GenBR uses MCTS and generative models for scalable best responses in multiagent settings, applied within PSRO using bargaining theory to build opponent models, achieving human-comparable performance in Deal-or-No-Deal negotiations.
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Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning
GenBR uses MCTS and generative models for scalable best responses in multiagent settings, applied within PSRO using bargaining theory to build opponent models, achieving human-comparable performance in Deal-or-No-Deal negotiations.