Multi-formalism modeling of human organization

Abstract

The modeling of a human organization for the analysis of its behavior in response to external stimuli is a complex problem and requires development and interoperation of a set of several models. Each model, developed using different modeling languages but the same data, offers unique insights and makes specific assumptions about the organization being modeled. Interoperation of such models can produce a more robust modeling and simulation capability to support analysis and evaluation of the organizational behavior. Meta-modeling analysis based on Concept Maps and Ontologies indicates what types of interoperation are valid between models expressed in different modeling languages. The approach is illustrated through several examples focusing on the use of Social Networks, Timed Influence Nets (a variant of Bayes Nets), and Colored Petri nets.