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As I noted, adversarial wordle shows that no words take 6 guesses and only 2 words take 5 guesses (BOOZY and BOOBY.)

If you removed just 1 of those 2 words (leaving 2312 possible Wordles) all Wordles can be solved in max 4 guesses.

Ignoring the 2 scenarios where your first two "optimal" guesses are the Wordle

X% of the time you have 1 word left (guesses= 3)

Y% of the time you have 2 words left (guesses =3.5)

(100-Y-X)% of the time there is a pool of words left, requiring one more "optimal" guess

And either your optimal guess #3 is the Wordle Z% of the time (guess=3) or there is now one word remaining (guess ≈ 4)

Where Z in this case is just a function of the number of words remaining (ie Y is just a special case of Z)

So you want to maximize X and the weighted average of Z across pools.

By sheer brute force you can do so

1) for each 2 guess combo 2) discard any "suboptimal" combo where for any remaining response state word pool there is no optimal guess #3 (ie not possible to definitively guess in 4 guesses) 3) calculate avg remaining guesses 4) identify optimal word 1 (minimum of sum of step 2 per first guess) 5) within combos with word 1, identify optimal guess 2 for each response state

And the weighted average of step 3 for these combos is the global minimum for Wordle.

I believe this is the algorithm you're after? In this case, we're making a first guess that maximizes the chance we will get 3 guesses instead of 4.

Per this algorithm, optimal guess 1 is RAVED.



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