Dear Maoqing Zhang ,

Neuroevolution is a paradigm that leverages evolutionary algorithms to train neural networks. Unlike traditional gradient-based optimization methods, which rely on backpropagation, neuroevolution evolves neural network architectures and parameters over generations.

https://vinaykumarmoluguri.medium.com/neuroevolution-training-neural-networks-using-evolutionary-algorithms-27487634d3bb#:~:text=Neuroevolution%20is%20a%20paradigm%20that,architectures%20and%20parameters%20over%20generations.

Regards,

Shafagat

Yes, evolutionary algorithms can be used for training neural networks. They optimize the network's weights and architecture by mimicking the process of natural selection, allowing for the exploration of a wide range of potential solutions.

Evolutionary algorithms can be used to enhance feature selection process which can further improve the training process.