Using Genetic Algorithms to Increase the Learning Rate of Neural Networks

Abstract

Using Genetic Algorithms to Increase the Learning Rate of Neural Networks

Tsygankov V.A., Shabalina O.A., Kataev A.V.

Incoming article date: 25.12.2022

Investigation of ways to accelerate the training of neural networks using genetic algorithms and the study of the dependence of the speed of genetic algorithms on the mutation rate. In this study, a program was implemented on the Unity graphics platform using genetic algorithms and mutations to determine their optimal coefficient. The experiment showed that the learning rate really depends on the mutation rate, and the highest learning rate was obtained at 5-7,5%.

Keywords: machine learning, deep learning, genetic algorithm, optimization, neural network, artificial neuron, mutation, artificial intelligence, non-player character, optimization