Method evidence record

Policy Scenario Cellular Automata

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.

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Policy Scenario Cellular Automata — Scenario-driven grid-based simulation for policy impact analysis

Taxonomic method record · process-pipeline / simulation

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. · DOI 10.1068/b240247
Batty, M. (2005). Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. MIT Press. ISBN 978-0262025836. · ISBN 978-0262025836

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Related methods

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Same method familyAgent-Based Modelingmachine-suggested · Relational suggestion, not evidence.Same method familyCellular Automatamachine-suggested · Relational suggestion, not evidence.Same method familyDiscrete-Event Simulationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPolicy Scenario Analysismachine-suggested · Relational suggestion, not evidence.Same method familySystem Dynamicsmachine-suggested · Relational suggestion, not evidence.