  In this article we consider risk-sensitive control of semi-Markov processes
with a discrete state space. We consider general utility functions and
discounted cost in the optimization criteria. We consider random finite horizon
and infinite horizon problems. Using a state augmentation technique we
characterise the value functions and also prescribe optimal controls.
