After years at the periphery of the social sciences, simulation is now emerging as an important and widely used tool for understanding social phenomena. Through simulation, researchers can identify causal effects, specify critical parameter estimates, and clarify the state of the art with respect to what is understood about how processes evolve over time. Moreover, simulation methods are often the most time-effective and cost-effective means of doing so and sometimes are the only means. This essay outlines current developments in the four main branches of social science simulation: systems dynamics models, network models (including neural network models), spatial models, and agent-based models. The limitations of simulation modeling are also discussed, along with methods for evaluating the validity of social science computer simulations.
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