Fuzzy Object-Oriented Dynamic Networks. II
This work addresses the problem of representing and evolving fuzzy knowledge in dynamic systems, likely for AI or data modeling domains, but appears incremental as it extends prior frameworks.
The authors generalized object-oriented dynamic networks to incorporate fuzzy logic, enabling representation of inherently fuzzy objects and classes and modeling their temporal changes. They proposed a novel knowledge acquisition mechanism that differs from existing methods, illustrated with a concrete example.
This article generalizes object-oriented dynamic networks to the fuzzy case, which allows one to represent knowledge on objects and classes of objects that are fuzzy by nature and also to model their changes in time. Within the framework of the approach described, a mechanism is proposed that makes it possible to acquire new knowledge on the basis of basic knowledge and considerably differs from well-known methods used in existing models of knowledge representation. The approach is illustrated by an example of construction of a concrete fuzzy object-oriented dynamic network.