  In the existing evidential networks with belief functions, the relations
among the variables are always represented by joint belief functions on the
product space of the involved variables. In this paper, we use conditional
belief functions to represent such relations in the network and show some
relations of these two kinds of representations. We also present a propagation
algorithm for such networks. By analyzing the properties of some special
evidential networks with conditional belief functions, we show that the
reasoning process can be simplified in such kinds of networks.
