Selecting Informative Data Samples for Model Learning Through Symbolic Regression
Continual model learning for nonlinear dynamic systems, such as autonomous robots, presents several challenges.First, it tends to be Dish Brushes computationally expensive as the amount of data collected by the robot quickly grows in time.Second, the model accuracy is impaired when data from repetitive motions prevail in the training set and outwei