Group project consisting of nine members creating a Game Theory Optimal (GTO) poker solver that computes balanced strategies for Texas Hold’em using algorithmic game theory and optimization techniques. The solver analyzes various in-game scenarios, such as preflop and postflop decisions, to determine equilibrium strategies that cannot be exploited by opponents. By integrating Monte Carlo simulations and recursive counterfactual regret minimization (CFR), the project demonstrates how computational models can mimic professional-level poker decision-making. Ultimately, the goal is to create a user-friendly interface for visualizing optimal strategies and understanding GTO play dynamics.
Adrienne Yahiro 