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Award ID contains: 1617590

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  1. ; (, Science)
    In recent years there have been great strides in artificial intelligence (AI), with games often serving as challenge problems, benchmarks, and milestones for progress. Poker has served for decades as such a challenge problem. Past successes in such benchmarks, including poker, have been limited to two-player games. However, poker in particular is traditionally played with more than two players. Multiplayer games present fundamental additional issues beyond those in two-player games, and multiplayer poker is a recognized AI milestone. In this paper we present Pluribus, an AI that we show is stronger than top human professionals in six-player no-limit Texas hold’em poker, the most popular form of poker played by humans. 
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    Full Text Available 
  2. ; (, Games and Economic Behavior)
    Full Text Available 
  3. ; ; ; (, Conference on Neural Information Processing Systems)
    Accepted Manuscript Full Text Available
  4. ; ; (, Management science)
    Accepted Manuscript Full Text Available
  5. ; ; (, International Conference on Machine Learning)
    Accepted Manuscript Full Text Available
  6. ; ; ; (, Mathematical programming)
    Accepted Manuscript Full Text Available
  7. ; ; (, AAAI Workshop on Reinforcement Learning in Games)
    Accepted Manuscript Full Text Available
  8. ; ; ; (, International Conference on Machine Learning)
    Accepted Manuscript Full Text Available
  9. ; ; ; (, AAAI Workshop on Reinforcement Learning in Games)
    Accepted Manuscript Full Text Available
  10. ; ; (, ACM Conference on Economics and Computation)
    Accepted Manuscript Full Text Available