Process / pipelineSimulation / optimization

Policy Scenario Cellular Automata — Grid-based simulation for comparing policy impacts

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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Sources

  1. 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
  2. Batty, M. (2005). Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. MIT Press. ISBN 978-0262025836. ISBN: 978-0262025836

Related methods

ScholarGatePolicy Scenario Cellular Automata (Policy Scenario Cellular Automata — Scenario-driven grid-based simulation for policy impact analysis). Retrieved 2026-06-04 from https://scholargate.app/en/simulation/policy-scenario-cellular-automata