Сравнение методов

	Агентное моделирование (АМ)	Фрактальный анализ
Область	Имитационное моделирование	Сложные системы
Семейство	Process / pipeline	Machine learning
Год появления	1970s–1990s (formalized as a field)	1983
Автор метода	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)	Benoit Mandelbrot
Тип	Computational simulation method	Geometric complexity quantification
Основополагающий источник	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.	Mandelbrot, B. B. (1983). The Fractal Geometry of Nature. W. H. Freeman. ISBN: 978-0-7167-1186-5
Другие названия	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling	Box-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal Analiz
Связанные	5	2
Сводка	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.