Reasonably reasoning AI agents can avoid game-theoretic failures in zero-shot, provably

This research explores whether AI agents can autonomously reach strategic equilibria in repeated interactions without specialized training. The author proves that "reasonably reasoning" agents—those capable of basic capabilities such as Bayesian learning and asymptotic best-response—naturally converge toward Nash equilibrium play, where posterior-sampling behaviors of off-the-shelf models guarantee asymptotic best response. The study further demonstrates that these agents successfully navigate environments, even when payoffs are unknown or stochastic, by inferring the game structure from private observations. Empirical simulations across various scenarios, such as the Prisoner’s Dilemma, confirm that advanced reasoning capabilities enable stable, predictable cooperation. Ultimately, the paper suggests that sophisticated AI naturally possesses the intrinsic mechanisms necessary for reliable decision-making in complex economic markets.