Stability and Sensitivity Measures for Solutions in Complex, Intelligent, Adaptive and Autonomous Systems

Simulation has become a pivotal tool for the design, analysis, and control of complex, intelligent, adaptive and autonomous systems and its components. However, due to the nature of these systems, traditional evaluation practices are often not sufficient. As the components follow adaptive rules, the cumulative events often exploit bifurcation enabling events, leading to clusters of solutions that do not follow the usual rules for standard distributed events. When using simulation for design, analysis, and control of such systems, the evaluation needs to be richer, applying bifurcation and cluster analysis to understand the distribution, applying factor analysis to understand the important factors for the necessary sensitivity analysis, and take not only point estimates for the solution and the sensitivity analysis into account, but contact a statistical stability analysis. The full exploitation of gaining numerical insights into the dynamic behavior and its deviations is needed. This paper introduces the pitfalls and recommends applicable methods and heuristics