# Finding the optimal human strategy for Wordle using maximum correct letter probabilities and reinforcement learning

arXiv: https://arxiv.org/abs/2202.00557 · HTML: https://mlsanity.com/paper/2202.00557/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 8 references that are in the map.
- First posted on arXiv 1 Feb 2022.

## Builds on (most cited first, 3 of 3)

- [Playing Atari with Deep Reinforcement Learning](https://mlsanity.com/paper/1312.5602/) (2013)
- [OpenAI Gym](https://mlsanity.com/paper/1606.01540/) (2016)
- [Dota 2 with Large Scale Deep Reinforcement Learning](https://mlsanity.com/paper/1912.06680/) (2019)

## Built on by (most cited first, 4 of 4)

- [Non Verbis, Sed Rebus: Large Language Models are Weak Solvers of Italian Rebuses](https://mlsanity.com/paper/2408.00584/) (2024)
- [Selecting Seed Words for Wordle using Character Statistics](https://mlsanity.com/paper/2202.03457/) (2022)
- [Using Wordle for Learning to Design and Compare Strategies](https://mlsanity.com/paper/2205.11225/) (2022)
- [Explore the difficulty of words and its influential attributes based on the Wordle game](https://mlsanity.com/paper/2305.03502/) (2023)

## Abstract (arXiv)

Wordle is an online word puzzle game that gained viral popularity in January 2022. The goal is to guess a hidden five letter word. After each guess, the player gains information about whether the letters they guessed are present in the word, and whether they are in the correct position. Numerous blogs have suggested guessing strategies and starting word lists that improve the chance of winning. Optimized algorithms can win 100% of games within five of the six allowed trials. However, it is infeasible for human players to use these algorithms due to an inability to perfectly recall all known 5-letter words and perform complex calculations that optimize information gain. Here, we present two different methods for choosing starting words along with a framework for discovering the optimal human strategy based on reinforcement learning. Human Wordle players can use the rules we discover to optimize their chance of winning.