Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Политическо-сценариен агентно-базиран модел× | Динамика на системните политики× | |
|---|---|---|
| Област | Симулационно моделиране | Симулационно моделиране |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1990s–2000s | 1960s–1990s |
| Създател≠ | Axelrod, R. and colleagues in computational social science | Forrester, J. W. (system dynamics); scenario integration formalized by Sterman and others |
| Тип≠ | Simulation-based policy comparison | Simulation-based policy analysis |
| Основополагащ източник≠ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. ISBN: 9780691015675 | Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill. ISBN: 9780072389159 |
| Други названия | Policy ABM, Policy Scenario ABM, Scenario-Based ABM, PS-ABM | PSSD, Policy SD Simulation, Scenario-Based System Dynamics, Policy Systems Modeling |
| Свързани | 5 | 5 |
| Резюме≠ | 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. | Policy Scenario System Dynamics combines system dynamics modeling with structured scenario analysis to evaluate how different policy interventions affect complex, feedback-driven systems over time. By running multiple policy scenarios through a calibrated stock-and-flow model, analysts can compare long-run outcomes, identify leverage points, and anticipate unintended consequences before real-world implementation. |
| ScholarGateНабор от данни ↗ |
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