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| Politikscenarie-agentbaseret modellering× | Politikscenarieanalyse× | |
|---|---|---|
| Fagområde | Simulering | Simulering |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | 1990s–2000s | 1967–1990s |
| Ophavsperson≠ | Axelrod, R. and colleagues in computational social science | Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD |
| Type≠ | Simulation-based policy comparison | Qualitative-quantitative hybrid scenario method |
| Oprindelig kilde≠ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. ISBN: 9780691015675 | Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146. DOI ↗ |
| Aliasser | Policy ABM, Policy Scenario ABM, Scenario-Based ABM, PS-ABM | PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis |
| Relaterede | 5 | 5 |
| Resumé≠ | 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 Analysis is a structured method for evaluating how different policy interventions perform across a range of plausible future states. By pairing specific policy levers with alternative scenarios, analysts can assess robustness, trade-offs, and unintended consequences of policy choices before implementation — making it a cornerstone of evidence-based policy design in fields from climate to public health. |
| ScholarGateDatasæt ↗ |
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