Stochastic generalized Nash equilibrium seeking under partial-decision information

We consider for the first time a stochastic generalized Nash equilibrium problem, i.e., with expected-value cost functions and joint feasibility constraints, under partial-decision information, meaning that agents communicate only some trusted neighbors. propose several distributed algorithms network games aggregative we show being special instances of preconditioned forward–backward splitting method. prove converge to when forward operator is restricted cocoercive by using approximation scheme variance reduction estimate expected value pseudogradient.