Cellular automata and agent-based models

Abstract

Two classes of models that have made major breakthroughs in regional science in the last two decades are cellular automata (CA) and agent-based models (ABM). These are both complex systems approaches and are built on creating microscale elemental agents and actions that, when permuted over time and in space, result in forms of aggregate behavior that are not achievable by other forms of modeling. For each type of model, the origins are explored, as are the key contributions and applications of the models and the software used. While CA and ABM share a heritage in complexity science and many properties, nevertheless each has its own most suitable application domains. Some practical examples of each model type are listed and key further information sources referenced. In spite of issues of data input, calibration, and validation, both modeling methods have significantly advanced the role of modeling and simulation in geography and regional science and gone a long way toward making models more accountable and more meaningful at the base level.