Cracking Wordle: Machine Learning based Strategies

Efrat Ravid Efrat Ravid
Language: English
video in English
The presentation was given on 2022.06.28 at PyCon Israel 2022 - Conference.

Wordle is an online word game that has gone viral with millions of daily players world-wide. We will consider strategies based on information theory and reinforcement learning, allowing the creation of agents outperforming most human Wordle players.

Have you seen the posts on social media featuring yellow, green and gray boxes? Yes, that’s Wordle, a simple online word game that has gone viral with millions of daily players world-wide.

Though being a simple game, naive automatic solutions do not provide a winning strategy for the game. Following the success of machine learning solvers in games like chess and go, we will dive into Wordle and demonstrate how to program python agents that outperform most human players.

We will implement a strategy based on information theory and a strategy based on reinforcement learning. We will present a Wordle python package for evaluating our agents, which you can later use for evaluating and comparing your own agent.

Finally, we address the question all players are asking: What is the best starter word?