LSLNCF - A HYBRID UNCERTAIN REASONING MODEL-BASED ON PROBABILITY

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', w hile the PROSPECTOR uncertain reasoning model is substantially consist ent with probability theory, due to 'taking them in'. This presents a difficult task for human experts when supplying prior probabilities. I n this paper, in order to overcome the difficulty, we propose a hybrid uncertain reasoning model, by combing rule strengths in the PROSPECTO R model with rule strengths in the EMYCIN model. Moreover, different f orms of rule strength will enable human experts to supply values for t he rule strengths more flexibly in a knowledge base. Finally, an examp le is given to illustrate the power of our methodology.