Counterfactual Regret Minimization for a simplified version of Texas Hold'em poker
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Updated
Oct 29, 2020 - C++
Counterfactual Regret Minimization for a simplified version of Texas Hold'em poker
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A GTO solver for Spin & Go poker variant
This project is a heads-up no-limit Texas Hold’em solver designed to compute GTO strategies. It leverages CFR with efficient abstractions, allowing scalable strategy computation and analysis. The solver supports range input, action abstraction, and real-time decision-making, making it suitable for both research and practical gameplay analysis
A Monte Carlo CFR solver for All-In or Fold poker, computing approximate Nash-equilibrium strategies efficiently
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