Some strategies for explanations in evidential reasoning

We present two methods to provide explanations for reasoning with belief functions. 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 approach is to examine the impact of each piece of evidence on the conclusion based on the measure of the information content provided by the evidence. We show the property of additivity for each pieces of evidence that are conditional independent within the context of the valuation-based systems. We give an example to show how these approaches are applied in an evidential network.