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| 강건 에이전트 기반 모델링× | 행위자 기반 모델링 (ABM)× | |
|---|---|---|
| 분야 | 시뮬레이션 | 시뮬레이션 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2000s | 1970s–1990s (formalized as a field) |
| 창시자≠ | Ligmann-Zielinska, A.; Railsback, S. F.; Grimm, V. | Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s) |
| 유형≠ | Simulation robustness framework | Computational simulation method |
| 원전≠ | Ligmann-Zielinska, A., Cheetham, W. (2006). Spatially-explicit sensitivity analysis of an agent-based model of land use change. International Journal of Geographical Information Science, 20(12), 1355-1377. link ↗ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗ |
| 별칭 | Robust ABM, ABM Robustness Analysis, Uncertainty-Aware ABM, Robust Multi-Agent Simulation | ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling |
| 관련 | 5 | 5 |
| 요약≠ | Robust Agent-Based Modeling (Robust ABM) integrates systematic uncertainty quantification and sensitivity analysis into agent-based simulation workflows. Rather than relying on a single parameter configuration, it explores the full parameter space to identify which inputs drive model outcomes, ensuring that conclusions hold across plausible input ranges and model structures. | 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. |
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