Combination of Agent-Based Social Simulation Models: Approaches and Challenges

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 is presented and current challenges are identified. 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.