Generating Explanations for Evidential Reasoning
  In this paper, we present two methods to provide explanations for reasoning
with belief functions in the valuation-based systems. One approach, inspired by
Strat's method, is based on sensitivity analysis, but its computation is
simpler thus easier to implement than Strat's. The other one is to examine the
impact of evidence on the conclusion based on the measure of the information
content in the evidence. We show the property of additivity for the pieces of
evidence that are conditional independent within the context of the
valuation-based systems. We will give an example to show how these approaches
are applied in an evidential network.
