Gentle introduction to the basics of Poker AI

I have written a multi-part series on the concepts and implementation of Counterfactual Regret Minimization (CFR), with Python code and toy example. CFR is at the heart of most advanced Poker AIs including the famed Pluribus

I hope you find it interesting: Steps to building a Poker AI (Part 1)

If there's enough interest I plan to continue the series in some form to talk more about the aspects specific to Texas Hold'em and some more advanced stuff that is necessary to make a strong AI.

Direct links to the other parts:

Part 2: Modelling Imperfect Information Games
Part 3: Regrets and Minimizing Regrets in One-Shot Games
Part 4: Regret matching for Rock-Paper-Scissors in Python
Part 5: Sequential Games, Kuhn Poker and Counterfactual Regrets
Part 6: Beating Kuhn Poker with CFR using Python
Part 7: Exploitability, Multiplayer CFR and 3-player Kuhn Poker

(X-post from r/poker)