An Introduction to Neuroevolution

Recently I’ve been really interested in getting my computer to play games by itself. Call me lazy, but with so much to do every day it’s nice to automate some of the less productive tasks. I did some reading and came across a technique called neuroevolution — a method for using natural evolution to create a structure for a neural network.

During my scouring of the internet, I found a paper called Evolving Neural Networks through Augmenting Topologies that discusses an algorithm commonly known as NEAT. …

Maybe you’re a data scientist trying to visualize some newfangled, complex dataset. Maybe you’re an artist that wants to try out some new kind of image-warping technique. Maybe you’re an aspiring AI enthusiast who just wants to get into image generation. Well, meet autoencoders — a feed-forward neural network whose primary focus is distilling larger concepts into their primary features.

What is an Autoencoder?

An autoencoder is an hourglass-shaped feed-forward neural network where the input and output are the same. What’s the point of that? …

It’s the year 2050. Flying cars are a thing, we’ve figured out nuclear fusion, and swarms of drones are flying about in the sky. One morning, while you’re out for your daily walk, you stop and look up at those drones. The computer that controls them must be extremely powerful, able to plot all of their courses in real-time. Nope! They’re doing it all by themselves thanks to emergent properties.

What Are Emergent Properties?

Emergent properties are, in general, properties held by a system that is not defined by any of its individual components. What do I mean by that? …