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I agree that because of, for example rake or table fees for cash games or competition structure for tournament in practice a game theoretically optimal choice may not be the right choice in practical play.

However the situation with an AI powered competitor which uses exploitative play is identical to a human, the GTO play will gradually take their chips at no risk.

It's not that they're optimal but that they've chosen not to be optimal and so that's why they lose money against GTO.

The AI is at least unemotional about this, humans with a "system" easily get tilted by GTO play and throw tantrums. How can it get there with KToff? What kind of idiot bluffs here with no clubs? Well the answer will usually be the one that's taking all your chips, be better. Humans used to seeing exploitable patterns in the play of other humans may mistake ordinary noise in the game for exploitable play in a GTO strategy and then get really angry when it's a mirage.



Right, I see what you're saying, but this is what I'm disputing - in two player games, what you wrote is true, but those properties of Nash equilibria don't generalise.

When there are more players, there can be multiple Nash equilibria, and (unlike the two player case) combinations of equilibrium strategies may no longer be an equilibrium strategy. So it's no longer true that you cannot be exploited, because that depends on other player's strategies too, and you cannot control those.

(See this paper for instance: https://webdocs.cs.ualberta.ca/~games/poker/publications/AAM...)


Yes, I agree that more players makes the theory at least extremely difficult and perhaps imponderable. That paper was interesting, thanks




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