Abstract Learning of fuzzy cognitive maps (FCMs) is one of the most useful characteristics
which have a high impact on modeling and inference capabilities of them. The learning
approaches for FCMs are concentrated on learning the connection matrix, based either on
expert intervention and/or on the available historical data. Most learning approaches for
FCMs are Hebbian-based and evolutionary-based algorithms. A new learning algorithm for
FCMs is proposed in this research work, inheriting the main aspects of the bagging …