An Agent Based Model Approach for Perusal of Social Dynamics

Agent-based modeling has recently gained popularity in the field of simulation and modeling. Due to their characteristic properties, agent-based models (ABMs) allow for an improved and flexible way of modeling complex systems. Social dynamics is one such a complex system, which has complex components, such as demography, sociology, economics, psychology, health, and so on. Demography is one of the bigger and more important sub-systems of this complex system. In this paper, we have focused on utilizing the potential of ABM techniques to analyze the underlying processes in social demography. We propose and implement a holistic ABM that can be used for analysis, understanding, and prediction of socio-demographic processes as well as a tool for policy design and evaluation. The proposed model incorporates well-known factors affecting demography and provides ease and flexibility of adding newer factors. In this paper, we considered the use case of Korea and utilized the Korean census data for model development. Many ABMs have been proposed for demography but most of them not only have limited functionalities, but also lack the suitable usage of agent-based modeling itself. The proposed approach is wide-ranging, flexible, and general and can be reused by simply making changes in the initial data set for the analysis of the target society. We exhibit the validation of the proposed model, as well as its usage by executing virtual experiments for socio-demographic analysis and prediction.