DOI
https://doi.org/10.1016/j.procs.2014.09.043

Summary
The article is focused on modeling systems thinking in complex adaptive systems. Firstly, the authors explain the concept of complex adaptive system (CAS) as a complex system which reacts and adapts to the changing environment and aims to perform its task. They also define systems thinking as a tool to detect and predict behavior of the system. The authors compare their approach with the conventional methods and conclude that fuzzy logic, artificial intelligence, linguistics, and other technologies lack integration in previous research. Secondly, the modeling of systems thinking in autonomous intelligent fuzzy control and information CAS in fuzzy environment is presented using mathematical formulation. The suggested approach includes the principles of fuzzy modeling, general systems theory, artificial intelligence and knowledge-based technologies. It is concluded that the proposed methods and technology can be useful in fuzzy environments in which uncertainty occurs.

Relevance for Complex Systems Knowledge
The application of fuzzy logic approach enables to convert language evaluations to the numerical models based on the given rules. This enables to transfer the model to the environments where the processes are not determined in advance or may be understood relevantly. It also helps to model system thinking in the environments which use different languages as only the defuzzification and fuzzification parts differ. However, the reasoning part is the same and includes drawing conclusions based on the given knowledge, making predictions and constructing explanations. Various artificial intelligence methods, fuzzy logic, systems theory and others are applied in this part to process data.

Point of Strength
The point of strength is the suggested idea of modelling system thinking with the application of fuzzy logic.