arXiv cs.NE
· Papers
When does learning pay off? A study on DRL-based dynamic algorithm configuration for carbon-aware scheduling
arXiv:2604.01886v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (DRL) has recently emerged as a promising tool for Dynamic Algorithm Configuration (DAC), enabling evolutionary algorithms to adapt their parameters online rather than relying on static tuned configurations. While DRL can learn effect