AdaE-SAEA uses meta-RL to adaptively select infill criteria and ensemble surrogate strategies (bagging/boosting) that balance robustness and accuracy across search phases in SAEAs.
R2 indicator and deep reinforce- ment learning enhanced adaptive multi-objective evolutionary algo- rithm.arXiv preprint arXiv:2404.08161, 2024
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Meta-Black-Box Optimization with Ensemble Surrogate Modeling for Robustness-Accuracy Trade-off within SAEA
AdaE-SAEA uses meta-RL to adaptively select infill criteria and ensemble surrogate strategies (bagging/boosting) that balance robustness and accuracy across search phases in SAEAs.