UNCERTAIN KNOWLEDGE REPRESENTATION BY MEANS OF TENSOR ALGEBRA

The article discusses the possibility of representing fuzzy knowledge in complex systems by means of tensor methodology. The tensor methodology is considered as a general system theory method used to analyze complex systems. The method is the result of applying the apparatus of tensor algebra in solving problems of the general theory of systems. A fuzzy logic apparatus is used to represent fuzzy knowledge in a complex system. Using the example of building fuzzy sets on a certain domain, a method is proposed for obtaining a tensor from elements of a fuzzy set and a membership function. The results are illustrated by the description of the world of fuzzy objects of a complex system, which includes the representation of objects and the relations between them. The advantages of using tensor methodology to represent fuzzy knowledge in complex systems are noted.

искусственный интеллект, представление знаний, представление нечетких знаний, нечеткости, нечеткая логика