Confronta i metodi

	Analisi di Scenario Basata su Agenti	Modellazione basata su agenti per scenari di policy
Campo	Simulazione	Simulazione
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	1990s–2000s	1990s–2000s
Ideatore	Axelrod, R.; Schoemaker, P. J. H. (combined lineage)	Axelrod, R. and colleagues in computational social science
Tipo	Hybrid simulation–scenario method	Simulation-based policy comparison
Fonte seminale	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. Princeton, NJ. ISBN: 9780691015675	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. ISBN: 9780691015675
Alias	ABSA, ABM scenario analysis, agent-based scenario planning, scenario-driven ABM	Policy ABM, Policy Scenario ABM, Scenario-Based ABM, PS-ABM
Correlati	4	5
Sintesi	Agent-based scenario analysis embeds agent-based simulation models inside a structured scenario planning framework. Researchers define two to four contrasting future scenarios, configure agent populations and environmental rules to reflect each scenario's assumptions, run the simulation under each condition, and compare emergent outcomes. This makes it possible to explore how decentralized individual behaviors aggregate into system-level consequences under radically different futures.	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.