| In reasoning and decision-making,the MP rules in logic rules reflect the essence of reasoning,that is,the process of obtaining conclusions from conditions and premises.Simply put: A、A(1)B(25)B.If A(1)B is known,and A can be known from the information obtained,then we can get B from it.Whether it is classical logical reasoning or precise probabilistic reasoning obtained by applying Bayesian rules,a definite conclusion can be obtained,which can help people strengthen or change their belief in decision-making.Although this seems to be an intuitive and very simple rule,the A obtained here is in a complete state.If the A here is not complete,but only a possibility,or in a state of uncertainty,the conclusion drawn in this way can only be a state of possibility and uncertainty.From the perspective of everyday language,there are a large number of adjectives such as "tall" and "short",as well as nouns such as "child" and "scientist".Their meanings are not precise,which makes different individuals have such concepts.According to his own interpretation,when an individual describes a person as a "tall" "scientist",it is based on his own knowledge,but for other individuals,this is not his knowledge.Such knowledge the difference makes individuals face uncertain information when they receive such information.This also leads to certain logical paradoxes,such as the bald head paradox.Facing this kind of imprecise language in everyday language,using fuzzy logic method to determine the degree of membership of the premise through the use of membership function solves this problem to a certain extent.Fuzzy logic can also be used to accurately "high" and "short" language inaccuracy problems.At the same time,in addition to the imprecision of everyday language,there are also some uncertain reasoning in scientific research.In the face of uncertainty,probability is one of the ways to describe uncertainty.However,there is no good way to assess the accuracy of probability.Measurement errors,incomplete information,contradictory information,and conflicting beliefs all make the probability inaccurate.Moreover,if a specific real number is used to express the probability,it will not be able to distinguish the degree of confirmation of a fact by two different pieces of evidence.Therefore,accurate probability should also be transformed into inaccurate probability.Using inaccurate probability to describe incomplete information will provide great help to the uncertainty reasoning caused by incomplete information. |
