The Simple Discrete Event Simulator requires the modeler to define simulation entities, the entities' state, and the events that cause the entities to transition their state. The following object-oriented pseudocode shows how we have implemented the entities' state and the movement transition function in the simple movement model:
This is a bare bones implementation. To provide more detail, we could incorporate the entity's average speed, distance traveled and frequency of movement into its state. The transition function would then change to make use of this additional information.
Let's assume that we have data describing the prowling behavior of some carnivore as linearly correlated to the animal's age. We can incorporate this information into our simulation as follows:
Of course, we can get even more detailed by finding the distribution of the varience in the above data. Assume a Gaussian distribution, the transition function now becomes:
To actually make these distributions worthwhile, the simulation has to have an age dispersion that reflects nature. Again we have to return to field data for average case behavior and variation of that behavior in a population.