A robust evolutionary strategy for generative validation of agent-based models using adaptive simulation ensembles

Fewstudies examine distinct characteristics of problems studied by agent-based models and their implications on operational validation. This paper focuses on exploratory and generative modeling perspective advocated by the agent-based modeling paradigm. The significance of robustness is emphasized, and a robust generative validation strategy is proposed for models used in scientific problems in which ambiguity and deep uncertainty pervade. The strategy is predicated on the premise of creative evolutionary systems perspective that enables viewing validation within the scientific method of falsification. That is, the strategy mimics the way scientific knowledge is constructed and validated by groups of scientists within a scientific discipline. The utility and feasibility of the method is demonstrated using a case study.