Innovation and its knowledge systems are complex phenomena. They generally interact through agents to create the Regional Innovation System, which consists of the organizations producing and transforming knowledge in a given region. Nevertheless, given their complex nature, agents and systems could also be classified as economic, social, public and private. Since such agents interact diversely, continuously and cooperatively, the main purpose is to build an appropriate analytic framework to study such phenomenon. Its evolution and interaction will be analyzed by means of modeling and simulation methodologies, used as analytic tools to study their structures and dynamics, based on their production of knowledge and innovation. In general, the structures and their dynamics will be studied through network analysis. Therefore the main indicators to approach such phenomenon will be: the clusterization index and the number of links formed within the network. Mainly, the clusterization index shows how knowledge networks interact in an innovation environment, where the higher the clusterization index, the higher the innovation and knowledge in a given region. Keywords: agents; innovation; interaction; simulation; system