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Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning
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- 1 Intro
- 2 Motivations
- 3 Policy-Space Response Oracles (PSRO) [Lanctot et. al '17] • Maintains a pool of strategies for each player, and iteratively.
- 4 Motivated Example: "Deal-or-No-Deal"[1]
- 5 Example: Bach or Stravinsky
- 6 PSRO on games beyond purely adversarial domains (no search)
- 7 Extending AlphaZero to Large Imperfect Information
- 8 MCTS in PSRO: A Bayesian Interpretation
