Higher-order Fuzzy Cognitive Maps

FCMs are aimed at modeling and simulation of dynamic systems. They exhibit numerous advantages, such as model transparency, simplicity, and adaptability to a given domain, to name a few. FCMs have been applied to numerous industrial and research areas. In some cases generic FCMs suffer from a certain drawback that originates from their definition and concerns a limited, first-order dynamics of processing realized at the nodes of the maps. In this study, we introduce a concept of higher-order memory based FCMs. The proposed extension modifies the simulation model of a generic FCM while it does not negatively impact transparency and simplicity of the model itself. We discuss several architectural alternatives along with the ensuing computing and optimization aspects. Preliminary experimental results included in this paper show superiority of the extended higher-order memory based FCMs over a generic FCM in terms of the modeling accuracy