Predicting CMA-ES Operators as Inductive Biases for Shape Optimization Problems

Author:

Friess Stephen1,Tino Peter1,Menzel Stefan2,Sendhoff Bernhard2,Yao Xin1

Affiliation:

1. University of Birmingham,CERCIA, School of Computer Science,UK

2. Honda Research Institute Europe, Offenbach a.M.,Germany

Publisher

IEEE

Reference25 articles.

1. Deep learning as a competitive feature-free approach for automated algorithm selection on the traveling salesperson problem;seiler;Conference on Parallel Problem Solving from Nature,0

2. Representing Experience in Continuous Evolutionary optimisation through Problem-tailored Search Operators

3. Artificial neural networks as feature extractors in continuous evolutionary optimization [accepted];friess;2021 IEEE International Joint Conference on Neural Networks (IJCNN),0

4. A comprehensive comparison of shape deformation methods in evolutionary design optimization;sieger;Proceedings of the International Conference on Engineering Optimization,0

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