The only limiting factor seems to be the need for discretization: in order for the game tree not to branch out uncontrollably, decisions get reduced to things like fold/call/raising 20%/raising 50%/going all-in. I've even seen 6-max Nash equilibrium solvers.
Heads-up no-limit Nash equilibrium solvers have been available for years. The academic work on Poker AI is pretty extensive, so definitely start there. Metacademy is a great resource which compiles lesson plans on popular machine learning topics.įor Beginner questions please try /r/LearnMachineLearning, /r/MLQuestions or įor career related questions, visit /r/cscareerquestions/ Please have a look at our FAQ and Link-Collection Rules For Posts + Research + Discussion + Project + News on Twitter Chat with us on Slack Beginners:
