[Baeocystin]

I am 100% certain that the training of such an AI will result in winning a game without ever building a single city* and 1,000 other exploits before being nerfbatted enough to play a 'real' game.

(That doesn't mean I don't want to see the ridiculousness it comes up with!)

* https://www.youtube.com/watch?v=6CZEEvZqJC0

[lordnacho]

I knew it, I knew it! It would be a Spiffing Brit video.

That guy is a genius at finding exploits in computer games. I don't know how he does it, I think you need to play a fair bit of each game before you find these little corners of the ruleset.

[boppo1]

Idk maybe he uses some sort of fuzzer

[jdietrich]

If you train the model purely based on win rate, sure. Fortunately, we can efficiently use RLHF to train a model to play in a human-like way and give entertaining matches.

[Aerroon]

But wouldn't this be amazing for the developer to fix a lot of edge cases/bugs?

[Baeocystin]

Maybe, maybe not. The stochastic, black-box nature of the current wave of ML systems gives me a gut feeling that using them like this is more of a Monkey's Paw wish granter than useful tool without a lot of refinement first. Time will tell!