We consider a class of discrete-time stochastic control systems, with Borel state and action spaces, and possibly unbounded costs. The processes evolve according to the equation x t +1 =F(x t , a t , ξ t ), t=0, 1, ..., where the ξ t are i.i.d. random vectors whose common distribution is...

We consider a class of discrete-time stochastic control systems, with Borel state and action spaces, and possibly unbounded costs. The processes evolve according to the equation x <Subscript> t +1</Subscript>=F(x <Subscript> t </Subscript>, a <Subscript> t </Subscript>, ξ <Subscript> t </Subscript>), t=0, 1, ..., where the ξ <Subscript> t </Subscript> are i.i.d. random vectors whose common distribution is...</subscript></subscript></subscript></subscript></subscript>

We consider a class of time-varying stochastic control systems, with Borel state and action spaces, and possibly unbounded costs. The processes evolve according to a discrete-time equation x n + 1 =G n (x n , a n , ξ n), n=0, 1, … , where the ξ n are i.i.d. ℜ k-valued random vectors whose...

We consider a class of time-varying stochastic control systems, with Borel state and action spaces, and possibly unbounded costs. The processes evolve according to a discrete-time equation x <Subscript>n + 1</Subscript>=G <Subscript>n</Subscript> (x <Subscript>n</Subscript> , a <Subscript>n</Subscript> , ξ<Subscript>n</Subscript>), n=0, 1, … , where the ξ<Subscript>n</Subscript> are i.i.d. ℜ<Superscript>k</Superscript>-valued random vectors whose...</superscript></subscript></subscript></subscript></subscript></subscript></subscript>