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Agentic markets can achieve near-optimal welfare in first-price auctions, with the price of anarchy driven to zero by competitive floors and approaching $1 - 1/e^2$ under near-independent value distributions.
Static equilibrium concepts may mislead researchers, as they can mask the chaotic dynamics that emerge in multi-agent learning environments.