Fuzzy Cognitive Maps

First approaches to cognitive maps

Robert Axelrod (1976) inaugurated the use of cognitive maps (CMs) for formally modeling decision making processes associated with political and social systems. CMs are directed graphs capable of modeling interrelationships or causalities existing amongst concepts (nodes). Concept variables and causal relations constitute the two fundamental elements that CMs employ for graphically describing systems. Concept variables are represented by nodes, such as C1, C2, C3, and C4 in Figure 1, a basic CM having four concept variables describing the impact of "Electromagnetic interference in the reading of an ultrasonic sensor".

Causal variables always depict concept variables at the origin of arrows; effect variables, on the other hand, represent concept variables at the terminal points of arrows. For example, in looking at C1 and C2 in the figure, C1 is said to impact C2 because C1 is the causal variable, whereas C2 is the effect variable.

Fuzzy cognitive maps

In this article we recall the notion of Fuzzy Cognitive Maps (FCMs), which was introduced by Bart Kosko[1] in the year 1986. FCMs have a major role to play mainly when the data concerned is an unsupervised one. Further this method is most simple and an effective one as it can analyse the data by directed graphs and connection matrices.