Confronta i metodi

	Analisi di Scenario Basata su Agenti	Modellazione basata su agenti (ABM)
Campo	Simulazione	Simulazione
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	1990s–2000s	1970s–1990s (formalized as a field)
Ideatore	Axelrod, R.; Schoemaker, P. J. H. (combined lineage)	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Tipo	Hybrid simulation–scenario method	Computational simulation method
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.
Alias	ABSA, ABM scenario analysis, agent-based scenario planning, scenario-driven ABM	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
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.	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.