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MIT researchers found that generalist algorithms can outperform specialists in imperfect-information games. The study, presented at the International Conference on Learning Representations, analyzed algorithms training neural networks for zero-sum competitions. The work challenges long-held assumptions about specialist advantages in such strategic settings.
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