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Agent-Based Scenario Analysis×Monte Carlo simulatsioon×
ValdkondSimulatsioonOtsustamine
PerekondProcess / pipelineMCDM
Tekkeaasta1990s–2000s1949
LoojaAxelrod, R.; Schoemaker, P. J. H. (combined lineage)Metropolis, N., Ulam, S.
TüüpHybrid simulation–scenario methodRobustness wrapper — Monte Carlo uncertainty propagation
AlgallikasAxelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. Princeton, NJ. ISBN: 9780691015675Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
RööpnimetusedABSA, ABM scenario analysis, agent-based scenario planning, scenario-driven ABM
Seotud40
KokkuvõteAgent-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.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateVõrdle meetodeid: Agent-based scenario analysis · MONTE-CARLO-SIMULATION. Loetud 2026-06-17 aadressilt https://scholargate.app/et/compare