Good; I've only done that since 1980. But I have also programmed several GAs and SAs, especially for fitting multi-variable solutions. For example, solving passive electrical filter network designs of high complexity (say, 30-40 components) where not only the fit of the impulse response is important but the cost, components count, weight, and volume of the filter must be considered as well.
Your experience in programming GAs is?
I do not think that it is a scientific principle that nature tries to evolve a population to solve a certain problem. I think that is a hallmark of intelligence.
Yes, it does. It's called survival of the fittest. That is what GAs look for - the fittest population to work with.
And as with life, for GAs there is no "best answer". There is a large - sometimes infinite - solution set, and you're looking for a good local fit. The GA continues modifying the members of the solution set - the population - based upon their fitness rating. Much like living in the Andes will weed out those who are physically incapable of such life.
The only difference between a GA and the theory of evolution is that the GA stops when the researcher decides they've reached a good enough answer; they'll happily keep chugging along creating generations of answers ranging from ludicrous to darn near perfect. And every generation you'll get that same range, but as time goes on you'll get more and more that fall towards the well-suited versus the ludicrous.
Much like, over time, the hearts and lungs of the native SA Andean indians has grown to allow for higher oxygen capacity when living in the mountains.
About the same as Richard Hardison who was cited in Scientific American.
Yes, it does. It's called survival of the fittest. That is what GAs look for - the fittest population to work with.
No it doesn't, according to those who speak to evolution.
Darwin first used Spencer's phrase "survival of the fittest" as a synonym for "natural selection" in the fifth edition of On the Origin of Species, published in 1869.[1][2] It is a metaphor, not a scientific description,[3] and is both incomplete and misleading. Survival is only one component of selection, and for example where a number of males survive to reproductive age, but only a few ever mate, the difference in reproductive success stems mainly from ability to attract mates rather than ability to survive. In an evolutionary sense, fitness is the average reproductive output of a class of genetic variants in a gene pool, and should not be confused with physically fit meaning biggest, fastest or strongest, which does not necessarily lead to reproductive success.[4] It is not generally used by modern biologists, who use the phrase "natural selection" almost exclusively.