  The maximum entropy principle can be used to assign utility values when only
partial information is available about the decision maker's preferences. In
order to obtain such utility values it is necessary to establish an analogy
between probability and utility through the notion of a utility density
function. According to some authors [Soofi (1990), Abbas (2006a) (2006b),
Sandow et al. (2006), Friedman and Sandow (2006), Darooneh (2006)] the maximum
entropy utility solution embeds a large family of utility functions. In this
paper we explore the maximum entropy principle to estimate the utility function
of a risk averse decision maker.
