Adaptation of Fuzzy Cognitive Maps – a Comparison Study

This paper deals with the experimental study and comparison of variousadaptation methods for setting-up parameters of fuzzy cognitive maps (FCMs). A survey isgiven of the best known methods, which are mostly based on unsupervised learning. Theauthors show better performance using supervised learning, namely least mean squareapproaches. Experiments were done on a simulation example of autonomous vehiclenavigation. The paper is concluded by comparing their efficacy and properties.