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المجالالمحاكاةاتخاذ القرار
العائلةProcess / pipelineMCDM
سنة النشأة1990s–2000s1949
صاحب الطريقةAxelrod, R. and colleagues in computational social scienceMetropolis, N., Ulam, S.
النوعSimulation-based policy comparisonRobustness wrapper — Monte Carlo uncertainty propagation
المصدر التأسيسيAxelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. ISBN: 9780691015675Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
الأسماء البديلةPolicy ABM, Policy Scenario ABM, Scenario-Based ABM, PS-ABM
ذات صلة50
الملخصPolicy 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.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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ScholarGateقارن الطرق: Policy Scenario Agent-Based Modeling · MONTE-CARLO-SIMULATION. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare