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What genetic algorithms do is validate the process of evolution and deriving complexity through unguided processes. While this doesn't "prove" biological evolution, it shows that there is nothing inherently impossible about greater complexity being derived from lesser complexity. I'd say this is a very important result.



>What genetic algorithms do is validate the process of evolution and deriving complexity through unguided processes.

No. They absolutely do nothing of the sort.

Do you truly understand how GAs work? There is nothing "unguided" about them. They are pre-programmed, with crossover functions, fitness measures, etc. As the OP mentioned, they operate within relatively simple, well-defined "environments". They are effectively used as a heuristic tool for searching solution sets to defined problems.

Also, no one claimed that it's inherently impossible to derive greater complexity from lesser complexity. That's a straw man. Still, just because it's possible doesn't mean it has actually happened or has any bearing whatsoever on the facts (actual evolution). But, beyond that, GAs are not purposed with "deriving complexity", nor is that a desirable result in their application. The goal is not to produce more complex offspring, but more suitable solutions.

In short, your comment is completely misguided.


>They are pre-programmed, with crossover functions, fitness measures, etc.

And these are all abstractions of the process of evolution in general, each one being analogous to genetic mutations, sex or gene sharing, fitness within an environment, etc.

>Also, no one claimed that it's inherently impossible to derive greater complexity from lesser complexity. That's a straw man

Plenty of people claim this; I never attributed that statement to you.

>GAs are not purposed with "deriving complexity", nor is that a desirable result in their application.

The "goal" is irrelevant to the question I'm addressing. Many people claim that evolution is impossible because complexity cannot be derived from "nothing". Genetic algorithms disprove that claim. The environment of a GA being artificial is irrelevant. Some GA's do in fact create complexity that even we cannot comprehend, I am reminded of a GA that developed a circuit design (for a DAC perhaps it was) that is completely incomprehensible, yet it works perfectly. This process validates the principle of evolution.




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