Incremental Knowledge Base for Uncertain Reasoning

Evidence theory has been widely applied to uncertain reasoning. However, the evidence space and hypothesis space are each defined as a fixed set. If the theory is applied to solve specific problems, the corresponding evidence and hypothesis spaces have to be defined at the outset. In the real world, there are lots of systems with incremental spaces of evidence and hypotheses. It is difficult to apply the original evidence theory to such dynamic systems. Therefore, in this paper an incremental knowledge base is proposed to deal with dynamic knowledge bases. In the incremental knowledge base, a set of definitions in evidence theory are generalized. Based on the definitions, a set of operations for the incremental knowledge base is provided. A well known example is used to demonstrate the knowledge base in a reasoning system.