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| 행위자 기반 모델링 (ABM)× | 프랙탈 분석× | |
|---|---|---|
| 분야≠ | 시뮬레이션 | 복잡계 |
| 계열≠ | Process / pipeline | Machine learning |
| 기원 연도≠ | 1970s–1990s (formalized as a field) | 1983 |
| 창시자≠ | Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s) | Benoit Mandelbrot |
| 유형≠ | Computational simulation method | Geometric complexity quantification |
| 원전≠ | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗ | Mandelbrot, B. B. (1983). The Fractal Geometry of Nature. W. H. Freeman. ISBN: 978-0-7167-1186-5 |
| 별칭 | ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling | Box-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal Analiz |
| 관련≠ | 5 | 2 |
| 요약≠ | 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. | Fractal Analysis quantifies the self-similar, scale-invariant complexity of geometric objects and time series through the fractal dimension D and the Hurst exponent H. Introduced systematically by Benoit Mandelbrot in his 1983 landmark work, the framework extends classical Euclidean geometry to irregular shapes found in nature, finance, physiology, and materials science. It provides a single dimensionless index that captures how completely a pattern fills space across multiple scales. |
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