Abstract: A definition of probability truth degree for formula in some common propositional logic is defined by the concepts of valuation density function and edge density function，some inference rules of probability truth degree are discussed，and the density of probability truth degree in[0,1] is proved.The definition of similaritie is given which discusses the properties of the relationship based on knowledge of the above.Thus the basis for the inference degree’s numerical is proved.

Key words: valuation density function, probability truth degree, inference rule, similarity degree

摘要： 通过引入赋值密度函数、边缘密度函数等概念，给出了几种常见的命题逻辑系统中公式概率真度的定义，研究了概率真度的推理规则并证明了全体公式的概率真度之集在[0，1]中的稠密性，在此基础上给出了相似度的定义并讨论了其性质，为推理程度的数值化提供了依据。

关键词: 赋值密度函数, 概率真度, 推理规则, 相似度