🚀 go-pugleaf

In article <1jlmb2INNjp4@gaia.ucs.orst.edu>, choup@ava.bcc.orst.edu (Ping Chou)
writes:
> 
>         Or the development of genetic algorithms has completed?
> 
>         Isn't it true that selection/mating/mutation/chromosome/hybrid/
> genotype/phenotype/gene/... are taken from genetics?

   The words yes, but genetic algorithms go far beyond the biological genetic 
model.  There are a number of papers on Lamarckian genetic algorithms, for
example.  Lamarck is a discarded reject in genetic theory; in genetic algorithms
his ideas are useful.

   I suppose what I'm getting at here is the point Chris Langston makes when he
attempts to difine the field of Artificial Life.  He says Alife is an attempt
to study life as it can be rather than as it is.  The practical code-hacking
implications of this are that while biology has benn and will continue to
be a source of insparation one cannot let it be a strait jacket.

>         Don't you think you may be able to discover new algorithms from
> studying genetics?

   Well, biology in general actually, but yes I'd guesstimate a roughly 100%
chance that there are good ideas for genetic algorithms lurking in biology. 
The paper I mentioned last week (Iterated Prisoner's Dillemma with Choice and
Refusal) studies the effect of rational partner selection on a genetic
algorithm.  Our inspiration for this was mate selection behavior in biology.
The effect was startling - the algorithm converged to places it never went
before.

   The problem is that taking a pile of courses won't help.  I've taken courses
and they consist of irrelevant trivia and foundational material valuable to work
within the discipline.  They seldom give the gestalt one needs to rip off good
ideas.  I maintain reading Science and Science news is a better way to get the
cross specialization you need to be a better GA programmer.
 
>         Do you really believe the complete genome of HIV is just a 4-state
> bits encoded string?

   Since there are at least thousands of HIV pseudospieceis, no.  On the
other hand the hardware we evolve our stings on, like my DEC station 3100,
is considerably less sophistocated than the hardware an HIV virus runs on,
a human cell.  The biology used to "run" a virus is roughly totally unrelated 
to the hardware used to run a GA.
 
>         Then please, give youself a chance, take a look at any modern
> genetics text book, and be a cross-discipline expert.

   You seem confused as to the source of knowledge...   ...the very best thing
you can do is ask an expert a specific question and ask questions while he
answers until you understand.  Reading Science will prevent you from being so
ignorant that said expert will refuse to talk to you.

> --Ping
> 
>         BTW, I would appreciate any reasonable arguments because I'm trying
> to learn ai-genetic from the genetics side.

   Good luck.

Dan
Danwell@IASTATE.EDU