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--- lctgmeetingsummary20250806 [2025.08.06 09:28] – created Steve Isenberg
+++ lctgmeetingsummary20250806 [2025.08.06 09:31] (current) – Steve Isenberg
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 ===Wordle-Solving Algorithm Optimization===
-The discussion focused on developing an optimal Wordle-solving algorithm using information theory concepts. The first version of the bot maximized entropy for each guess, achieving an average score of 4.2, but the second version, which considered word frequencies and adjusted its strategy to balance information gain with probability of success, improved to an average score of 3.6. The optimal opening word was found to be ”crane,” and the best-case scenario after two guesses leaves about 10 bits of uncertainty, suggesting that a perfect algorithm could solve Wordle in three guesses on average.
+The discussion focused on developing an optimal Wordle-solving algorithm (bot) using information theory concepts. The first version of the bot maximized entropy for each guess, achieving an average score of 4.2, but the second version, which considered word frequencies and adjusted its strategy to balance information gain with probability of success, improved to an average score of 3.6. The optimal opening word was found to be ”crane,” and the best-case scenario after two guesses leaves about 10 bits of uncertainty, suggesting that a perfect algorithm could solve Wordle in three guesses on average.
 ===Wordle: Mechanics and Human Intuition===