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Equilibrium Learning in Unbounded Stochastic Games with Gaussian Transitions

arXiv:2610.16149v1 Announce Type: new Abstract: Learning equilibria from data is difficult when several decision makers interact indefinitely and the system state has no prescribed bounds. We examine discounted general-sum stochastic games with compact action sets and an unknown nonlinear drift obs…

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  1. 2026-10-14 04:00 · arXiv stat.ML
    Equilibrium Learning in Unbounded Stochastic Games with Gaussian Transitions

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