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Learned corner selection for cooperative guards dramatically boosts deployment efficiency and agent utilization in partially observable environments, outperforming established methods without sacrificing formal guarantees.
Some LLMs can outsmart Nash equilibria in two-player games, but their coordination skills falter in larger teams.
