Shawn,
The two ways to answer your question would either be to invoke artificial
selection (i.e., because you can design a genetic algorithm to do anything you
want, just as chicken breeders can keep whichever eggs or to invoke Wilson's
"trait group selection." In trait group selection you break selection into two
parts, within-group and between-group selection. If you do that, you can, under
the right conditions, find that types of individuals who reproduce less well
within any group can still out-compete the competition when you look between
groups. Math available upon request. I have a vague memory that this has come
across the FRIAM list before. 

Eric

On Fri, Jul  9, 2010 06:47 PM, Shawn Barr <[email protected]> wrote:
>
>
>Ted,
>
>I'm confused.  Why would a genetic algorithm ever select a hen that produces
fewer eggs over a hen that produces more eggs?
>
>
>Shawn
>
>


>>On Fri, Jul 9, 2010 at 2:57 PM, Ted Carmichael <<#>> wrote:
>Nick, this is perfect.  Thank you!>
>
>>BTW - the reason for this request is, my advisor and I were asked to write a
chapter on Complex Adaptive Systems, for a cognitive science textbook.  In it,
I talk briefly about GA, and put this story about the chickens in because I
thought it was a neat example.
>
>>
>
>>I'll add the references now.  Much appreciated.
>>
>
>>
>-t
>
>>
>>
>>
>>On Fri, Jul 9, 2010 at 12:28 PM, Nicholas Thompson <<#>> wrote:
>
>
>
>
>>
>>
>>
>
>>
>>
>>Ted, 
>>
> 
>>Ok.  So, if I am correct,  this was an actual EXPERIMENT done by two
researchers at Indiana University, I think.  As  I "tell" the "story", it was
the practice to use individual selection to identify the most productive
chickens, but the egg production method involved crates of nine chickens.  The
individual selection method inadvertently selected for the most aggressive
chickens, so that once you threw them together in crates of nine, it would be
like asking nine prom queens to work together in a tug of war.  The chickens
had to be debeaked or they would kill each other.  So, the researchers started
selection for the best producing CRATES of chickens.  Aggression went down,
mortality went down, crate production went up, and debeaking became
unnecessary.  
>
>
>>
> 
>>The experiment is described in Sober and Wilson's UNTO OTHERS or Wilson's
EVOLUTION FOR EVERYBODY,  which are  safely tucked away in my book case 2000
miles away in Santa Fe.   Fortunately, it is also described in 
>
>
>> 
>>Dave Wilson's blog 
<http://www.huffingtonpost.com/david-sloan-wilson/truth-and-reconciliation_b_266316.html>
>
>
>
>>
> 
>>Here is the original reference: 
>>
> 
>>GROUP SELECTION FOR ADAPTATION TO MULTIPLE-HEN CAGES : SELECTION PROGRAM AND 
>>DIRECT RESPONSES 
>Auteur(s) / Author(s)
>>
><http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=auteursNom:%20%28MUIR%29>
> ; 
>Revue / Journal Title
>>
><http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=listeTitreSerie:%20%28Poultry%20science%29>
>    ISSN  
><http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=identifiantsDoc:%20%280032-5791%29>
>   CODEN POSCAL  
>
>
>Source / Source
>>1996, vol. 75, no4, pp. 447-458 [12 page(s) (article)]
>> 
>>If you Google "group selection in chickens," you will find lots of other 
>>interesting stuff. 
>> 
>> 
>>Let me know if this helps and what you think.  
>> 
>>N
>> 
>>Nicholas S. Thompson
>>
>>Emeritus Professor of Psychology and Ethology, 
>>Clark University (<#>)
>><http://home.earthlink.net/%7Enickthompson/naturaldesigns/>
>>
><http://www.cusf.org> [City University of Santa Fe]
>> 
>> 
>> 
>
>
>> 
>
>>
>>----- Original Message ----- 
>>
>From: <a title="" href="#" target="">Ted Carmichael</a> 
>
>>
>>
>To: <a title="" href="#" target="">The Friday Morning Applied Complexity 
>Coffee Group</a>
>
>
>
>>
>>
>Sent: 7/9/2010 5:34:29 AM 
>
>>
>Subject: [FRIAM] Real-world genetic algorithm example... help!
>
>>
>
>Dear all,
>>
>
>>I'm trying to find reference to a story I read some time ago (a few years, 
>>perhaps?), and I'm hoping that either: a) I heard it from someone on this 
>>list, or b) someone on this list heard it, too.
>>
>
>>Anyway, it was a really cool example of a real-world genetic algorithm, 
>>having to do with chickens.  Traditionally, the best egg-producing chickens 
>>were allowed to produce the offspring for future generations.  However, these 
>>new chickens rarely lived up to their potential.  It was thought that maybe 
>>there were unknown things going on in the clusters of chickens, which 
>>represent the actual environment that these chickens are kept in.  And that 
>>the high producers, when gathered together in these groups, somehow failed to 
>>produce as many eggs as expected.
>
>
>>
>
>>So researchers decided to apply the fitness function to groups of chickens, 
>>rather than individuals.  This would perhaps account for social traits that 
>>are generally unknown, but may affect how many eggs were laid.  In fact, the 
>>researchers didn't care what those traits are, only that - whatever they may 
>>be - they are preserved in future generations in a way that increased 
>>production.
>
>
>>
>
>>And the experiment worked.  Groups of chickens that produced the most eggs 
>>were preserved, and subsequent generations were much more productive than 
>>with the traditional methods.
>>
>
>>Anyway, that's the story.  If anyone can provide a link, I would be very 
>>grateful.  (As I recall, it wasn't a technical paper, but rather a story in a 
>>more accessible venue.  Perhaps the NY Times article, or something similar?)
>
>
>>
>
>>Thanks!
>>
>
>>-Ted
>
>
>
>
>
>
>
>>============================================================
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>FRIAM Applied Complexity Group listserv
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Eric Charles

Professional Student and
Assistant Professor of Psychology
Penn State University
Altoona, PA 16601


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