  We introduce a new interpretation of two related notions - conditional
utility and utility independence. Unlike the traditional interpretation, the
new interpretation renders the notions the direct analogues of their
probabilistic counterparts. To capture these notions formally, we appeal to the
notion of utility distribution, introduced in previous paper. We show that
utility distributions, which have a structure that is identical to that of
probability distributions, can be viewed as a special case of an additive
multiattribute utility functions, and show how this special case permits us to
capture the novel senses of conditional utility and utility independence.
Finally, we present the notion of utility networks, which do for utilities what
Bayesian networks do for probabilities. Specifically, utility networks exploit
the new interpretation of conditional utility and utility independence to
compactly represent a utility distribution.
