Quote:
Originally Posted by Hazbuk
Im surprised nobody has mentioned this point. Since its trying to play GTO it will have a set of algorithms it religiously follows, a human aware of these algorithms would easily beat it, thereby making it pointless in those situations.
Rusty has made some really interesting points. And is right imo, poker is incredibly complex and will likely never have a GTO solution. God help us if it does.
It's not really that simple. For one thing, the algorithm only determines the process the model uses to create the optimal formula, and the exact formula would be impossible to reverse engineer unless you had the same model and data set. More importantly though, a truly game theory optimal strategy is not exploitable so the best you could do would be to break even.
I don't know much about game theory beyond the basics, but wouldn't a truly optimal strategy have to be solved by pure math, not using machine learning/simulation? With machine learning or simulations you can only converge to an optimal strategy, you can't actually reach it. Also, current machine learning is really poorly equipped to handle some of the problems that solving the game of poker poses, so I really don't see much progress being made using machine learning without the invention of dramatically different techniques.
As someone who recently got back into poker, I have to say that the recent obsession by poker players with GTO is a bit amusing. As a rule, exploiting the other player's strategy is always going to be more profitable assuming there's a large enough skill difference that it can be done. I'm not saying there's not a place for GTO-style thinking and play in a poker player's arsenal, but its usefulness seems to be overestimated by a lot of players. I find the math/AI part of it an interesting intellectual exercise, but most players would probably be better off, for instance, using empirical evidence from their database to design strategies to exploit other players.
Last edited by Ez MonEz; 11-12-2013 at 04:20 AM.