Cellular automata learning of fuzzy cognitive map

A learning methodology is proposed for automatically constructing fuzzy cognitive map. In the proposed method, the evolutionary mechanism of cellular automata is used to learn the connection matrix of FCM. One-dimension cellular automata are used to code weight parameters, the cellular states are chosen within the range [0, 1] to form a cell space. In order to guide the optimization direction effectively and accelerate the speed of convergence, a mutation operator is added in the algorithm. Finally, an illustrative example is provided, and its results suggest that the method is capable of automatically generating FCM model.