Methoden vergleichen

	Agentenbasiertes Modellieren (ABM)	Fraktalanalyse
Fachgebiet	Simulation	Komplexe Systeme
Familie	Process / pipeline	Machine learning
Entstehungsjahr	1970s–1990s (formalized as a field)	1983
Urheber	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)	Benoit Mandelbrot
Typ	Computational simulation method	Geometric complexity quantification
Wegweisende Quelle	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
Aliasnamen	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling	Box-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal Analiz
Verwandt	5	2
Zusammenfassung	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.