Fuzzy Cognitive Maps (FCMs) have been proposed to represent causal reasoning by numeric processing. FCMs have the following features:
(1) They store domain knowledge in nodes and directional connections.
(2) They graphically represent uncertain causal reasoning.
(3) Their matrix representations allow causal inferences to be made as feedback associative memory recollections.
Many researchers have studied FCMs and applied them to various fields. However, there are some shortcomings concerned with knowledge representation in the conventional FCMs. In this paper, we propose Extended Fuzzy Cognitive Maps (E-FCMs) to represent causal relationships more naturally. The features of the E-FCMs are the following:
(1) They can deal with nonlinear causal relationships.
(2) They have time delay weights.
(3) They have conditional weights.
Computer simulation results indicate the effectiveness of the E-FCMs.