Notes on 'Modeling, Simulation and Analysis of Complex Networked Systems'

摘要

While this area is relatively new as a subject in mathematical physics. Modeling and simulation of complex systems in operations and systems research, including the energy economy has been around for a long time. Efforts in the commercial and research arenas arguably dwarfs that of traditional scientif c computing. Discrete Event Simulation (DES) and Agent-Based (AB) modeling are usually the tools of choice for modeling practical complex systems (as they are usually employed, the former could be considered a special case of the latter). Yet the mathematical underpinnings that might relate entity models and interconnection topologies are largely missing. Often experimental results are impractical or too expensive for the physical systems of most interest. Lacking any guidance from mathematical physics, behavior can only be exampled at full scale. For example, understanding the impact on stability of a even a seemingly minor change in the electrical grid is not practical nor desirable experimentally. Lacking the definitive experimental evidence of overall behavior and the mathematical underpinnings to extrapolate to scale, designers of such simulations often consider the better model to be one for which as much detail as possible is loaded into the entities and their connections. Because they lack these tools, this is done without a clear understanding of each parameters dependence in the emergent behavior of the overall system nor its interdependence with other parameters.