A Comparison of Methods for Transforming Belief Function Models to Probability Models

Recently, we proposed a new method called the plausibility transformation method to convert a belief function model to an equivalent probability model. In this paper, we compare the plausibility transformation method with the pignistic transformation method. The two transformation methods yield qualitatively different probability models. We argue that the plausibility transformation method is the correct method for translating a belief function model to an equivalent probability model that maintains belief function semantics.