Symbots are simple little robots that have wheels and two sensors. They live on the unit square.

They're evolved to seek out a source of energy/light/food at the center of the square.

This code uses the Watchmaker framework. Watchmaker is on github at @dwdwyer/watchmaker.

Here is a sample image showing a sample path of an evolved individual randomly placed on the unit square seeking the source at the center of the square.

This example comes from a book on evolutionary computation, the relevant pages of which you can see here.

IF you type in "neuroevolution" on Google scholar, you'll get lots of papers about evolving neural networks for actual useful things, like classifying data and time series prediction.

A readable paper that is widely cited on this topic is:

Randall D. Beer and John C. Gallagher. Evolving dynamical neural networks for adaptive behavior. Adaptive Behavior, 1:92–121, 1992.

You can grab a copy here.