Question

I named it as “AI way” because I’m thinking make Application to play the hangman game without human being interactive.

The scenario is like this:

1. a available word list which would contains hundreds of thousands English word.
2. The Application will pick certain amount of words, e.g 20 from the list.
3. The Application play Hangman against each word until either WON or FAILURE.
   The restriction here is max wrong bad guess.
   26 does not make sense obviously and let’s say 6 for the max wrong guess.

I tried the strategy mentioned at wiki page but it does not work well.
Basically successful rate is about 30%.

Any suggestions / comments regarding strategy as well as which field I should dig in order to find a fair good strategy?

Thanks a lot.

-Simon

PS: A JavaScript implementation which looks fairly well.
(https://github.com/freizl/play-hangman-game)

Answer 1

Updated Idea

1. Download a dictionary of words and put it into some database or structure of your choice
2. When presented with a word, narrow your guesses to words of the same length and perform a letter frequency distribution (you can use a dictionary and/or list collection for fast distribution analysis and sorting)
3. Pick the most common letter from this list
4. If the letter is found, create a regex pattern based on the known letter(s) and the word length and repeat from step 2
5. You should be able to quickly narrow down a single word resulting from your pattern search

For posterity:

Take a look at this wiki page. It includes a table of frequencies of the first letters of words which may help you tune your algorithm.

You could also take into account the fact that if you find a vowel or two in a word the likelihood of finding other vowels will decrease significantly and you should then try more common consonants instead. The example from the wiki page you listed start with E then T and then tries three vowels in a row: A, O and I. The first two letters are missed but once the third letter is found, twice then the process should switch to common consonants and skip trying for more vowels since there will likely be fewer.

Any useful strategies will certainly employ frequency distribution charts on letters and possibly words e.g. some words are very common while others are rarely used so performing a letter frequency distribution on a set of more common words might help… guessing that some words may appear more frequently than other but that depends on your word selection algorithm which might not take into account “common” usage.

You could also build specialized letter frequency tables and possibly even on-the-fly. For example, given the wikipedia h a ngm a n example: You find the letter A twice in a word in two locations 2nd and 6th. You know that the word has seven letters and with a fairly simple reg ex you could isolate the words from a dictionary that match this pattern:

_ a _ _ _ a _

Then perform a letter frequency on that set of words that matches this pattern and use that set for your next guess. Rinse and repeat. I think doing some of those things I mentioned but especially the last will really increase your odds of success.