Uncertain knowledge representation and processing based on rough set
不确定信息的粗糙集表示和处理

The randomness and fuzziness are the most important and basic for the uncertainty characteristics. Some major expansion of set theory about uncertain knowledge representation and processing are analyzed and compared in this paper. There is a systematic introduction of uncertainty based on rough set knowledge representation and processing methods. Extension of rough set theory based on the classical set theory is discussed deeply. Core operators of rough set were analyzed based on the classical set theory. At the same time, rough logic defined on the information systems is analyzed. It is proved that the important role and advantages of rough set theory for representing and dealing with the uncertainty based on the typical cases in the field of artificial intelligence. Finally, key issues about further studying on uncertain knowledge representation and processing are also discussed.