Assessing Certainty Factors in Decision-Making !!
Abstract: A Certainty Factor (CF) is a quantitative measurement of how strongly the antecedent of a rule supports its conclusion. CFs are used in rule-based systems to represent uncertain knowledge and assign weight to facts or pieces of knowledge. CF value Meaning -1 Certainly false +1 Definitely true Intermediate values Varying degrees of certainty 0 Unknown CFs were first introduced in the MYCIN expert system for medical diagnosis. The developers of MYCIN abandoned Bayes' Theorem and the p-function because they felt that experts' knowledge and intuition defied rigorous analysis. The CF model has theoretical and practical limitations. A belief network representation is similar to the CF model but is grounded in probability theory. The belief network representation has several advantages over the CF model, including overcoming many of the limitations of the CF model. Keywords Certainty Factors, Certainly False, Definitely True, CF Model, Knowledge and Int