A first study of Fuzzy Cognitive Maps learning using cultural algorithm

In this paper a new algorithm for Fuzzy Cognitive Maps learning is introduced. The proposed approach is based on the cultural algorithm and it is used to build the weight matrices that allow the Fuzzy Cognitive Map algorithm to find the final steady states. A Fuzzy Cognitive Map (FCM) is a fuzzy signed directed graph with feedback and models complex systems as a collection of concepts and causal relations between concepts. An FCM can be constructed by using experts' knowledge or historical data. In this paper we have developed an automated method FCM learning which uses a type of evolutionary algorithm known as a cultural algorithm. We explain the algorithm and demonstrate its performance advantages.