I thought this would be about how you can beat binary search in the 'Guess Who?' game. There's a cool math paper about it [0] and an approachable video by the author. [1]
You can't beat binary search in Guess Who. From the abstract:
>> Instead, the optimal strategy for the player who trails is to make certain bold plays in an attempt catch up.
The reason that's optimal, if you're losing, is that you assume that your opponent, who isn't losing, is going to use binary search. They're going to use binary search because it's the optimal way to find the secret.
Since you're behind, if you also use binary search, both players will progress toward the goal at the same rate, and you'll lose.
Trying to get lucky means that you intentionally play badly in order to get more victories. You're redistributing guesses taken between games in a negative-sum manner - you take more total guesses (because your search strategy is inferior to binary search), but they are unevenly distributed across your games, and in the relatively few games where you perform well above expectation, you can score a victory.
You can't beat binary search in Guess Who. From the abstract:
>> Instead, the optimal strategy for the player who trails is to make certain bold plays in an attempt catch up.
The reason that's optimal, if you're losing, is that you assume that your opponent, who isn't losing, is going to use binary search. They're going to use binary search because it's the optimal way to find the secret.
Since you're behind, if you also use binary search, both players will progress toward the goal at the same rate, and you'll lose.
Trying to get lucky means that you intentionally play badly in order to get more victories. You're redistributing guesses taken between games in a negative-sum manner - you take more total guesses (because your search strategy is inferior to binary search), but they are unevenly distributed across your games, and in the relatively few games where you perform well above expectation, you can score a victory.