Code generation by genetic algorithms

Question

Evolutionary programming seems to be a great way to solve many optimization problems. The idea is very easy and the implementation does not make problems.

I was wond

Answer 1

Since this question was asked, the field of genetic programming has advanced a bit, and there have been some additional attempts to evolve code in configurations other than the tree structures of traditional genetic programming. Here are just a few of them:

• PushGP - designed with the goal of evolving modular functions like human coders use, programs in this system store all variables and code on different stacks (one for each variable type). Programs are written by pushing and popping commands and data off of the stacks.
• FINCH - a system that evolves Java byte-code. This has been used to great effect to evolve game-playing agents.
• Various algorithms have started evolving C++ code, often with a step in which compiler errors are corrected. This has had mixed, but not altogether unpromising results. Here's an example.
• Avida - a system in which agents evolve programs (mostly boolean logic tasks) using a very simple assembly code. Based off of the older (and less versatile) Tierra.