Readings & sources.

Poker, Chance and Skill

Alon (2013). Poker, Chance and Skill.

Toy models of Hold'em show skilled players beat weaker ones at rates variance can't explain away forever.

Approximating Game-Theoretic Optimal Strategies for Full-scale Poker

Billings et al. (2003). Approximating GTO Strategies for Full-scale Poker. U. of Alberta.

Abstracted 10¹⁸-node Hold'em down 100 billion× while keeping strategic structure — the blueprint for modern solvers.

Matemáticas en el «Texas Hold'em Poker»: El arte de vencer a la suerte

García Díaz (2014). La Gaceta de la RSME 17(2), 247–271.

Combinatorics, hypergeometric outs, and expected value — the math layer behind every price you pay.

Pseudo-Optimal Solutions to Texas Hold'em with Improved Chance Node Abstraction

Fellows (2007). Pseudo-Optimal Hold'em Solutions. UCSD / AAAI Computer Poker Competition.

Board-card bucketing from empirical strategy structure — ranges aren't arbitrary, they're abstracted information.

Blind Stealing: Experience and Expertise in a Mixed-Strategy Poker Experiment

Van Essen & Wooders (2014). Blind Stealing. UTS Working Paper.

Online experts randomise steal/defend frequencies closer to Nash than novices — experience transfers to the lab.

Tabla de manos iniciales (BSS)

PokerStrategy.com (2010). Starting Hands Chart — NL BSS.

Classic position-tier chart: same hand is raise, call, or fold depending on seat and action before you.

Matemáticas en el «Texas Hold'em Poker»: El arte de vencer a la suerte

García Díaz (2014). La Gaceta de la RSME 17(2), 247–271.

Combinatorics, hypergeometric outs, and expected value — the math layer behind every price you pay.

Exploitability and Game Theory Optimal Play in Poker

Li (2018). Exploitability and GTO Play in Poker. Boletín de Matemáticas.

Single-hand EV maximisation can lose long-run — ranges, implied odds, and balance matter across hands.

Most Important Fundamental Rule of Poker Strategy

Ganzfried & Chiswick (2020). Most Important Fundamental Rule of Poker Strategy. AAAI.

MDF alone is incomplete — integrate range advantage: defend at min(MDF, MDF − ½·RA + ¼).

The Search for GTO: Determining Optimal Poker Strategy Using Linear Programming

Young (2017). The Search for GTO via Linear Programming. College of Wooster.

LP formulations of simplified Hold'em make Nash equilibria concrete — the math behind solver output.

Approximating Game-Theoretic Optimal Strategies for Full-scale Poker

Billings et al. (2003). Approximating GTO Strategies for Full-scale Poker. U. of Alberta.

Abstracted 10¹⁸-node Hold'em down 100 billion× while keeping strategic structure — the blueprint for modern solvers.

A Demonstration of the Polaris Poker System

Bowling et al. (2008). A Demonstration of the Polaris Poker System. U. of Alberta.

Polaris adapts to weak opponents — GTO is the floor, exploitation is the point in imperfect-information games.

Exploitability and Game Theory Optimal Play in Poker

Li (2018). Exploitability and GTO Play in Poker. Boletín de Matemáticas.

Single-hand EV maximisation can lose long-run — ranges, implied odds, and balance matter across hands.

Most Important Fundamental Rule of Poker Strategy

Ganzfried & Chiswick (2020). Most Important Fundamental Rule of Poker Strategy. AAAI.

MDF alone is incomplete — integrate range advantage: defend at min(MDF, MDF − ½·RA + ¼).

Opponent Modelling in Texas Hold'em Poker as the Key for Success

Félix & Reis (2006). Opponent Modelling in Texas Hold'em. FAIA 178.

An observer agent that profiles opponents beats fixed strategies — exploit beats one-size-fits-all GTO.

Beyond Game Theory Optimal: Profit-Maximizing Poker Agents for No-Limit Hold'em

Yi & Yi (2024). Beyond GTO: Profit-Maximizing NLHE Agents.

Build an unexploitable baseline with CFR, then adapt to opponent leaks — exactly the curriculum order.

Pseudo-Optimal Solutions to Texas Hold'em with Improved Chance Node Abstraction

Fellows (2007). Pseudo-Optimal Hold'em Solutions. UCSD / AAAI Computer Poker Competition.

Board-card bucketing from empirical strategy structure — ranges aren't arbitrary, they're abstracted information.

The Search for GTO: Determining Optimal Poker Strategy Using Linear Programming

Young (2017). The Search for GTO via Linear Programming. College of Wooster.

LP formulations of simplified Hold'em make Nash equilibria concrete — the math behind solver output.

Blind Stealing: Experience and Expertise in a Mixed-Strategy Poker Experiment

Van Essen & Wooders (2014). Blind Stealing. UTS Working Paper.

Online experts randomise steal/defend frequencies closer to Nash than novices — experience transfers to the lab.

Tabla de manos iniciales (BSS)

PokerStrategy.com (2010). Starting Hands Chart — NL BSS.

Classic position-tier chart: same hand is raise, call, or fold depending on seat and action before you.

Poker, Chance and Skill

Alon (2013). Poker, Chance and Skill.

Toy models of Hold'em show skilled players beat weaker ones at rates variance can't explain away forever.

Matemáticas en el «Texas Hold'em Poker»: El arte de vencer a la suerte

García Díaz (2014). La Gaceta de la RSME 17(2), 247–271.

Combinatorics, hypergeometric outs, and expected value — the math layer behind every price you pay.

Most Important Fundamental Rule of Poker Strategy

Ganzfried & Chiswick (2020). Most Important Fundamental Rule of Poker Strategy. AAAI.

MDF alone is incomplete — integrate range advantage: defend at min(MDF, MDF − ½·RA + ¼).

Exploitability and Game Theory Optimal Play in Poker

Li (2018). Exploitability and GTO Play in Poker. Boletín de Matemáticas.

Single-hand EV maximisation can lose long-run — ranges, implied odds, and balance matter across hands.

Exploitability and Game Theory Optimal Play in Poker

Li (2018). Exploitability and GTO Play in Poker. Boletín de Matemáticas.

Single-hand EV maximisation can lose long-run — ranges, implied odds, and balance matter across hands.

Most Important Fundamental Rule of Poker Strategy

Ganzfried & Chiswick (2020). Most Important Fundamental Rule of Poker Strategy. AAAI.

MDF alone is incomplete — integrate range advantage: defend at min(MDF, MDF − ½·RA + ¼).