A very basic python based GTO Texas Hold'em poker solver for people who want to understand the basics of the game and the theoretical approach behind optimal play
This project represents a study on Game Theory Optimal (GTO) strategy applied to No-Limit Texas Hold'em Poker, with a focus on the development and analysis of a Python-based Poker solver. The research question guiding this project is: "How can a GTO solver for No-Limit Texas Hold'em Poker be developed and what are the key concepts involved in such a solver and in GTO poker?"
POSSIBLE IMPROVEMENTS
The Equity Array class can definetely be optimized, it is slow and inefficient. A possible solution could be to save the analysis of the hand and board as a file so that calculations won't have to be reiterated every time one runs the algorithm.
EXTRA ALGORITHMS AND CONCEPTS TO IMPLEMENT
Exploitative Play Blockers Opponent Modeling and Opponent Modeling Algorithms Counterfactual Regret Minimization (CRM) Algorithm Independent Chip Model (ICM)