6 Neuroevolution optimization

This chapter covers

  • How DL networks optimize or learn
  • Replacing backpropagation training of neural networks with GAs
  • Evolutionary optimization of neural networks
  • Employing evolutionary optimization to a Keras DL model
  • Scaling up neuroevolution to tackle image class recognition tasks

In the last chapter, we managed to get our feet wet by employing evolutionary algorithms for the purposes of optimizing DL network hyperparameters. We saw how using EA could improve the search for hyperparameters beyond simple random or grid search algorithms. Employing variations of EA, such as PSO, evolutionary strategy, and differential evolution, uncovered insights into methods used to search and for hyperparameter optimization ...

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