I've programmed computers since 1965. It is not obvious to me that he is ignorant of how they work. Richard Dawkins seems to think that the Weasel program is a genetic algorithm. At least he touts it as such. Plus there are many others who think so. Monash University, the largest university in Australia, teaches this.
In a genetic algorithm (GA) we try to evolve a population of candidate solutions to a certain problem. In this case we are trying to evolve a population of strings to match the line "methinks it is like a weasel".
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.
The tricky thing about evolution--and I agree that it's a philosophical issue, but no more than that--is that the problem is changing along with the solution, and the exact nature of the problem is unknown until after the fact. The problem is survival in a changing environment. The particular problem at any one time may involve an ice age, or it may involve an extended dry period or an asteroid strike, but which it is is unknown while the evolution is going on. But nature comes up with a lot of solutions, and with luck one of them matches the problem.
It's like betting on roulette. You don't know the problem (the ball lands on 18) when you bet, but there are lots of solutions (red, even, 1-18...). It doesn't take any intelligence to come up with a solution for the problem.
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.