problem solving in evolutionary algorithmic processes
I've been thinking a lot about evolution recently. I just finished reading a book on evolution (Darwin's Dangerous Idea) and I've got a few particular questions. I've only formulated one so far, the rest are just intuitions at this point.
The one question I'm having trouble with is: how do evolutionary processes identify problem solving situations?
Essentially, how do the algorithmic processes of evolution recognize when they're in a "problem solving situation"?
Some things that I've come upon in trying to answer my question is that perhaps evolution is in a constant state of problem solving. It is not that the algorithmic processes ever stop working out "problems"; instead, they continually "work" within their evolutionary process.
However, the problem I have with my own attempt (probably poor) to answer my own question, is that I don't see how the evolutionary processes can ever "stop" at the good outcomes that eventually get produced. Is this where the idea of "fitness" comes in? Do the outside pressures of the environment "cause" the algorithmic process to stop churning out possible solutions to a problem that now has a solution? Or is it the case, that something else determines when the solved problem gets left alone and kept, as a trait to that species (for example)?
Ahh my brain hurts...been at school all day and thinking about evolution along with everything else!
The implication that we should put Darwinism on trial overlooks the fact that Darwinism has always been on trial within the scientific community. -- From Finding Darwin's God by Kenneth R. Miller
Chaos and chance don't mean the absence of law and order, but rather the presence of order so complex that it lies beyond our abilities to grasp and describe it. -- From From Certainty to Uncertainty by F. David Peat