Acquisition of explicit and implicit knowledge in fuzzy systems

As people acquire knowledge, part of it becomes explicit and forms common domain. The other part is implicit and is unique for each person. These two types of knowledge can be represented as a fuzzy system with two types of rules. However, aggregation in this system of two types of rules, representing explicit and implicit knowledge can lead to inconsistency. The paper shows that using uninorm operators we can overcome these difficulties. Another problem that arises in knowledge acquisition is that usually fuzzy systems deal with predicates that can be represented as fuzzy sets, and this feature limits their application to representation and acquisition of human knowledge. It is shown that this problem can be resolved by extension of the above method to set-like alternatives that are present in a large part of human knowledge