Re-visiting Reservoir Computing architectures optimized by Evolutionary Algorithms. (arXiv:2211.06254v1 [cs.NE])

For many years, Evolutionary Algorithms (EAs) have been applied to improve
Neural Networks (NNs) architectures. They have been used for solving different
problems, such as training the networks (adjusting the weights), designing
network topology, optimizing global parameters, and selecting features. Here,
we provide a systematic brief survey about applications of the EAs on the
specific domain of the recurrent NNs named Reservoir Computing (RC). At the
beginning of the 2000s, the RC paradigm appeared as a good option for employing …

algorithms architectures arxiv computing evolutionary algorithms