Agent-based modeling reveals emergent group effects unpredictable from individual-level knowledge

Evidence

By examining multiagent interactions over time, agent-based modeling can reveal important emergent effects that could not be predicted only on the basis of knowledge of individual-level processes. At the same time, the ability to independently manipulate the nature of the agents’ individual and dyadic motives and behavior permits direct tests of the roles of these processes in producing aggregate outcomes. Finally, the ABM environment permits the manipulation of social context-level variables that are difficult to systematically vary in laboratory experiments. The ability to examine multiagent interactions over time also is a unique feature of agent-based modeling that cannot be accomplished with standard behavioral laboratory methods. — Roderick M. Kramer, Geoffrey J. Leonardelli, Robert W. Livingston, Social Cognition, Social Identity, and…, 859

Categorization

• DEFINE: Defines what agent-based modeling uniquely offers: emergent effects, manipulable motives, and context variables unavailable to lab experiments.
• XREF: connects to: Computer simulation can test hypotheses about large-scale social learning — Cailin O’Connor and James Owen Weatherall, The Misinformation Age: How False…, 47