Types of Simulation Systems: Dynamic, Discrete, Continuous and Social Simulation Systems

- Dynamic Simulation Systems: It has a model that accommodates for changes in data over time. This means that the input data affecting the results will be entered in to the simulation during its entire lifetime than just at the beginning. A simulation system used to predict the growth of the economy may need to incorporate changes in economic data is a good example of a dynamic simulation systems.

- Discrete Simulation Systems: These systems use models that have discrete entities with multiple attributes. Each of these entities can be in any state, at any given time, represented by the value of its attributes. The state of the system is a set of all the states of all its entities. This stage changes one discrete step at a time as events happen in the system. therefore, the actual designing of the simulation involves making choices about which entities to model. Examples include simulated battlefield scenarios, highway traffic control systems etc.

- Continuous Simulation Systems: If instead of using a model with discrete entities, we use data with continuous values, we will end up with continuous simulation.

- Social Simulation Systems: It is not a technique by itself but uses the various types of simulation described above. However, because of the specialized application of those techniques for social simulation, it deserves a special mention of its own. The field of social simulation involves using simulation to learn about and predict various social phenomenon such as voting patterns, migration patterns, economic decisions made by the general population etc.