Aggregation of Subjective Uncertainties: A New Interpretation and Combinations of Certainty Factors with Possibility Theory

Abstract

Information aggregation has a long history of studies and is being used in decision-making, sensor fusion, affective intelligence, Web Intelligence, and many other fields for combining certainties, reliabilities, sentiments and other degrees to judge something from uncertain information in the real world. The paper discusses a method to combine uncertainties represented by Certainty Factors, which is a traditional and practical representation of uncertainty used in many intelligent systems, but has been criticized due to lack of a sound mathematical theory. The paper tries to establish a theory for sound interpretation of Certainty Factors and proposes a new interpretation using Possibility theory. It also proposes a few methods to combine Certainty Factors with good theoretical basis, one of which is exactly the same as the one criticized for long time.