EN
We consider a class of $ℝ^d$-valued stochastic control systems, with possibly unbounded costs. The systems evolve according to a discrete-time equation $x_{t+1} = Gₙ(x_t,a_t)+ξ_t$ (t = 0,1,... ), for each fixed n = 0,1,..., where the $ξ_t$ are i.i.d. random vectors, and the Gₙ are given functions converging pointwise to some function $G_{∞}$ as n → ∞. Under suitable hypotheses, our main results state the existence of stationary control policies that are expected average cost (EAC) optimal and sample path average cost (SPAC) optimal for the limiting control system $x_{t+1} = G_{∞}(x_t,a_t)+ξ_t$ (t = 0,1,...).