A Survey of Fuzzy Cognitive Map Learning Methods

There are many techniques that can be used for modeling and analysis of dynamic systems. Generally speaking, they may be divided in to two groups such as quantitative and qualitative techniques [22]. The former one encompasses all quantitative methods that target both well-understood systems, (e.g., mathematical programming techniques of operation research) as well as those that ae less understood, e.g. statistically based data mining methods. The main restrictions of quantitative approaches originate from the fact that they require substantial effort and specialized knowledge from the outside of application domain in order to develop a correct model. In addition, some complex nonlinear systems cannot be modeled in this way. In a nutshell, quantitative modeling in some cases is difficult, costly, or even impossible [1]. The latter, alternative group includes qualitative approaches, which are free from the above restrictions. Modeling dynamic systems with the use of FCMs falls into this group. It is characterized by simplicity of both model representation and its execution. Furthermore, FCMs can easily incorporate human knowledge and adapt to a given domain.