This came up as an pre-interview employment challenge that I did a few months ago. I've uploaded my code here: https://gist.github.com/2242816 https://gist.git

This came up as an pre-interview employment challenge that I did a few months ago. I've uploaded my code here: https://gist.github.com/2242816 https://gist.github.com/2242816. I could make good arguments for both "most likely to be present" and "most information gain", so I implemented a mixed strategy. I calculated the information gain (in bits) and the probability of a correct guess, then used a linear combination of them to determine which letter to guess. Additionally, the weights changed over the course of the game so that correct guesses were valued more as incorrect guesses became more scarce. To determine appropriate weights, I ran a crude Monte Carlo simulation. The final weights I ended up with were 0.60:0.03 with no incorrect guesses and 0.54:0.69 once there aren't any strikes left. (bits information gain : p(correct guess))