Abstract
This chapter examines the newest types of social simulations, which are object-based to represent social entities in ways that are more explicit than through variable-oriented models. The social simulations examined in this chapter constitute a rich and growing family of generative models consisting of two main classes: cellular automata and agent-based or multi-agent models. Both are generally seen as spatial models, but they can as easily capture network aspects of social complexity. Processes of urbanization and opinion dynamics are often simulated through the use of cellular automata. Spatial or organizational agent-based models are used to simulate social complexity in an increasing variety of domains, ranging from cultural dynamics to financial crises; from regional transportation systems to public health management; from humanitarian crises to global processes, such as climate change and the rise and fall of polities and civilizations. Agent-based simulations do this by using the versatility of multi-agent systems as computational frameworks within which modelers and programmers integrate social, natural, and artificial entities and dynamics. These social simulations often make use of other methodologies, such as network analysis or geographic information systems and remote sensing data.
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AÂ toroidal landscape is one where the borders wrap around, such that the landscape is continuous, without an edge.
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Cioffi-Revilla, C. (2014). Simulations III: Object-Oriented Models. In: Introduction to Computational Social Science. Texts in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-5661-1_10
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DOI: https://doi.org/10.1007/978-1-4471-5661-1_10
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