Most Important Fundamental Rule of Poker Strategy
Abstract
Poker is a large complex game of imperfect information, which has been singled out as a major AI challenge problem. 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. The strongest agents are based on algorithms for approximating Nash equilibrium strategies, which are stored in massive binary files and unintelligible to humans. A recent line of research has explored approaches for extrapolating knowledge from strong game-theoretic strategies that can be understood by humans. This would be useful when humans are the ultimate decision maker and allow humans to make better decisions from massive algorithmically-generated strategies. 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.
- Publication:
-
arXiv e-prints
- Pub Date:
- June 2019
- arXiv:
- arXiv:1906.09895
- Bibcode:
- 2019arXiv190609895G
- Keywords:
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- Computer Science - Artificial Intelligence;
- Computer Science - Computer Science and Game Theory;
- Computer Science - Machine Learning;
- Economics - Theoretical Economics