Agent-Based Models (ABMs) are artificial societies of software people (though agents can also be mosquitoes, viruses, vehicles, teams) who interact with one another to generate surprising and important social patterns of scientific and policy interest. Racial segregation, intergroup conflict, skewed distributions of wealth, pandemic spread, financial contagion, ancient civilizations, urban dynamics, social networks, and more have been generated “from the bottom up” in micro-worlds of agents. Like real people, these agents can be driven (often unaware) by powerful emotions; they may have poor information, and can make systematic errors interpreting it. The method of agents positions us to understand how the micro world of individuals generates the macro world of collective phenomena. Thus, the agent-based model is the principal scientific instrument in providing generative explanations for macro-patterns.
This Lab is NYU's hub for agent-based modeling, which encompasses affiliated from the entire University. Its mission is to advance interdisciplinary science, deepening the theoretical foundations, and expanding the humane applications, of agent-based modeling and complementary areas of mathematics across the social, behavioral, and health sciences.