Invalidation of dynamic network models

Models of discrete event systems combine ideas from control theory and computer science to represent the evolution of distributed processes. We formalize a notion of the invalidation of models presumed to describe dynamics on networks, and introduce an algorithm to evaluate a class of event-driven processes that evolve close to an invariant and stable state. The algorithm returns the value true, if according to the proposed notion of invalidation, the evolution of empirical observations is inconsistent with the stability properties of the model. To illustrate the approach, we represent a generic decision-making process in which the marginal utility of allocating agents to particular nodes rests on the well-known concept in economy theory of the law of diminishing returns.