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Real-world genetic algorithm example... help!

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Ted Carmichael

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

James Steiner

Re: Real-world genetic algorithm example... help!

I remember it too! It seems that individual high producers were also
bullies, tending to stomp on other hens' eggs and attack the other
hens. So by breeding these hens, they created entire pens of nothing
but psychotic killer hens, stomping each other's eggs and tearing each
other apart.

But by looking at overall pen production, and breeding those hens,
they got pens of happy, friendly hens that didn't destroy eggs, or
each other.

~~James

On 7/9/10, Ted Carmichael <[hidden email]> wrote:

> 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
>

Douglas Roberts-2

Re: Real-world genetic algorithm example... help!

You do realize how much that sounds like a description of FRIAM, don't you?

;-}

--Doug

On Fri, Jul 9, 2010 at 7:17 AM, James Steiner <[hidden email]> wrote:

I remember it too! It seems that individual high producers were also
bullies, tending to stomp on other hens' eggs and attack the other
hens.

John Kennison

Re: Real-world genetic algorithm example... help!

In reply to this post by Ted Carmichael

I believe it is referred to in the book "Unto Others" by David Sloan Wilson and Eliot Sober.

________________________________________
From: [hidden email] [[hidden email]] On Behalf Of Ted Carmichael [[hidden email]]
Sent: Friday, July 09, 2010 5:34 AM
To: The Friday Morning Applied Complexity Coffee Group
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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Paul Paryski

Re: Real-world genetic algorithm example... help!

In reply to this post by Ted Carmichael

This is also applicable to most politicians. cheers, Paul

-----Original Message-----
From: Ted Carmichael <[hidden email]>
To: The Friday Morning Applied Complexity Coffee Group <[hidden email]>
Sent: Fri, Jul 9, 2010 3:34 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.

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.

Thanks!

-Ted

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Nick Thompson

Re: Real-world genetic algorithm example... help!

In reply to this post by Ted Carmichael

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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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.

Nicholas S. Thompson

Emeritus Professor of Psychology and Ethology,

Clark University ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

Ted Carmichael

Re: Real-world genetic algorithm example... help!

In reply to this post by Douglas Roberts-2

LOL ... you guys crack me up.

-t

On Fri, Jul 9, 2010 at 9:32 AM, Douglas Roberts <[hidden email]> wrote:

You do realize how much that sounds like a description of FRIAM, don't you?

;-}

--Doug

On Fri, Jul 9, 2010 at 7:17 AM, James Steiner <[hidden email]> wrote:

I remember it too! It seems that individual high producers were also
bullies, tending to stomp on other hens' eggs and attack the other
hens.

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Ted Carmichael

Re: Real-world genetic algorithm example... help!

In reply to this post by Nick Thompson

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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Shawn Barr

Re: Real-world genetic algorithm example... help!

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 <[hidden email]> 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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Ted Carmichael

Re: Real-world genetic algorithm example... help!

Well, it wouldn't ... unless you were selecting for the lowest producing hens.

The GA selects for the groups of chickens that produce the most eggs, not the individuals. Some of those individuals may actually not produce many eggs, but they must somehow help the ones that do produce more eggs (in their group).

-t

On Fri, Jul 9, 2010 at 6:47 PM, Shawn Barr <[hidden email]> 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 <[hidden email]> 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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Douglas Roberts-2

Re: Real-world genetic algorithm example... help!

In reply to this post by Shawn Barr

It's kind of a cosmic yolk.

On Fri, Jul 9, 2010 at 4:47 PM, Shawn Barr <[hidden email]> 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 <[hidden email]> 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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Victoria Hughes

Re: Real-world genetic algorithm example... help!

In reply to this post by Ted Carmichael

Fascinating. The original story and its appearance/discussion here.

I am writing a book on the five simple stages that projects move through, from idea to reality.

Part of the chapter, whose midst I am in, discusses "teams", inner and outer: the grouping of abilities and attributes required to get unstuck and get something done.

Sometimes the 'crate o' chickens' is outside of us, if we are working with a team. Sometimes our team is made from aspects of our own mind: the internal - complex- interconnection of knowledge, abilities, ideas, etc all squawking, laying, attacking, defending, at once, inside our brains.

Glad to know that even among the inheritors of the reptilian hind brain there can be cooperation for a larger good, even if that is for more chickens.

Tory

On Jul 9, 2010, at 4:53 PM, Ted Carmichael wrote:

Well, it wouldn't ... unless you were selecting for the lowest producing hens.

The GA selects for the groups of chickens that produce the most eggs, not the individuals. Some of those individuals may actually not produce many eggs, but they must somehow help the ones that do produce more eggs (in their group).

