Confronta i metodi

	Analisi di Scenario Basata su Agenti	Dinamica dei Sistemi
Campo	Simulazione	Simulazione
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	1990s–2000s	1961
Ideatore	Axelrod, R.; Schoemaker, P. J. H. (combined lineage)	Jay W. Forrester
Tipo	Hybrid simulation–scenario method	Continuous simulation / feedback modelling
Fonte seminale	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. Princeton, NJ. ISBN: 9780691015675	Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159
Alias	ABSA, ABM scenario analysis, agent-based scenario planning, scenario-driven ABM	stock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulation
Correlati	4	3
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.	System dynamics is a continuous simulation method, developed by Jay W. Forrester at MIT in 1961, that represents a complex system through stocks (accumulations), flows (rates of change), and feedback loops. By expressing these relationships as coupled ordinary differential equations, it reproduces how policies, delays, and nonlinear feedbacks drive system behaviour over time — making it a cornerstone tool in policy analysis, organisational modelling, and sustainability research.