Сравнение методов

	Симуляция клеточных автоматов для сценариев политики	Анализ политических сценариев
Область	Имитационное моделирование	Имитационное моделирование
Семейство	Process / pipeline	Process / pipeline
Год появления	1979–1997	1967–1990s
Автор метода	Tobler, W. (CA foundations); Clarke, K.C. et al. (policy/urban CA scenarios)	Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD
Тип	Grid-based scenario simulation	Qualitative-quantitative hybrid scenario method
Основополагающий источник	Clarke, K. C., Hoppen, S., & Gaydos, L. (1997). A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, 24(2), 247–261.	Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146.
Другие названия	PSCA, CA Policy Scenario Modeling, Policy-driven CA Simulation, Scenario-based Cellular Automata	PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis
Связанные	5	5
Сводка	Policy Scenario Cellular Automata (PSCA) combines cellular automata simulation with structured scenario analysis to evaluate how alternative policy decisions reshape spatially distributed systems over time. Each scenario encodes a different set of transition rules or constraints, and the model iterates to reveal divergent spatial outcomes — enabling direct, visual comparison of policy consequences at the local and system level.	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.