Many historical processes are
dynamic, in that they change with time:
populations increase and decline, economies expand and contract, states grow and collapse, and so on. As such, practitioners of cliodynamics apply
mathematical models to explain
macrohistorical patterns—things like the rise of
empires,
social discontent,
civil wars, and
state collapse. Cliodynamics is the application of a
dynamical systems approach to the
social sciences in general and to the study of
historical dynamics in particular. More broadly, this approach is quite common and has proved its worth in innumerable applications (particularly in the
natural sciences). The dynamical systems approach is so called because the whole phenomenon is represented as a
system consisting of several elements (or
subsystems) that interact and change dynamically (i.e., over time). More simply, it consists of taking a
holistic phenomenon and splitting it into separate parts, assuming they interact with each other. In the dynamical systems approach, one explicitly specifies, using mathematical formulae, how different subsystems interact. This mathematical description is the model of the system, and one can use a variety of methods to study the dynamics predicted by the model, as well as to test it by comparing its predictions with observed
empirical dynamic evidence. Although the focus is usually on the dynamics of large groups of people, cliodynamics does not preclude the inclusion of human agency in its explanatory theories. Such questions can be explored with
agent-based computer simulations. ==Databases and data sources==