There is a diversity of frameworks and methodologies for enabling architecture developments. Static representation frameworks provide a standardized way to communicate the architecture to stakeholders, but do not provide means to analyze the system states and system behavior. Therefore, there is a need to convert static representation frameworks to executable models. The aim of this paper is to present Artificial Life approaches as a methodology for understanding behavior of System of Systems. For this, an Artificial Life based framework for modeling System of Systems is presented. The framework comprises cognitive architectures embedded in multi-agent models. Financial markets are selected as an analysis domain to demonstrate the framework since they are a good example of self-organizing systems that are nonproprietary and exhibit emergence on a grand scale. From the Artificial Life Framework trader-based architectures are formulated as models to analyze system level behavior. The Artificial Life based framework provides a flexible way of modeling sub-systems of System of Systems and it captures the adaptive and emergent behavior of the system.