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

The biggest selling point of genetic algorithms, as you say, is that they are dirt simple. They don't have the best performance or mathematical background, but even if you have no idea how to solve your problem, as long as you can define it as an optimization problem you will be able to turn it into a GA.

Programs aren't really suited for GA's precisely because code isn't good chromossome material. I have seen someone who did something similar with (simpler) machine code instead of Python (although it was more of an ecossystem simulation then a GA per se) and you might have better luck if you codify your programs using automata / LISP or something like that.

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On the other hand, given how alluring GA's are and how basically everyone who looks at them asks this same question, I'm pretty sure there are already people who tried this somewhere - I just have no idea if any of them succeeded.