Comparer des méthodes

	Microsimulation stochastique	Microsimulation multi-agents
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1957	1957 (microsimulation); 2000s (hybrid ABMS)
Auteur d'origine	Guy H. Orcutt	Orcutt, G. H. (microsimulation roots); Bonabeau, E. and others (ABM integration)
Type	Stochastic individual-level simulation	Hybrid simulation
Source fondatrice	Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123.	Birkin, M., & Clarke, M. (2012). The enhancement of spatial microsimulation models using geodemographics. Annals of Regional Science, 49(2), 515–532.
Alias	Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM	ABMS, Agent-Based Micro-Simulation, Microsimulation with Agent-Based Modeling, Hybrid ABM-Microsimulation
Apparentées	6	5
Résumé	Stochastic Microsimulation tracks a large population of individual units — people, households, or firms — through time by applying random draws from empirically estimated probability distributions at each transition event. Unlike deterministic counterparts, every state change is decided by chance, preserving realistic heterogeneity and allowing rigorous uncertainty quantification across multiple simulation runs.	Agent-based microsimulation (ABMS) merges traditional microsimulation's individual-level statistical tracking with agent-based modeling's behavioral rules and interaction mechanisms. It creates virtual populations of heterogeneous agents who evolve over time according to transition probabilities, adaptive behaviors, and social interactions, producing emergent system-level outcomes from micro-level dynamics.