LSLNCF: A Hybrid Uncertain Reasoning Model Based on Probability

Abstract

The "take-them-in-or-leave-them-out" of prior probabilities is a key problem in uncertain reasonings. The EMYCIN uncertain reasoning model is inconsistent with probability theory, due to 'leaving them out', while the PROSPECTOR uncertain reasoning model is substantially consistent with probability theory, due to 'taking them in'. This presents a difficult task for human experts when supplying prior probabilities. In this paper, in order to overcome the difficulty, we propose a hybrid uncertain reasoning model, by combing rule strengths in the PROSPECTOR model with rule strengths in the EMYCIN model. Moreover, different forms of rule strength will enable human experts to supply values for the rule strengths more flexibly in a knowledge base. Finally, an example is given to illustrate the power of our methodology.