Optimization in genetically evolved fuzzy cognitive maps supporting decision-making: The limit cycle case

Abstract

The use of Fuzzy Cognitive Maps (FCM) as a technique for modeling real world problems and supporting the decision-making process was analyzed. The technique focuses on handling the limit cycle phenomenon and proposing an improvement in the decision-making processes. The development of the FCM is based on the utilization of domain experts knowledge that defines the active concepts and the degree of influence between them. The activation level of the nodes participating in an FCM model can be calculated using specific updating equations in a series of iterations. A combination of FCM with Genetic Algorithms facilitates the study of hypothetical scenaria describing the real-world problem and provide powerful means of decision making.