Neuroevolution, or optimization of neural networks through population-based search, allows constructing intelligent agents in domains where gradients are not available and significant exploration is needed to find good solutions. This tutorial introduces participants to the basics of neuroevolution, reviews example application areas, and provides hands-on experience through a colab exercise.
(1) Neuroevolution for control
(2) Evolutionary Model Merging
(3) Quality Diversity for Model Merging.
Instructions are given in the notebook.