-t

On Fri, Jul 9, 2010 at 6:47 PM, Shawn Barr <[hidden email]> 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 <[hidden email]> 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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

-----------------------------------

TORY HUGHES

[hidden email]

Tory Hughes website

Facebook|Tory Hughes Art

------------------------------------

Eric Charles

Re: Real-world genetic algorithm example... help!

In reply to this post by Ted Carmichael

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 <[hidden email]> 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 <tedsaid@...> 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 <nickthompson@...> 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 <a href="http://www.huffingtonpost.com/david-sloan-wilson/truth-and-reconciliation_b_266316.html" target="" onclick="window.open('http://www.huffingtonpost.com/david-sloan-wilson/truth-and-reconciliation_b_266316.html');return false;">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)

<a href="http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=auteursNom:%20%28MUIR%29" target="" onclick="window.open('http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=auteursNom:%20%28MUIR%29');return false;">MUIR W. M. ;

Revue / Journal Title

<a href="http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=listeTitreSerie:%20%28Poultry%20science%29" target="" onclick="window.open('http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=listeTitreSerie:%20%28Poultry%20science%29');return false;">Poultry science ISSN <a href="http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=identifiantsDoc:%20%280032-5791%29" target="" onclick="window.open('http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=identifiantsDoc:%20%280032-5791%29');return false;">0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 (nthompson@...)

<a href="http://home.earthlink.net/%7Enickthompson/naturaldesigns/" target="" onclick="window.open('http://home.earthlink.net/%7Enickthompson/naturaldesigns/');return false;">http://home.earthlink.net/~nickthompson/naturaldesigns/

<a href="http://www.cusf.org" target="" onclick="window.open('http://www.cusf.org');return false;">http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: Ted Carmichael

To: The Friday Morning Applied Complexity Coffee Group

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at <a href="http://www.friam.org" target="" onclick="window.open('http://www.friam.org');return false;">http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at <a href="http://www.friam.org" target="" onclick="window.open('http://www.friam.org');return false;">http://www.friam.org
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Eric Charles

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

Stephen Thompson

Projects: 5 Stages

In reply to this post by Victoria Hughes

Tory:

I am part way through Scott Page's book titled The Difference He discussed the the power of diversity to
produce better groups and outcomes. Are you aware of that reference? None, some, or much diversity
would influence the stages or at least successful completion of the stages would it not?

Steph T

Victoria Hughes wrote:

Fascinating. The original story and its appearance/discussion here.

I am writing a book on the five simple stages that projects move through, from idea to reality.

Part of the chapter, whose midst I am in, discusses "teams", inner and outer: the grouping of abilities and attributes required to get unstuck and get something done.

Sometimes the 'crate o' chickens' is outside of us, if we are working with a team. Sometimes our team is made from aspects of our own mind: the internal - complex- interconnection of knowledge, abilities, ideas, etc all squawking, laying, attacking, defending, at once, inside our brains.

Glad to know that even among the inheritors of the reptilian hind brain there can be cooperation for a larger good, even if that is for more chickens.

Tory

On Jul 9, 2010, at 4:53 PM, Ted Carmichael wrote:

Well, it wouldn't ... unless you were selecting for the lowest producing hens.

The GA selects for the groups of chickens that produce the most eggs, not the individuals. Some of those individuals may actually not produce many eggs, but they must somehow help the ones that do produce more eggs (in their group).

-t

On Fri, Jul 9, 2010 at 6:47 PM, Shawn Barr <[hidden email]> 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 <[hidden email]> 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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

-----------------------------------

TORY HUGHES
[hidden email]

Tory Hughes website

Facebook|Tory Hughes Art

------------------------------------
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Victoria Hughes

Re: Projects: 5 Stages

Yup, in most cases. Sometimes limitations force unusual, possibly more successful, resolutions. I don't know the book, will look into it. Thanks.

Tory

On Jul 9, 2010, at 5:51 PM, Stephen Thompson wrote:

Tory:

I am part way through Scott Page's book titled The Difference He discussed the the power of diversity to
produce better groups and outcomes. Are you aware of that reference? None, some, or much diversity
would influence the stages or at least successful completion of the stages would it not?

Steph T

Victoria Hughes wrote:
Fascinating. The original story and its appearance/discussion here.

I am writing a book on the five simple stages that projects move through, from idea to reality.

Part of the chapter, whose midst I am in, discusses "teams", inner and outer: the grouping of abilities and attributes required to get unstuck and get something done.

Sometimes the 'crate o' chickens' is outside of us, if we are working with a team. Sometimes our team is made from aspects of our own mind: the internal - complex- interconnection of knowledge, abilities, ideas, etc all squawking, laying, attacking, defending, at once, inside our brains.

Glad to know that even among the inheritors of the reptilian hind brain there can be cooperation for a larger good, even if that is for more chickens.

