Abstract
Social simulations became famous in the 1960s through dynamical models used to predict the future of the world in terms of population growth, urbanization, pollution, and other variables. This chapter examines the contemporary landscape of variable-based model used in CSS. The emphasis is on system dynamics models and queuing models, two of the most important classes of variable-oriented models in use today. Both social simulation modeling traditions are examined in terms of the methodology introduced in the previous chapter and examples are provided from areas of pure and applied CSS research. In general, system dynamics simulations emphasize deterministic causal processes, whereas queuing simulations highlight stochastic processes and mean, statistical behaviors. However, this is only a matter of general orientation, since both classes of models can share some features of the other, especially system dynamics models with probabilistic components. Both classes of models comprise a large scientific literature and numerous applications that range from basic scientific research to applied policy domains in national defense and homeland security, transportation, public health, commercial and management applications, to name just a few.
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Cioffi-Revilla, C. (2017). Simulations II: Variable-Oriented Models. In: Introduction to Computational Social Science. Texts in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-50131-4_9
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DOI: https://doi.org/10.1007/978-3-319-50131-4_9
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-50131-4
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