Methoden vergleichen

	Agentenbasierte Systemdynamik	Agentenbasiertes Modellieren (ABM)
Fachgebiet	Simulation	Simulation
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	2000s	1970s–1990s (formalized as a field)
Urheber	Borshchev, A. & Filippov, A. (hybrid formalization); Sterman, J. D. (system dynamics foundation)	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Typ	Hybrid simulation model	Computational simulation method
Wegweisende Quelle	Borshchev, A., & Filippov, A. (2004). From system dynamics and discrete event to practical agent based modeling: Reasons, techniques, tools. In Proceedings of the 22nd International Conference of the System Dynamics Society. Oxford, UK.	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
Aliasnamen	AB-SD, Hybrid ABM-SD, Agent-based SD, Multi-level hybrid simulation	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Verwandt	5	5
Zusammenfassung	Agent-based system dynamics (AB-SD) is a hybrid simulation paradigm that couples agent-based modeling (ABM) at the micro level with system dynamics (SD) stock-and-flow structures at the macro level. This allows researchers to capture emergent individual behavior and feedback-driven aggregate dynamics within a single coherent model, making it especially valuable for complex socio-economic and epidemiological systems.	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.