Abstract: Learning differential evolution (DE) algorithms are widely adopted to address flexible job-shop scheduling problems (FJSPs) because of the optimization ability. However, traditional learning ...
Abstract: Robotic learning from sparse rewards can be a considerable challenge due to large amounts of data required for mastering a task. We explore the application of curriculum learning (CL) ...
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