I do personally dislike that GTO became the nomenclature , as I prefer "theory-based", since it causes this confusion, but trying to fight it at this point is hopeless because GTO is the search term people are using. And when people say they "play GTO" they usually mean "equilibrium" rather than "optimal against my specific opponents" which is "exploitative".
If you actually watch what the top players advocate for, everyone suggests you want to play exploitatively. However, there's one equilibrium solution and effectively infinite exploitative solutions, so equilibrium is a reasonble starting point to develop a baseline understanding of the mechanics of the game. It's tough to know how much "too much" bluffing is unless you know a baseline.
Furthermore, if you "exploit" people by definition you are opening yourself up to being exploited so you need to be very careful your assumptions are true.
Also, with solvers like piosolver, you can "node lock" (tell a node in the game tree to play like your opponent, rather than an equilibrium way plays), but there's many pitfalls, such as the solver adjusting in very unnatural ways on other nodes to adjust, and it being impractical to "lock" a strategy every node in the tree. There's new ideas called "incentives" which gives the solver an "incentive" to play more like a human would (e.g. calling too much) but these are new ideas still being actively explored.
Rock paper scissors is frequently used to explain GTO but it's not the best example because equilibrium in rock paper scissors will break even against all opponents, but equilibrium poker strategy will actually beat most human poker players, albeit not as much as a maximally exploitative one.
There's two other huge pieces this article glosses over:
1) It's as impossible for a human to play like a computer in poker as in chess - in fact far more impossible, because in poker you need to implement mixed strategies. In chess there's usually a best move, but in poker the optimal solution often involves doing something 30% of the time and something else 70% of the time. The problem is that, not only are there too many situations to memorize all the solutions, but actually implementing the correct frequencies is impossible for a human. Some players like to use "randomizers" like dice at the table, or looking at a clock, but I find that somewhat silly since it still so unlikely you are anywhere near equilbrium.
2) Reading someone's "tells" live is still a thing. While solvers have led to online poker to decline due to widespread "real time assistance", live poker is booming (the 2024 World Series of Poker Main Event just broke the record yet again) , and in person in live poker, people still give off various information about their hand via body language. From the 70s to the early 2000s, people were somewhat obsessed with "tells" as a way to win at poker. Since computers have advanced so much, it's fallen out of favor, but the truth is, both are useful. It's totally mistaken to think that advancement in poker AI , GTO , and solvers have rendered live reads obsolete. In fact, in 2023, Tom Dwan won the biggest pot in televised poker history (3.1 million) and credited a live read to his decision, in a spot where the solver would randomize between a call and a fold.
Yes indeed glad you noticed! Been too addicted to that godforsaken game at points so figured borrow some of its qualities for my studying apps...in general I'm interested in gamification + studying.
https://www.livepokertheory.com
I do personally dislike that GTO became the nomenclature , as I prefer "theory-based", since it causes this confusion, but trying to fight it at this point is hopeless because GTO is the search term people are using. And when people say they "play GTO" they usually mean "equilibrium" rather than "optimal against my specific opponents" which is "exploitative".
If you actually watch what the top players advocate for, everyone suggests you want to play exploitatively. However, there's one equilibrium solution and effectively infinite exploitative solutions, so equilibrium is a reasonble starting point to develop a baseline understanding of the mechanics of the game. It's tough to know how much "too much" bluffing is unless you know a baseline.
Furthermore, if you "exploit" people by definition you are opening yourself up to being exploited so you need to be very careful your assumptions are true.
Also, with solvers like piosolver, you can "node lock" (tell a node in the game tree to play like your opponent, rather than an equilibrium way plays), but there's many pitfalls, such as the solver adjusting in very unnatural ways on other nodes to adjust, and it being impractical to "lock" a strategy every node in the tree. There's new ideas called "incentives" which gives the solver an "incentive" to play more like a human would (e.g. calling too much) but these are new ideas still being actively explored.
Rock paper scissors is frequently used to explain GTO but it's not the best example because equilibrium in rock paper scissors will break even against all opponents, but equilibrium poker strategy will actually beat most human poker players, albeit not as much as a maximally exploitative one.
There's two other huge pieces this article glosses over:
1) It's as impossible for a human to play like a computer in poker as in chess - in fact far more impossible, because in poker you need to implement mixed strategies. In chess there's usually a best move, but in poker the optimal solution often involves doing something 30% of the time and something else 70% of the time. The problem is that, not only are there too many situations to memorize all the solutions, but actually implementing the correct frequencies is impossible for a human. Some players like to use "randomizers" like dice at the table, or looking at a clock, but I find that somewhat silly since it still so unlikely you are anywhere near equilbrium.
2) Reading someone's "tells" live is still a thing. While solvers have led to online poker to decline due to widespread "real time assistance", live poker is booming (the 2024 World Series of Poker Main Event just broke the record yet again) , and in person in live poker, people still give off various information about their hand via body language. From the 70s to the early 2000s, people were somewhat obsessed with "tells" as a way to win at poker. Since computers have advanced so much, it's fallen out of favor, but the truth is, both are useful. It's totally mistaken to think that advancement in poker AI , GTO , and solvers have rendered live reads obsolete. In fact, in 2023, Tom Dwan won the biggest pot in televised poker history (3.1 million) and credited a live read to his decision, in a spot where the solver would randomize between a call and a fold.