Space in Agent-Based Models

  • Kiril Stanilov


The chapter offers an overview of the issues related to the integration and representation of space in agent-based models (ABMs), with a focus on those models that can be considered spatially explicit. Key aspects of space in ABM are highlighted, related to: the role of space as an attribute of agents and the environment; as an interaction component; as a determinant of issues of scale; and as a tool for communicating and validating model outcomes. The chapter reviews the issues and challenges arising from the difficulties of integrating space in agent-based modeling. It outlines the emerging trend towards improving the level of realism in representing space, which can lead not only to an enhanced comprehension of model design and outcomes, but to an enhanced theoretical and empirical grounding of the entire field of agent-based modelling.


Cellular Automaton Residential Location Cellular Automaton Model Modifiable Areal Unit Problem Urban Modeling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Centre for Applied Spatial Analysis (CASA)University College LondonLondonUK

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