follows:
The agent gets 1-6 points depending on how fast the agent guesses the word. For example, getting the word on the first guesses rewards 6 points, getting the word on the second guess rewards 5 points, etc
The agent also is rewarded for colors in the current row (so the current guess). Right now, the agent is rewarded 3 points for each green tile, and 1 point for each yellow tile. No points are giving for grey tiles
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