Algorithms for texas hold em poker11/20/2023 ![]() Using techniques from machine learning we have uncovered a new simple, fundamental rule of poker strategy that leads to a significant improvement in performance over the best prior rule and can also easily be applied by human players. This would be useful when humans are the ultimate decision maker and allow humans to make better decisions from massive algorithmically-generated strategies. When employed in self-play, the average strategy of the players are then guaranteed to converge to a Nash equilibrium. A recent line of research has explored approaches for extrapolating knowledge from strong game-theoretic strategies that can be understood by humans. The strongest agents are based on algorithms for approximating Nash equilibrium strategies, which are stored in massive binary files and unintelligible to humans. Recently there has been a series of breakthroughs culminating in agents that have successfully defeated the strongest human players in two-player no-limit Texas hold 'em. ![]() Download a PDF of the paper titled Most Important Fundamental Rule of Poker Strategy, by Sam Ganzfried and Max Chiswick Download PDF Abstract:Poker is a large complex game of imperfect information, which has been singled out as a major AI challenge problem. 885 - 890 DOI: 10.1126/science.aay2400 AI now masters six-player poker Computer programs have shown superiority over humans in two-player games such as chess, Go, and heads-up, no-limit Texas holdem poker. ![]()
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