Rule-based models are based on logic programming with condition-action expressions, where the left side of the expressions consists of several conditions that returns a logical result, and the right side consists of several actions. Rules in rule-based models indirectly specify a mathematical model. However, unlike equation-based models which refer to the overall or aggregate behaviour of a system, rule-based models focus on the behaviour of the individual components of a system. That’s why the implementation of rule-based models is most often done by cellular automata models or agent-based models, in which the aggregate behaviour of the system emerges from the interaction of the individual agents or cells over time. Many geographic patterns and dynamics are formed by systems of interacting actors/cells with heterogeneous characteristics and behaviours, in which such dynamic behaviours can be implemented as rules. The aim of this topic is to provide knowledge about rule based models and to understand their advantages and disadvantages.
Understand how models can be specified into logical rules
Evaluate when rule-based models can be applied to spatiotemporal problems
Discuss options of combining rule-based models with other individual modelling approaches
Completed (GI-N2K)