steeg@ai.toronto.edu ("Evan W. Steeg") (03/05/91)
In article <Mar.2.23.03.44.1991.21960@athos.rutgers.edu> cphoenix@csli.stanford.edu (Chris Phoenix) writes: >From what I've heard, it is true that a nanomachine can be easily designed >to avoid mutation. But I don't believe it would be that hard to build one >that mutated. All you'd need is some encoding of the specification in a >format such that a high (say, .01%) number of random changes to the spec >produced something meaningful. Then program it to change 3 bits of the spec >before it replicates itself. "genetic" algorithms work in finding good >solutions to problems, and while I don't know much about them, it seems that >there should be a way to code a machine spec so that it could be optimized in >this way. >.... >[Genetic algorithms are a good example of what I'm talking about. > As an experiment, try writing a self-reproducing program in C that > introduces random changes in itself, and still works. Genetic > algorithms use highly inefficient production system mechanisms > for the same reason cells do--because they are the only way (we > know of) to make evolution actually work. > --JoSH] Of course, the dynamics of evolution ("artificial" or "biological", to the extent that that distinction exists), and hence the efficacy of the evolution as an optimizer of something-or-other, depends greatly on the specifics of the "mutation" mechanisms. *Very different* sorts of things happen if changes occur at the "bits" level in the C program (i.e., the level of individual nucleotides in DNA/RNA) versus if changes also occur at the level of whole C keywords or lines of code or function definitions (genes or linearly distributed multi-gene-and-promoters-etc. sets). All of the various theories and observed or postulated mechanisms for *large* sections of DNA/RNA/Protein jumping around, inverting, repeating, etc. have huge implications for evolutionary biology, and are therefore also of serious interest to those who would study or employ "artificial evolution". (BTW of course the term "mutation" is not typically used by molecular biology people for these larger kinds of DNA change and movement.) -- Evan -- Evan W. Steeg (416) 978-7321 steeg@ai.toronto.edu (CSnet,UUCP,Bitnet) Dept of Computer Science steeg@ai.utoronto (other Bitnet) University of Toronto, steeg@ai.toronto.cdn (EAN X.400) Toronto, Canada M5S 1A4 {seismo,watmath}!ai.toronto.edu!steeg [Let me try to clear up what may be a common misconception about evolution here. *Most* of evolution is *not* done by mutation but by mixing and matching the genes from the parents in sexual reproduction. Mutation only comes in when you need to expand the "solution space" rather than simply search it. Even when it gets expanded, though, it must still be searched. Working genetic algorithms tend to have a mechanism very analogous to sexual reproduction for this reason. --JoSH]