Tory

On Jul 9, 2010, at 4:53 PM, Ted Carmichael wrote:

Well, it wouldn't ... unless you were selecting for the lowest producing hens.

The GA selects for the groups of chickens that produce the most eggs, not the individuals. Some of those individuals may actually not produce many eggs, but they must somehow help the ones that do produce more eggs (in their group).

-t

On Fri, Jul 9, 2010 at 6:47 PM, Shawn Barr <[hidden email]> 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 <[hidden email]> 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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

-----------------------------------

TORY HUGHES
[hidden email]

Tory Hughes website

Facebook|Tory Hughes Art

------------------------------------
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

-----------------------------------

TORY HUGHES

[hidden email]

Tory Hughes website

Facebook|Tory Hughes Art

------------------------------------

QEF@aol.com

Re: Projects: 5 Stages

Tory --

How does this relate (if at all) to the simplistic group dynamics model I learned in business school (attributed to Bruce Tuckman)?

forming
storming
norming
performing

At a minimum, I'm missing a stage, and I'm sure there's much more to your analysis. Excuse my speculations.

- Claiborne Booker -

-----Original Message-----
From: Victoria Hughes <[hidden email]>
To: The Friday Morning Applied Complexity Coffee Group <[hidden email]>
Sent: Fri, Jul 9, 2010 8:14 pm
Subject: Re: [FRIAM] Projects: 5 Stages

Yup, in most cases. Sometimes limitations force unusual, possibly more successful, resolutions. I don't know the book, will look into it. Thanks.

Tory

On Jul 9, 2010, at 5:51 PM, Stephen Thompson wrote:

Tory:

I am part way through Scott Page's book titled The Difference He discussed the the power of diversity to
produce better groups and outcomes. Are you aware of that reference? None, some, or much diversity
would influence the stages or at least successful completion of the stages would it not?

Steph T

Victoria Hughes wrote:
Fascinating. The original story and its appearance/discussion here.

I am writing a book on the five simple stages that projects move through, from idea to reality.

Part of the chapter, whose midst I am in, discusses "teams", inner and outer: the grouping of abilities and attributes required to get unstuck and get something done.

Sometimes the 'crate o' chickens' is outside of us, if we are working with a team. Sometimes our team is made from aspects of our own mind: the internal - complex- interconnection of knowledge, abilities, ideas, etc all squawking, laying, attacking, defending, at once, inside our brains.

Glad to know that even among the inheritors of the reptilian hind brain there can be cooperation for a larger good, even if that is for more chickens.

Tory

On Jul 9, 2010, at 4:53 PM, Ted Carmichael wrote:

Well, it wouldn't ... unless you were selecting for the lowest producing hens.

The GA selects for the groups of chickens that produce the most eggs, not the individuals. Some of those individuals may actually not produce many eggs, but they must somehow help the ones that do produce more eggs (in their group).

-t

On Fri, Jul 9, 2010 at 6:47 PM, Shawn Barr <[hidden email]> 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 <[hidden email]> 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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

-----------------------------------

TORY HUGHES
[hidden email]

Tory Hughes website

Facebook|Tory Hughes Art

------------------------------------
============================================================


FRIAM Applied Complexity Group listserv


Meets Fridays 9a-11:30 at cafe at St. John's College


lectures, archives, unsubscribe, maps at http://www.friam.org
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

-----------------------------------

TORY HUGHES

[hidden email]

Tory Hughes website

Facebook|Tory Hughes Art

------------------------------------

============================================================


FRIAM Applied Complexity Group listserv


Meets Fridays 9a-11:30 at cafe at St. John's College


lectures, archives, unsubscribe, maps at http://www.friam.org

Russ Abbott

Re: Real-world genetic algorithm example... help!

In reply to this post by Eric Charles

It's a great story, but it's not a genetic algorithm as we normally think about it. It's really just breeding. For one thing, no computer was involved. The point of the whole thing is to establish the notion of group selection, which was forbidden in the biological world for a while. This experiment shows that it makes sense.

In what sense was it just breeding? Well, what was bred was coops rather than chickens. So the original population was 6 coops. The best one was selected and propagated. The best of those was selected, etc. Not at all what GA is about. There was no crossover or mutation between the population elements -- which are coops. Of course there is crossover among the chickens in the coop, but it wasn't chickens that were bred. The fitness function was a function applied to the coop.

So even though it is a very nice experiment and even though it makes a very strong case for group selection, it's probably not a good example for a chapter on genetic algorithms in a text book.

-- Russ

On Fri, Jul 9, 2010 at 4:25 PM, ERIC P. CHARLES <[hidden email]> wrote:

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 <[hidden email]> 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 <tedsaid@...> 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 <nickthompson@...> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 (nthompson@...)

