Proper Policies in Infinite-State Stochastic Shortest Path Problems

We consider stochastic shortest path problems with infinite state and control spaces, a nonnegative cost per stage, and a termination state. We extend the notion of a proper policy, a policy that terminates within a finite expected number of steps, from the context of finite state space to the context of infinite state space. We consider the optimal cost function $J^{\ast }$, and the optimal cost function $\widehat{J}$ over just the proper policies. We show that $J^{\ast }$ and $\widehat{J}$ are the smallest and largest solutions of Bellman’s equation, respectively, within a suitable class of Lyapounov-like functions. If the cost per stage is bounded, these functions are those that are bounded over the effective domain of $\widehat{J}$. The standard value iteration algorithm may be attracted to either $J^{\ast }$ or $\widehat{J}$, depending on the initial condition.