This paper explores the combination of agent-based social simulation (ABSS) models. Model combination facilitates the efficient development of more complex models through reuse, enabling a more comprehensive understanding of phenomena and outcomes that individual models cannot provide on their own. Through a narrative literature review of model combination in other simulation paradigms, six different approaches were identified: ensemble techniques, meta-analysis, model merging, models as modules, model integration and model chains . For each approach, examples and relevant literature are presented, and current challenges are identified. To illustrate the different approaches, a number of models of disease spread are then implemented and combined according to each approach. Through this, the paper aims to both provide inspiration to modelers and to identify paths for future research for the combination of ABSS models and model results.
Johansson et al. (Fri,) studied this question.