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. 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. Fixed Limit is different from Pot Limit, which is different from No Limit. Omaha, Stud and others exist and are widely played. ![]() 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. Here are some aspects which change the correct strategy (and your AI): A cash game is different from a tournament -The number of players makes the decisions different. 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.
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