Tuomas Sandholm: Poker and Game Theory | Lex Fridman Podcast #12

In poker, players must reason not only over hidden cards but also over belief distributions about what others know and think, so you cannot just learn a simple state-value function as in Go; strategy and beliefs are co-determined via equilibrium concepts.

The system computed near–Nash-equilibrium strategies over abstracted versions of the massive game tree, avoided reliance on past human data, and proved that purely equilibrium-based play can reach superhuman performance in high-stakes poker.

Both information abstraction (grouping hands by current and future potential) and action abstraction (choosing representative bet sizes) must be carefully constructed; finer abstractions are not always better and can paradoxically yield worse real-game play.

A game-theoretic strategy is unexploitable but may leave money on the table; hybrid approaches start from equilibrium play and selectively adjust in parts of the game tree where data reveal consistent opponent weaknesses, while staying close enough to avoid counter-exploitation.

With more players or non-zero-sum payoffs, multiple equilibria, coordination issues, and collusion (e.g., in bridge or multiway poker) introduce equilibrium selection problems and strategic instability that current techniques only partially address.