Welcome to Genetic Programming Source

Welcome to Genetic Programming Source, a website dedicated to the wonderful world of Genetic Programming.

Genetic Programming (GP) is a methodology for automatically solving problems with computers, inspired by biological evolution. GP begins with a statement of the problem at hand and through analogues of natural selection, crossover and mutation develops potential solutions. The creative power of GP is astounding, being able to automatically produce complex solutions to a wide-range of domains including statistical modelling, electronic circuitry, game-playing strategies, computational finance, and even art.

Genetic Programming is not altering the genes of living beings to produce useful results, but that's a common misconception! This website was created for several purposes, outlined below:

  • To celebrate the elegance of Genetic Programming: For many people, computer science seems like a downright boring discourse, but even these people can't help but be fascinated by GP. Not even considering its real-world applications, GP is an intriguing field for its own sake and when we start examining what GP can do, the potential seems unimaginably great. GP is just interesting, if nothing else.
  • To explain Genetic Programming to a general audience: Most work on the subject of GP is geared towards a particularly advanced computer programming crowd. Read Koza's 1992 book and you are immediately bombarded with complex mathematical formulae and cryptic CS-talk. This need not be the case. GP should be accessible to a more general audience.
  • To explain how Genetic Programming works to programmers: An interest in computer science certainly helps reach a more full understanding of GP, and I imagine most people visiting this site probably have some programming experience. While we try to keep the CS-jargon to a minimum, we do include descriptions and sample java code for several GP algorithms to help computer programmers better understand GP.

If you're new to Genetic Programming and would like to learn more, please read our Beginner's Guide to Genetic Programming.

If you have any comments or questions concerning genetic programming, I would love hear from you. Just If you feel so compelled, don't hesitate to show your support by donating through Paypal.