Tag Archives: Genetic Algorithms


via Inteligencia Artificial un Enfoque Práctico – Genetic Algorithms.


Training Neural Networks with Genetic Algorithms

via Training Neural Networks with Genetic Algorithms | One Life.

In this blog post I present my findings of an independent analytical and computational study of using genetic algorithms to train neural networks. This was my final project for an Introduction to Cognitive Science course that I took at The University of Texas at Austin, under Dr. David Beaver.
My motivation comes from the fact that animal brains, and particularly the human brain which is the topic of this entire course, are themselves genetically evolved neural networks. Therefore, artificial neural networks trained by genetic algorithms are a good starting rudimentary model of understanding the hardware of the brain. This sentiment is echoed in my primary reference, Evolutionary Algorithms for Neural Network Design and Training, Branke et al (1995). However, the paper mostly discusses the idea qualitatively, and I decided that since it is a relatively simple algorithm to implement, I would benefit my understanding to a much greater extent by implementing it myself on some simple networks.