A geometrical approach to evidential reasoning

A model for evidential reasoning is proposed, in which the belief function of a piece of evidence is modeled as a probability density function which can be a continuous or discrete form. A polar notation of mutual dependency relationship between the evidence is considered, in which the dependency between two interrelated pieces of evidence is described by an angle. This method can resolve the conflict resulting from either the mutual dependency among many pieces of evidence or the structural dependency in an inference network due to the evidence combination order. Belief conjunction, belief combination, belief propagation procedures and AND/OR operations of an inference network based on the proposed model are all presented. Examples are given to demonstrate the advantages of this method over the conventional approaches