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The dynamics of protection processes has been a fundamental challenge insystemic risk analysis. The conceptual principle and methodological techniquesbehind the mechanisms involved [in such dynamics] have been harder to graspthan researchers understood them to be. In this paper, we show how to constructa large variety of behaviors by applying a simple algorithm to networkedagents, which could, conceivably, offer a straightforward way out of thecomplexity. The model starts with the probability that systemic risk spreads.Even in a very random social structure, the propagation of risk is guaranteedby an arbitrary network property of a set of elements. Despite intensivesystemic risk, the potential of the absence of failure could also be drivenwhen there has been a strong investment in protection through a heuristicallyevolved protection level. It is very interesting to discover that manyapplications are still seeking the mechanisms through which networkedindividuals build many of these protection process or mechanisms based onfitness due to evolutionary drift. Our implementation still needs to bepolished against what happens in the real world, but in general, the approachcould be useful for researchers and those who need to use protection dynamicsto guard against systemic risk under intrinsic randomness in artificialcircumstances.

Network and Agent Dynamics with Evolving Protection against Systemic Risk