This paper considers an exponential cost optimality problem for finite horizon semi-Markov decision processes (SMDPs). The objective is to calculate an optimal policy with minimal exponential costs over the full set of policies in a finite horizon. First, under the standard regular and compact-continuity conditions, we establish the optimality equation, prove that the value function is the unique solution of the optimality equation and the existence of an optimal policy by using the minimum nonnegative...

This work concerns a discrete-time Markov chain with time-invariant transition mechanism and denumerable state space, which is endowed with a nonnegative cost function with finite support. The performance of the chain is measured by the (long-run) risk-sensitive average cost and, assuming that the state space is communicating, the existence of a solution to the risk-sensitive Poisson equation is established, a result that holds even for transient chains. Also, a sufficient criterion ensuring that...

In this paper we are concerned with a class of time-varying discounted Markov decision models ${ℳ}_n$ with unbounded costs $c_n$ and state-action dependent discount factors. Specifically we study controlled systems whose state process evolves according to the equation $x_{n+1}=G_n(x_n,a_n,{\xi }_n),n=0,1,...$, with state-action dependent discount factors of the form ${\alpha }_n(x_n,a_n)$, where $a_n$ and ${\xi }_n$ are the control and the random disturbance at time $n$, respectively. Assuming that the sequences of functions $\left\{{\alpha }_n\right\}$,$\left\{c_n\right\}$ and $\left\{G_n\right\}$ converge, in certain sense, to ${\alpha }_{\infty }$, $c_{\infty }$ and $G_{\infty }$, our...