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1. ​ ‘RL’ tag

2. ​ ‘Diplomacy AI’ tag

3. ​ ‘Hanabi AI’ tag

4. ​ ‘poker AI’ tag

5. ​ ‘RL exploration’ tag

6. ​ ‘MuZero’ tag

7. ​ BetaZero: Belief-State Planning for Long-Horizon POMDPs using Learned Approximations

8. ​ Posterior sampling for multi-agent reinforcement learning: solving extensive games with imperfect information

9. ​ AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong

10. ​ DeepNash: Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning

11. ​ DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning

12. ​ Vector Quantized Models for Planning

13. ​ Suphx: Mastering Mahjong with Deep Reinforcement Learning

14. ​ From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization

15. ​ Finding Friend and Foe in Multi-Agent Games

16. ​ Monte Carlo Neural Fictitious Self-Play: Approach to Approximate Nash equilibrium of Imperfect-Information Games

17. ​ A Survey and Critique of Multiagent Deep Reinforcement Learning

18. ​ Solving Imperfect-Information Games via Discounted Regret Minimization

19. ​ ExIt-OOS: Towards Learning from Planning in Imperfect Information Games

20. ​ Regret Minimization for Partially Observable Deep Reinforcement Learning

21. ​ LADDER: A Human-Level Bidding Agent for Large-Scale Real-Time Online Auctions

22. ​ Deep Recurrent Q-Learning for Partially Observable MDPs

23. ​ Monte-Carlo Planning in Large POMDPs

24. ​ One Writer Enters International Competition to Play the World-Conquering Game That Redefines What It Means to Be a Geek (and a Person)

25. ​ So Has AI Conquered Bridge?

26. ​ The Steely, Headless King of Texas Hold ’Em

27. ​ Artificial Intelligence Beats Eight World Champions at Bridge

28. ​ A Poker-Playing Robot Goes to Work for the Pentagon

29. ​ 2022-perolat-figure1b-deepnashstrategoselfplayarchitecture.png

30. ​ https://intapi.sciendo.com/pdf/10.2478/ijasitels-2020-0003

31. ​ 536f380a88e2cf5d1aa196dc9c33a7dbdc467901.pdf

32. ​ https://www.reddit.com/r/reinforcementlearning/comments/cdwzp3/pluribus_superhuman_ai_for_multiplayer_poker/etwu82u/

33. ​ 87f57c57495f55ca13842c7c25db6c9ed9e0efa3.html

34. ​ https://x.com/nickchk/status/1635731621801496577

35. ​ DeepNash: Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning

36. ​ Sherjil Ozair

37. ​ https%253A%252F%252Farxiv.org%252Fabs%252F2206.15378%2523deepmind.html

38. ​ Vector Quantized Models for Planning

39. ​ Sherjil Ozair

40. ​ https%253A%252F%252Farxiv.org%252Fabs%252F2106.04615%2523deepmind.html

41. ​ Monte-Carlo Planning in Large POMDPs

42. ​ %252Fdoc%252Freinforcement-learning%252Fmodel%252F2010-silver.pdf.html

43. Wikipedia Bibliography:

    1. ​ Scotland Yard

    2. ​ Tom Eccles

    3. ​ Mark Rowland

    4. ​ David Silver (programmer)

    5. ​ Satinder Singh

    6. ​ Demis Hassabis

    7. ​ Oriol Vinyals