Researchers used math to crack Wordle

I crushed wordle within a few days of its popularity entering my sphere. It was pretty easy to brute-force a decision tree minimizing the average number of guesses using a lowly python script and a few days of qpu time.

Don't Wordle[1] is significantly more interesting; I've got a solver but the maximum score takes my lowly python script upwards of a day (per day) to solve using brute force. For now, I solve it with a heuristic that terminates in about 20 minutes. My old wordle solver was useful to find a good but suboptimal tree for identifying the answer in 5 undos or less.

Today:

  Don't Wordle 1491 - SURVIVED
  Hooray! I didn't Wordle today!
  ..... 8089
  ..... 4647
  ..... 2492
  ..... 1026
  .Y... 231
  ..G.. 100
  Undos used: 3

    100 words remaining
  x 10 unused letters
  = 1000 total score

[1] https://dontwordle.com/

I thought this was old news? I remember people making videos about using information theory to solve Wordle back when it was particularly hyped. (After writing this I checked, there's even a 3 blue 1 brown video on this)

My favourite along those lines was solving wordle in 1 guess using the distribution of coloured squares on social media https://www.kaggle.com/code/benhamner/wordle-1-6

This isn't groundbreaking science, sure, but it is a great way to get people interested in a topic. After all, it wouldn't be on Hacker News if the word Wordle wasn't in it. I'm a huge fan of using things like this to teach science, math and engineering.

We started using "Solve 100 Wordles programmatically" as our technical interview, and people _love_ it. They get really into it and have fun. It's pretty easy to do inefficiently, and it's great to watch people build on it and try to improve their scores.

It has two benefits: 1/ everyone clearly understands the problem 2/ people see it as fun rather than a drag.

Hacker News commenter uses grep -i ^.u...$ /usr/share/dict/words | grep -i c | grep -i -v '^..c..$' | grep -i -v '^...c.$' to crack today's Wordle

I'd quickly realised that a set of words which covered most of the alphabet (20 words, leaving b, g, j, q, v, and z excluded) allowed solving virtually all Wordle puzzles. The game quickly lost any challenge.

  wimpy
  crowd
  thank
  fuels

It would be possible to vary word choice based on revealed matches and hits, but if your goal is simply to solve (rather than minimise attempts), the above list works quite well.

>In simulations, their approach solved 99% of Wordle puzzles, while the traditional method solved just 90%.

This seems wrong to me, getting a 98%+ solve rate for Wordle is pretty common.

To paraphrase von Neumann, isn't that how everyone does it?

What I'm interested in is the best starting word. Using Shannon entropy, the paper finds that it is "tares".

Paper: https://orb.binghamton.edu/nejcs/vol8/iss1/6/

plug to my blog post where I did something similar a few years back! https://willbeckman.com/wordle.html :). Not sure if this is an identical solution, but it was a fun little project.