the incomprehensible challenge of poker
When reading in Nature about two deep learning algorithms winning at a version of poker within a few weeks of difference, I came back to my “usual” wonder about poker, as I cannot understand it as a game. (Although I can see the point, albeit dubious, in playing to win money.) And [definitely] correlatively do not understand the difficulty in building an AI that plays the game. [I know, I know nothing!]
April 6, 2017 at 10:02 am
Dear Xian,
This cool blog post helped me understand some of it: http://www.sirlin.net/articles/solvability
In a nutshell, part of the draw and complexity of poker is that playing the Nash-equilibrium solution is not actually what you want to do, because your opponent is not perfect. You want to detect how your opponent strays from optimality and punish his deviations.*
Furthermore, since your opponent is also trying to do that, you also want to appear to have deviations from optimality so that you can punish his reactions.
Guillaume
April 6, 2017 at 2:46 pm
Merci Guillaume, this is most helpful!!!