REPRESENTING HEURISTIC KNOWLEDGE IN D-S THEORY
Wr Liu, JG Hughes, MF McTear · 1992
The Dempster-Shafer theory of evidence has been used intensively to deal with uncertainty in knowledge-based systems. However the representation of uncertain relationships between evidence and hypothesis groups (heuristic knowledge) is still a major research problem. This paper presents an approach to representing such heuristic knowledge by evidential mappings which are defined on the basis of mass functions. The relationships between evidential mappings and multivalued mappings, as well as between evidential mappings and Bayesian multi- valued causal link models in Bayesian theory are discussed. Following this the detailed procedures for constructing evidential mappings for any set of heuristic rules are introduced. Several situations of belief propagation are discussed. 1 INTRODUCTION In the design and implementation of expert systems and decision making systems, the problem of uncertain knowledge and evidence has to be solved. Several approaches can be used to deal with this probl...