AI Solly outbluffs elite humans at Liar’s Poker

AI Solly outbluffs elite humans at Liar’s Poker

AI that thrives on bluffing

Researchers built Solly, an AI that learns Liar’s Poker—a fast, bluff-heavy game with many players and hidden info.

Instead of studying only two-player poker, Solly tackles truly multi-player dynamics. Trained via self-play with a model-free, actor-critic deep reinforcement learning approach, it taught itself when to bid, call, or bluff.

  • Performance: Won over 50% of hands and earned positive equity in both heads-up and multi-player matches.
  • Against people: Played at elite human level and wasn’t easily exploitable by world-class players.
  • Against AI: Outperformed large language models, even those designed for reasoning.
  • Strategy: Discovered novel bidding patterns and used effective randomization to stay unpredictable.

Why it matters: Liar’s Poker pushes AI beyond perfect-information games into messy, human-like uncertainty and deception—a step toward systems that can reason, negotiate, and make decisions with incomplete data.

Paper: arXiv:2511.03724

Paper: http://arxiv.org/abs/2511.03724v1

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#AI #ReinforcementLearning #SelfPlay #GameTheory #DeepRL #MultiAgent #LiarsPoker #Poker

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