不确定性中的随机性和模糊性

随着不确定性研究的深入,世界的不确定性特征越来越得到学术界的普遍认可。人工智能中的不确定性主要是由随机性和模糊性引起的。人们用概率论和数理统计研究随机性,将＂随机性＂用＂概率＂予以量化表示,而贝叶斯理论等就成为人工智能中处理不确定性的重要工具。对于模糊性,人们用模糊数学作为工具来研究,在经典模糊集合论中引入＂隶属度＂来更好地处理人工智能中的模糊性问题。近十几年来,在随机数学和模糊数学的基础上,亦提出了用云模型来统一刻画语言值中大量存在的随机性、模糊性以及两者之间的关联性。随着不确定性研究的深入,必将为人工智能的应用提供更广阔的空间。

The Randomness and Fuzziness of Uncertainty

With the deep going study of uncertainty,the uncertainty characteristics of the world has been more and more widely recognized by academics.The uncertainty in artificial intelligence is mainly caused by randomness and fuzziness.People use probability theory and mathematical statistics to study the randomness,using the ＂probability＂ to quantify ＂randomness＂.The Bayesian theory has become an important tool for dealing with the uncertainty in artificial intelligence.People use fuzzy math as a tool to study fuzzy.We introduced the ＂membership＂ in classical fuzzy set theory to better deal with the ambiguity problem in artificial intelligence.Over the last decade,based on the random and fuzzy mathematics,we unified randomness,ambiguity,and the correlation between them which exit in the linguistic with the cloud model.With a detailed research of uncertainty,the application of artificial intelligence will be provided more room.