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	Policy Scenario Agent-Based Modeling	Agent-Based Modeling (ABM)
Ämnesområde	Simulering	Simulering
Familj	Process / pipeline	Process / pipeline
Ursprungsår	1990s–2000s	1970s–1990s (formalized as a field)
Upphovsperson	Axelrod, R. and colleagues in computational social science	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Typ	Simulation-based policy comparison	Computational simulation method
Ursprungskälla	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. ISBN: 9780691015675	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
Alias	Policy ABM, Policy Scenario ABM, Scenario-Based ABM, PS-ABM	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Närliggande	5	5
Sammanfattning	Policy Scenario Agent-Based Modeling (PS-ABM) is a simulation method that uses agent-based models to evaluate and compare multiple policy scenarios. Heterogeneous autonomous agents interact under different policy regimes, and emergent system-level outcomes are compared across scenarios to inform evidence-based policy decisions. It is widely used in public health, urban planning, economics, and social policy research.	Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone.