Abstract
Automata-based models have enjoyed widespread application to urban simulation in recent years. Cellular automata (CA) and multi-agent systems (MAS) have been particularly popular. However, CA and MAS are often confused. In many instances, CA are paraphrased as agent-based models and simply re-interpreted as MAS. This is interesting from a geographical standpoint, because the two may be distinguished by their spatial attributes. First, they differ in terms of their mobility: CA cannot “move”, but MAS are mobile entities. Second, in terms of interaction, CA transmit information by diffusion over neighborhoods; MAS transmit information by themselves, moving between locations that can be at any distance from an agent’s current position. These different views on the basic geography of the system can have important implications for urban simulations developed using the tools. It may result in different space-time dynamics between model runs and may have important consequences for the use of the models as applied tools. In this chapter, a patently spatial framework for urban simulation with automata Tools is described: Geographic Automata Systems (GAS). The applicability of the GAS approach will be demonstrated with reference to practical implementations, showing how the framework can be used to develop intuitive models of urban dynamics.
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Torrens, P.M. (2006). Geosimulation and its Application to Urban Growth Modeling. In: Portugali, J. (eds) Complex Artificial Environments. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-29710-3_8
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DOI: https://doi.org/10.1007/3-540-29710-3_8
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