Comparer des méthodes

	Équations Différentielles Stochastiques (EDS)	Modélisation Basée sur les Agents (MBA)
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1944 (theory); 1992 (numerical framework)	1970s–1990s (formalized as a field)
Auteur d'origine	Kiyosi Itô (Itô calculus, 1944); Peter Kloeden & Eckhard Platen (numerical methods, 1992)	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Type	Continuous-time stochastic process model	Computational simulation method
Source fondatrice	Øksendal, B. (2003). Stochastic Differential Equations: An Introduction with Applications (6th ed.). Springer.	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
Alias	SDE, Itô equations, Stokastik Diferansiyel Denklemler (SDE)	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Apparentées	4	5
Résumé	Stochastic differential equations (SDEs) are differential equation models that combine a deterministic drift term — governing the average tendency of a system — with a stochastic diffusion term driven by a Wiener process (Brownian motion). Pioneered through Itô calculus by Kiyosi Itô in 1944 and given a comprehensive numerical treatment by Kloeden and Platen in 1992, SDEs are the standard modelling language for continuous-time systems subject to random noise, including financial asset prices, population dynamics, and physical processes.	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.