A research paper of Hossein Sabzian (2019), Theories and Practice of Agent based Modeling: Some practical Implications for Economic Planners, ArXiv, 54p

Nowadays, we are surrounded by a large number of complex phenomena such as virus epidemic, rumor spreading, social norms formation, emergence of new technologies, rise of new economic trends and disruption of traditional businesses. To deal with such phenomena, social scientists often apply reductionism approach where they reduce such phenomena to some lower-lever variables and model the relationships among them through a scheme of equations (e.g. Partial differential equations and ordinary differential equations). This reductionism approach which is often called equation based modeling (EBM) has some fundamental weaknesses in dealing with real world complex systems, for example in modeling how a housing bubble arises from a housing market, the whole market is reduced into some factors (i.e. economic agents) with unbounded rationality and often perfect information, and the model built from the relationships among such factors is used to explain the housing bubble while adaptability and the evolutionary nature of all engaged economic agents along with network effects go unaddressed. In tackling deficiencies of reductionism approach, in the past two decades, the Complex Adaptive System (CAS) framework has been found very influential. In contrast to reductionism approach, under this framework, the socio-economic phenomena such as housing bubbles are studied in an organic manner where the economic agents are supposed to be both boundedly rational and adaptive. According to CAS framework, the socio-economic aggregates such as housing bubbles emerge out of the ways agents of a socio-economic system interact and decide. As the most powerful methodology of CAS modeling, Agent-based modeling (ABM) has gained a growing application among academicians and practitioners. ABMs show how simple behavioral rules of agents and local interactions among them at micro-scale can generate surprisingly complex patterns at macro-scale. Despite a growing number of ABM publications, those researchers unfamiliar with this methodology have to study a number of works to understand (1) the why and what of ABMs and (2) the ways they are rigorously developed. Therefore, the major focus of this paper is to help social sciences researchers get a big picture of ABMs and know how to develop them both systematically and rigorously.