The paper deals with a class of semi-Markov control models with Borel state and control spaces, possibly unbounded costs, and unknown holding times distribution H. Assuming that H does not depend on state-action pairs, we combine suitable methods of statistical estimation of H with control...

The paper deals with a class of semi-Markov control models with Borel state and control spaces, possibly unbounded costs, and unknown holding times distribution H. Assuming that H does not depend on state-action pairs, we combine suitable methods of statistical estimation of H with control...

The paper deals with a class of discrete-time Markov control processes with Borel state and action spaces, and possibly unbounded one-stage costs. The processes are given by recurrent equations x t +1 =F(x t ,a t ,ξ t ), t=1,2,… with i.i.d. ℜ k – valued random vectors ξ t whose density...

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...

The paper deals with a class of discrete-time Markov control processes with Borel state and action spaces, and possibly unbounded one-stage costs. The processes are given by recurrent equations x <Subscript> t </Subscript> <Subscript>+1</Subscript>=F(x <Subscript> t </Subscript>,a <Subscript> t </Subscript>,ξ<Subscript> t </Subscript>), t=1,2,… with i.i.d. ℜ<Superscript> k </Superscript>– valued random vectors ξ<Subscript> t </Subscript> whose...</subscript></superscript></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 <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>