Agent-Based Modeling for Psychological Research on Social Phenomena

This paper describes seven potential benefits of incorporating agent-based modeling (ABM) as a core research methodology for psychological research on social phenomena: building formal theories of complex social systems, validating multilevel causation, understanding temporal and non-linear dynamics, demonstrating the completeness of theories, balancing consideration of people with their environments, bridging psychology and policy, and identifying unknown unknowns and the limits of prediction. Those benefits accrue from a resonance between how they approach questions and the questions they ask. For example, both rely on experiments to explore how individual interactions generate collective phenomena. The paper compares micro-mechanism-driven and macro-pattern-driven ABM paradigms and introduces a new research approach—the minimal society paradigm—and a modeling strategy, principle-oriented modeling. This framework integrates ABM into psychological research, supporting both theory building through minimal societies and adaptation to specific contexts. Last, recent methodological developments in this field are discussed.