"Tim Tyler" <[email protected]> wrote in message news:[email protected]... > irr <[email protected]> wrote or quoted: > > "Tim Tyler" <[email protected]> wrote in message > > > IRR <[email protected]> wrote or quoted: > > > > The best-established way of measuring complexity is to > > > use Kolmogorov complexity. > > > > > > This: > > > > > > * Confines discussion to digital phenomena; > > > * Is difficult to measure; > > > * Has a subjective element - since it depends on a > > > choice of descriptive language. > > > > > > The first is no problem, if we are content to confine > > > ourselves to the complexity of genomes. > > > > > > The second is a problem in theory: > > > > > > * Except in a few trivial cases, you can only put > > > bounds on the metric - > > > rather than measure it exactly (and even then the > > > lower bound is rarely > > > much use). I would suggest ignoring this problem - > > > and measuring the value using a conventional high- > > > quality compressor of a type that is capable of > > > dealing well with repeated sequences. > > > > > > ...and in practice... > > > > > > * You need to sequence the genome in question before > > > you can measure its complexity; > > > > > > The third makes the metric less asethetically > > > attractive. My approach would probably be to say > > > something along the lines of: > > > > > > "Always use FORTRAN-77 as your language". > > ....] > > > > IMO this third problem -- choosing a language with which > > to quantify complexity -- is still *the* showstopper > > when it comes to biology. > > I like the answer I gave. > > I almost always give this answer. > > So far - IMO - I have had no serious complaints ;-) Better check your audience ;-). > > There may be a few even more "unbiased" languages out > there - but FORTRAN-77 is convenient enough. > > > While we might all agree that the primate brain is an > > incredibly complex organ, it's not at all agreed upon > > what it is we mean by this. For example, a Kolmogorov > > measure fails miserably in classifying the brain as > > complex, after all you're really only talking about two > > dozen or so different recognized cell types stamped out > > in enormous repetition with iterated connections between > > them -- in other words, a digital representation of the > > brain is incredibly compressible. > > IMO - this makes no sense at all :-| > > An acceptable digital version of the brain would handle > the same I/O - and produce similar inputs from similar > outputs. This sounds like a job for a huge computer with > an *extremely* lengthy description to me - and of course a > correspondingly enormous Kolmogorov complexity. > -- > __________ > |im |yler http://timtyler.org/ [email protected] Remove > lock to reply. > Certainly a huge computer, but really an extremely lengthy description? Check out the top 500 list (top500.org) -- the fastest computers in the world are and will continue to be iterations of the single processor system you're likely reading this reply on right now. While such massively parallel systems -- including the human brain -- are increadibly impressive to look at, they are remarkably regular. Kolmogorov essentially a measure of regularity; low in highly parallel architectures and high in random ones.