Combining Fuzzy Cognitive Maps and Discrete Random Variables
  In this paper we propose an extension to the Fuzzy Cognitive Maps (FCMs) that
aims at aggregating a number of reasoning tasks into a one parallel run. The
described approach consists in replacing real-valued activation levels of
concepts (and further influence weights) by random variables. Such extension,
followed by the implemented software tool, allows for determining ranges
reached by concept activation levels, sensitivity analysis as well as
statistical analysis of multiple reasoning results. We replace multiplication
and addition operators appearing in the FCM state equation by appropriate
convolutions applicable for discrete random variables. To make the model
computationally feasible, it is further augmented with aggregation operations
for discrete random variables. We discuss four implemented aggregators, as well
as we report results of preliminary tests.
