CFR Poker Solver
Build a Counterfactual Regret Minimization solver from first principles. Play against the algorithms, visualize convergence, and go from Rock-Paper-Scissors to No-Limit Hold'em.
Start Chapter 1Curriculum
Five chapters taking you from zero to a working NLHE solver.
Regret Matching & Nash Equilibrium
The atomic algorithm inside every poker solver, understood through Rock-Paper-Scissors. Play against a learning bot and watch it adapt to your strategy.
Kuhn Poker & CFR
Extend regret matching to sequential games with hidden information. Play Kuhn Poker against Nash Equilibrium and build a full CFR solver.
Leduc Poker & Multi-Street CFR
Community cards, multiple betting rounds, and the emergence of semibluffing. Play against a Nash bot and explore equilibrium strategies.
Abstraction for Real Poker
Card bucketing, action abstraction, and the engineering tricks that make solving NLHE tractable.
Building the NLHE Solver
Putting it all together: CFR+ and Monte Carlo CFR applied to real No-Limit Hold'em subgames.
What You'll Learn
Theory
Nash Equilibrium, the Minimax Theorem, regret minimization, and convergence guarantees with full proofs and citations.
Implementation
Working Python code at every step. Each chapter includes a companion script you can run and modify.
Interactive Demos
Play against the algorithms yourself, visualize convergence, and explore equilibrium strategies in your browser.
Poker Applications
Understand exactly how tools like PIOsolver work under the hood, from regret matching to full NLHE solving.
Who This Is For
This course sits at the intersection of game theory, algorithms, and poker. You'll get the most out of it if you have:
Basic programming skills
Python experience helps for the companion code, but the interactive demos work with no setup.
Comfort with probability
Expected value, probability distributions, and basic linear algebra. Nothing beyond undergraduate level.
Curiosity about poker or game theory
Whether you're a poker player wanting to understand solvers, a CS student studying game theory, or just curious how AI plays poker — this course is for you.