A Texas Hold'em poker player based on automated abstraction and real-time equilibrium computation

We demonstrate our game theory-based Texas Hold'em poker player. To overcome the computational difficulties stemming from Texas Hold'em's gigantic game tree, our player uses automated abstraction and real-time equilibrium approximation. Our player solves the first two rounds of the game in a large off-line computation, and solves the last two rounds in a real-time equilibrium approximation. Participants in the demonstration will be able to compete against our opponent and experience first-hand the cognitive abilities of our player. Some of the techniques used by our player, which does not directly incorporate any poker-specific expert knowledge, include such poker techniques as bluffing, slow-playing, check-raising, and semi-bluffing, all techniques normally associated with human play.

• Publication year

  2006

• Venue

  Adaptive Agents and Multi-Agent Systems

• Publication date

  2006-05-08

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1145/1160633.1160911
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Finding equilibria in large sequential games of imperfect information

  2006cited by this paper
• A Competitive Texas Hold'em Poker Player via Automated Abstraction and Real-Time Equilibrium Computation

  2006cited by this paper
• Approximating game-theoretic optimal strategies for full-scale poker

  2003cited by this paper
• The challenge of poker

  2002cited by this paper
• Abstraction Methods for Game Theoretic Poker

  2000cited by this paper
• Representations and Solutions for Game-Theoretic Problems

  1997cited by this paper
• Efficient Computation of Equilibria for Extensive Two-Person Games

  1996cited by this paper
• Efficient Computation of Behavior Strategies

  1996cited by this paper

• Deep Reinforcement Learning for Equilibrium Computation in Multistage Auctions and Contests

  2025cites this paper
• KrwEmd: Revising the Imperfect-Recall Abstraction from Forgetting Everything

  2025cites this paper
• Efficient Subgame Refinement for Extensive-form Games

  2023cites this paper
• World-class interpretable poker

  2022cites this paper
• Scalable sub-game solving for imperfect-information games

  2021cites this paper
• A Review of Incomplete Information Game about Games

  2019cites this paper
• Algorithms for Subgame Abstraction with Applications to Cyber Defense

  2018cites this paper
• Combining Graph Contraction and Strategy Generation for Green Security Games

  2016cites this paper
• Abstraction Methods for Solving Graph-Based Security Games

  2016cites this paper
• Designing Defender Strategies Against Frequent Adversary Interaction

  2015cites this paper
• Defender Strategies In Domains Involving Frequent Adversary Interaction

  2015cites this paper
• Online Monte Carlo Counterfactual Regret Minimization for Search in Imperfect Information Games

  2015cites this paper
• Self-play Monte-Carlo tree search in computer poker

  2014influential citation
• Evaluating public state space abstractions in extensive form games with an application in poker

  2014cites this paper
• Adapting Strategies to Opponent Models in Incomplete Information Games: A Reinforcement Learning Approach for Poker

  2012cites this paper
• Lossy stochastic game abstraction with bounds

  2012influential citation
• Deploying Affect-Inspired Mechanisms to Enhance Agent Decision-Making and Communication

  2012cites this paper
• Building a poker playing agent based on game logs using supervised learning

  2010cites this paper
• Strategy generation in multi-agent imperfect-information pursuit games

  2010cites this paper
• Algorithms for abstracting and solving imperfect information games

  2009cites this paper
• Charles University in Prague Faculty of Mathematics and Physics MASTER THESIS

  2009cites this paper
• Algorithmic game theory and the computation of market equilibria

  2009cites this paper
• Opponent modeling in interesting adversarial environments

  2008cites this paper
• Using Stereotypes to Improve Early-Match Poker Play

  2008cites this paper
• GS3 and Tartanian: game theory-based heads-up limit and no-limit Texas Hold'em poker-playing programs

  2008cites this paper
• Better automated abstraction techniques for imperfect information games, with application to Texas Hold'em poker

  2007cites this paper
• A near-optimal strategy for a heads-up no-limit Texas Hold'em poker tournament

  2007cites this paper
• A Fast Bundle-based Anytime Algorithm for Poker and other Convex Games

  2007cites this paper
• Algorithms for abstracting and solving imperfect information games

  2007cites this paper
• A New Algorithm for Generating Equilibria in Massive Zero-Sum Games

  2007cites this paper
• Gradient-Based Algorithms for Finding Nash Equilibria in Extensive Form Games

  2007cites this paper
• Robust planning in domains with stochastic outcomes, adversaries, and partial observability

  2006cites this paper
• Knowledge vs. Simulation for Bidding in Tarok

  2006cites this paper
• Finding equilibria in large sequential games of imperfect information

  2006cites this paper
• 5 Paranoia versus Overconfidence in Imperfect-Information Games

  year unknowncites this paper
• Learning adversary modeling from games

  year unknowninfluential citation