The theory of evolution can certainly describe some of what we see, however, it is woefully incomplete in its suggested role in creation theory. And while randomness clearly has a role in nature, it has become the default go-to for too many things which science cannot explain. Notice how the parent just casually tossed out randomness as the "obvious" explanation for such complex behavior, as if it was a foregone conclusion. It's anything but.
These are tremendously organized and complex systems (including the creation of the Universe itself), for which the prime driver is supposedly randomness. I just think it funny that people deride religious explanations as utter silliness, while so willingly believing that randomness is responsible for, effectively, everything we see. What is scientific about that? We even suspend basic laws of thermodynamics regarding matter creation to accomodate our random-centric explanations.
Better to just say, "we don't know".
Put another way, genetic algorithms are derived from our theories about nature, not the other way around. That they can effectively model solution sets to (much simpler) problems that we identify or create, neither proves nor disproves our theories about nature.
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.
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.