Safety and data efficiency are important concerns in data-driven control, especially for nonlinear systems with unknown dynamics and subject to disturbances. In this work, we consider a class of ...

Learning differential evolution (DE) algorithms are widely adopted to address flexible job-shop scheduling problems (FJSPs) because of the optimization ability. However, traditional learning DEs are ...