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| 정책 시나리오 셀룰러 오토마타× | 행위자 기반 모델링 (ABM)× | |
|---|---|---|
| 분야 | 시뮬레이션 | 시뮬레이션 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1979–1997 | 1970s–1990s (formalized as a field) |
| 창시자≠ | Tobler, W. (CA foundations); Clarke, K.C. et al. (policy/urban CA scenarios) | Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s) |
| 유형≠ | Grid-based scenario simulation | Computational simulation method |
| 원전≠ | 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 ↗ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗ |
| 별칭 | PSCA, CA Policy Scenario Modeling, Policy-driven CA Simulation, Scenario-based Cellular Automata | ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling |
| 관련 | 5 | 5 |
| 요약≠ | 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. | Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone. |
| ScholarGate데이터셋 ↗ |
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