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Comment by Laremere | Hacker News Reader

Can you please share the specifics? I'm trying to make my own AI for this game, and would like to compare mine against random play to estimate its strength.

Also, in your listing of your ai beating the random, how are you counting drawn games?

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The current code for board generation is as follows:

  var neutralChances = Random.Range(1, MaxNeutralChances + 1);
  square.GoodChances = Random.Range(MinGoodChances, 20 - neutralChances);
  square.BadChances = 20 - (square.GoodChances + neutralChances);

MaxNeutralChances and MinGoodChances are both set to 6 in the release build. Note that one chance is equal to one face of the die, so 5%. Also, this overload of Random.Range() has an inclusive min value but an exclusive max value.

I guess I didn't include ties in that little blurb I wrote up, but the real results of my 10k trials were around 5:1:11.5 (lose:tie:win) for the AI vs random actor.

Would love to see your AI when it's done! Please shoot me an email if you want. My email is in my profile / in the site footer.

Why an AI? Just for the fun of implementing it (totally valid, just curious)? Given the probabilities of the outcomes couldn't you just "solve" for the best way to play it based on expected value?

If there are 65% and 50% to complete a row in one direction, and a 35% and 20% in another direction, you don't really need AI to tell you which one would be more advantageous to go after?

Yes, I've made what is intended to be a perfect solver (Although it in some testing it's clearly making mistakes, so I have some debugging to do yet). I'm making it because I was nerd sniped into thinking through how to handle some of the trickiness with the solving. It's not an AI in the LLM or machine learning sense, but in the previously common use of the term (eg, deep blue), or in the video game sense.

Very cool! Best of luck working on it!

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