[canistel]

Well, Bridge remains unconquered, although it is unclear whether it is because of disinterest or incapability. As I have highlighted before, the day a computer false-cards will be the day. (False-carding - playing a certain card with the primary intention of deceiving the opponents and forcing an error)

[IlikeKitties]

Does Bridge have card draw from a randomized deck? Because that's most likely the issue. I'm facing similar problems when trying to build something that plays Magic The Gathering like games reasonably competent. The combinatorics explosion and dealing with bluffing/hidden knowledge is really a tough nut to crack. My current guess is that you need something like monte carlo reinforcement learning to do it.

Forcing an Error is an especially hard case because in machine vs machine matches both sides would be aware that something could force an error and would therefore not fall for it.

[gsf_emergency]

How about the slightly easier* Poker? OpenAI seem to be mildly interested

https://xcancel.com/polynoamial?lang=en

https://arxiv.org/abs/2301.09159

(To be fair, re (card) games: I'm also only interested in seeing Cyborg-on-Cyborg action. Lee vs a-G almost qualified :)

[Cthulhu_]

I need to ask, when playing against AI players in poker games, are they fair (= work on the same sets of cards, are not aware of your hand) or do they get to cheat?

(I played a MTG game years ago and it was not fair, the opponent's deck was not shuffled but they always had cards that provided a certain experience)

[evandijk70]

They are indeed fair. The strongest poker bots are not AI in the way it is commonly defined. From my understanding they calculate the nash-equilibrium for a simplified game and extrapolate that to the full game.