Simulate this! An Introduction to Agent-Based Models and their Power to Improve your Research Practice. Issue 1 (3rd July 2017)

• Record Type: Journal Article
• Authors: Eberlen, Julia; Scholz, Geeske; Gagliolo, Matteo
• Is Part Of: International review of social psychology. Volume 30:Issue 1(2017)
• Page Start: 149
• Page End: 160
• Publication Date: 2017-07-03
• Subjects: Social Psychology -- Agent-Based Models -- Computational Social Sciences -- Replication Crisis -- Methodology; Social psychology -- Periodicals; 302.05
• DOI: 10.5334/irsp.115
• Languages: English
• ISSNs: 2397-8570

Abstract

The method of agent-based modeling is rarely used in social psychology, but has the potential to complement and improve traditional research practices. An agent-based model (ABM) consists of a number of virtual individuals – the "agents" – interacting in an artificial, experimenter-controlled environment. In this article, we discuss several characteristics of ABMs that could prove particularly useful with respect to recent recommendations aimed at countering issues related to the current "replication crisis". We address the potential synergies between planning and implementing an ABM on the one hand, and the endeavor of pre-registration on the other. We introduce ABMs as tools for both the generation and the improvement of theory, testing of hypotheses, and for extending traditional experimental approaches by facilitating the investigation of social processes from the intra-individual all the way up to the societal level. We describe examples of ABMs in social psychology, including a detailed description of the CollAct model of social learning. Finally, limitations and drawbacks of agent-based modeling are discussed. In annex 1 and 2, we provide literature and tool recommendations for getting started with an ABM.