The concept of artificial neural networks (ANN) was inspired by the structure of the human brain. There was a strong belief that, if we were able to imitate this intricate structure in a very similar way, we would be able to create artificial intelligence. We are still on the road to achieving this. Although we can implement Narrow AI agents, we are still far from creating a Generic AI agent.
This chapter introduces you to the concept of ANNs and the two methods that we can use to train them (the gradient descent with error backpropagation and neuroevolution) so that they learn how to approximate the objective function. However, we will mainly focus on discussing the neuroevolution-based family of algorithms. You will learn about the implementation of the evolutionary process that's inspired by natural evolution and become familiar with...