J. A. Mavroforas

Equilibrium Learning in Unbounded Stochastic Games with Gaussian Transitions

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 observed through Gaussian transition noise. The proposed procedure uses...