Agent-based models reveal aggregate consequences no individual agent intends or foresees.

Evidence

In such systems, each agent typically represents an individual human acting according to a set of established behavioral motives and rules. These behavioral motives and rules generally reflect the kinds of individual-level processes that have been widely studied by psychologists. In an ABM, many simulated agents interact with one another and/or their environments over simulated time, based on the individual processes that guide the agents’ actions. Importantly, the outcomes of the agents in such a system are interdependent: each agent’s ability to achieve its goals depends not only on what it does but also what other agents do. Thus, the model permits observation of the emergent, aggregate consequences of many agents interacting interdependently and dynamically over a period of time (for a recent example, see Mason, Conrey, & Smith, 2007). — Roderick M. Kramer, Geoffrey J. Leonardelli, Robert W. Livingston, Social Cognition, Social Identity, and…, 821

Categorization

• DEFINE: Defines agent-based modeling as a method bridging individual intrapsychic processes and population-level emergent outcomes.
• SEED: Article angle: using ABM to show how quotidian ingroup preference rules, each individually mild, aggregate into segregated institutions nobody deliberately built — parallel to how agent-based models reveal emergent collective outcomes.
• corroborated: 2 independent passages support this claim — Roderick M. Kramer, Geoffrey J. Leonardelli, Robert W. Livingston, Social Cognition, Social Identity, and…, 821