Bandingkan metode

	Otomata Seluler Skenario Kebijakan	System Dynamics
Bidang	Simulasi	Simulasi
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	1979–1997	1961
Pencetus	Tobler, W. (CA foundations); Clarke, K.C. et al. (policy/urban CA scenarios)	Jay W. Forrester
Tipe	Grid-based scenario simulation	Continuous simulation / feedback modelling
Sumber perintis	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.	Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159
Alias	PSCA, CA Policy Scenario Modeling, Policy-driven CA Simulation, Scenario-based Cellular Automata	stock-flow modelling, Sistem Dinamiği (Stock-Flow Modelleme), SD modelling, feedback simulation
Terkait	5	3
Ringkasan	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.	System dynamics is a continuous simulation method, developed by Jay W. Forrester at MIT in 1961, that represents a complex system through stocks (accumulations), flows (rates of change), and feedback loops. By expressing these relationships as coupled ordinary differential equations, it reproduces how policies, delays, and nonlinear feedbacks drive system behaviour over time — making it a cornerstone tool in policy analysis, organisational modelling, and sustainability research.