Although Snowie claims to be GTO, I now realize that I object to the phrase 'GTO' on principle, because it implies that there's a unique equilibrium strategy. Maybe there is, maybe there isn't. Snowie is a neural network that has played a gazillion hands both against itself and against opponents created to try to exploit it. All it does is try to maximise the EV of its strategy against the strategies that it has seen. This probably leads it to play an equilibrium strategy, but unless you're playing a two player zero sum game, there's so much more to it than just finding an equilibrium strategy and claiming it's 'GTO', whatever that means.
I don't really get what you're saying about multiple equilibria. Would you mind explaining that a bit more to a fish like me?
Luckily I've been thinking about this, so here's some examples. Remember, I'm a novice at this, so be nice to me.
Let's consider a 6max table where there are four players playing some rubbishy strategies and two other players who have to decide between two possible strategies, Aggro and Snowie. If they both play the strategy Snowie, they win at 8bb/100 hands, and if they both play Aggro, they win at 4bb/100 hands. If they play different strategies, the player who plays Aggro wins more bb/100 than the player who plays Snowie. Ofc, this is slightly tongue in cheek, because the real situation is astronomically more complex, but it gives you something to think about.
Game 1
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Aggro wins at 6bb/100 hands against Snowie's 2bb/100 hands. In the table the first number is the winrate of the player who chooses a row, and the second the winrate of the player who chooses a column.
If both players play Aggro, switching to Snowie unilaterally will reduce his winrate to 2bb/100 hands. This is therefore an equilibrium strategy pair.
Similarly, if both players play Snowie, they have no incentive to change strategy, so this is also an equilibrium strategy pair.
Voila! Multiple equilibria, as promised.
If they play different strategies, the Snowie player has an incentive to turn Aggro, and vice versa. Where will they jump to? Who knows! That's the tricky point. You need to know about the dynamics of this game when it's played repeatedly to find out what happens. How should we model the dynamics? Good question. Feel free to try to answer.
Game 2
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Let's change the winrates of the players when they play different strategies to 10 and 2bb/100 hands.
If they both start playing like Snowie, they both have an incentive to start playing Aggro. Once they're playing different strategies, the Snowie player has an incentive to start playing Aggro too so that he's not getting pwned any more. In this case (Aggro, Aggro) is the only equilibrium. However, notice that they'd both make more money if they played (Snowie, Snowie). This game is identical to the classical Prisoner's Dillema game. If you've seen this, you'll know that the prisoners would be better off keeping their mouths shut, but the equilibrium strategy is for both to confess.
Game 3
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Finally, let's look at what happens when the winrates are 10 and 6bb/100 hands. Now, if the players start off using the same strategy, they each have an incentive to change. Both (Aggro, Snowie) and (Snowie, Aggro) are equilibrium pairs. This game is identical to the classical Game of Chicken. (Two cars drive head first at each other, and they can Drive On or Swerve.) I know that there's also a mixed equilibrium strategy for this game where each player could play either strategy with some probability. (There may be mixed strategy equilibria for the other games too, but I haven't chekced.)
What do I conclude from this? Well, as I've said before, there's more that game theory can suggest to us than 'play GTO', it's not clear what 'play GTO' even means, and frankly, the whole thing makes my head spin. I'm planning to try to look at some toy dynamic poker games, where I add in some model for how the players switch between strategies, and I think I have an undergraduate student starting a Maths of Poker project soon, so if he's any good he can have a crack at it.