Developing a scientific formalism

I believe that that the study of complex systems requires a scientific formalism to test the hypotheses developed. This means we use a form of statistical hypothesis testing to "separate the demonstrably false from the probably true." Far too often, people have approached complexity from a philosophical viewpoint - believing that the understanding of complexity in systems may be accomplished by force of logically reasoned arguments. I encourage those who hold those beliefs to pursue that path, but in a separate forum. The reason - complexity has often proven to be counter-intuitive or paradoxical in its behavior. I believe there is a consistent, if not complete way of accommodating that behavior.

Next, attempts to understand complexity by lexical definition has proved difficult, if not impossible. It is hoped that by developing the scientific formalism, we might characterize certain features and patterns of complexity that will aid in our understanding, if not actually leading us to a definition.

Therefore, I am proposing that the scientific formalism be mathematically based using recurrent network graph models, category theory, statistical mechanics, and graph thermodynamics. This sounds more complicated than it really is. I have found that during the process of creating a scientific formalism (the processes), the knowledge gained by applying the methodology inherent in these techniques toward the formalism (a product) teaches us much about both the product and the processes. As time permits, I will be posting more about the formalism and validation techniques.