方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 政策情景多主体建模× | 政策情景系统动力学× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s | 1960s–1990s |
| 提出者≠ | Axelrod, R. and colleagues in computational social science | Forrester, J. W. (system dynamics); scenario integration formalized by Sterman and others |
| 类型≠ | Simulation-based policy comparison | Simulation-based policy analysis |
| 开创性文献≠ | 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 |
| 别名 | Policy ABM, Policy Scenario ABM, Scenario-Based ABM, PS-ABM | PSSD, Policy SD Simulation, Scenario-Based System Dynamics, Policy Systems Modeling |
| 相关 | 5 | 5 |
| 摘要≠ | 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. |
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