Sliding Window Symbolic Regression for Detecting Changes of System Dynamics

In this chapter we discuss sliding window symbolic regression and its ability to systematically detect changing dynamics in data streams. The sliding window defines the portion of the data visible to the algorithm during training and is moved over the data. The window is moved regularly based on the generations or on the current selection pressure when using offspring selection. The sliding window technique has the effect that population has to adapt to the constantly changing environmental conditions.