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: Ted Carmichael

To: The Friday Morning Applied Complexity Coffee Group

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org
Eric Charles

Professional Student and
Assistant Professor of Psychology
Penn State University
Altoona, PA 16601
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Russ Abbott

Re: Real-world genetic algorithm example... help!

I should also have added that unlike GAs in which one is manipulating an explicit genome, there was no explicit genome in this experiment.

Russ

On Fri, Jul 9, 2010 at 6:18 PM, Russ Abbott <[hidden email]> wrote:

It's a great story, but it's not a genetic algorithm as we normally think about it. It's really just breeding. For one thing, no computer was involved. The point of the whole thing is to establish the notion of group selection, which was forbidden in the biological world for a while. This experiment shows that it makes sense.

In what sense was it just breeding? Well, what was bred was coops rather than chickens. So the original population was 6 coops. The best one was selected and propagated. The best of those was selected, etc. Not at all what GA is about. There was no crossover or mutation between the population elements -- which are coops. Of course there is crossover among the chickens in the coop, but it wasn't chickens that were bred. The fitness function was a function applied to the coop.

So even though it is a very nice experiment and even though it makes a very strong case for group selection, it's probably not a good example for a chapter on genetic algorithms in a text book.

-- Russ
On Fri, Jul 9, 2010 at 4:25 PM, ERIC P. CHARLES <[hidden email]> wrote:
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 <[hidden email]> 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 <tedsaid@...> 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 <nickthompson@...> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 (nthompson@...)

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: Ted Carmichael

To: The Friday Morning Applied Complexity Coffee Group

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org
Eric Charles

Professional Student and
Assistant Professor of Psychology
Penn State University
Altoona, PA 16601
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Robert J. Cordingley

Re: Real-world genetic algorithm example... help!

In reply to this post by Victoria Hughes

But it might only be for the larger good of the tribe and this might be what's behind our tribal (crate o' chickens) mentalities as a species? Even if tribes enrich our culture they do tend to go to war with each other. I wonder how it changes with scale: local (crate), regional (farm), national and transnational tribes.
Thanks
Robert C

On 7/9/10 5:20 PM, Victoria Hughes wrote:

Fascinating. The original story and its appearance/discussion here.

I am writing a book on the five simple stages that projects move through, from idea to reality.

Part of the chapter, whose midst I am in, discusses "teams", inner and outer: the grouping of abilities and attributes required to get unstuck and get something done.

Sometimes the 'crate o' chickens' is outside of us, if we are working with a team. Sometimes our team is made from aspects of our own mind: the internal - complex- interconnection of knowledge, abilities, ideas, etc all squawking, laying, attacking, defending, at once, inside our brains.

Glad to know that even among the inheritors of the reptilian hind brain there can be cooperation for a larger good, even if that is for more chickens.

Tory

On Jul 9, 2010, at 4:53 PM, Ted Carmichael wrote:

Well, it wouldn't ... unless you were selecting for the lowest producing hens.

The GA selects for the groups of chickens that produce the most eggs, not the individuals. Some of those individuals may actually not produce many eggs, but they must somehow help the ones that do produce more eggs (in their group).

-t

On Fri, Jul 9, 2010 at 6:47 PM, Shawn Barr <[hidden email]> 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 <[hidden email]> 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 <[hidden email]> 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)

MUIR W. M. ;

Revue / Journal Title

Poultry science ISSN 0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 ([hidden email])

http://home.earthlink.net/~nickthompson/naturaldesigns/

http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: [hidden email]

To: [hidden email]

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

-----------------------------------

TORY HUGHES
[hidden email]

Tory Hughes website

Facebook|Tory Hughes Art

------------------------------------
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Eric Charles

Re: Real-world genetic algorithm example... help!

In reply to this post by Eric Charles

Russ,
Completely agreed.
I'm not sure how one would connect the chicken stuff in a pretty way to standard computer genetic algorithms. I suppose one could relate them together to suggest the need for variation in "selection" methods when using GAs. That's Ted's part. I only claimed to know how the chicken part worked through (either artificial or natural) selection for something other than best individual production.

Eric

On Fri, Jul 9, 2010 09:18 PM, Russ Abbott <[hidden email]> wrote:

It's a great story, but it's not a genetic algorithm as we normally think about it. It's really just breeding. For one thing, no computer was involved. The point of the whole thing is to establish the notion of group selection, which was forbidden in the biological world for a while. This experiment shows that it makes sense.

In what sense was it just breeding? Well, what was bred was coops rather than chickens. So the original population was 6 coops. The best one was selected and propagated. The best of those was selected, etc. Not at all what GA is about. There was no crossover or mutation between the population elements -- which are coops. Of course there is crossover among the chickens in the coop, but it wasn't chickens that were bred. The fitness function was a function applied to the coop.

So even though it is a very nice experiment and even though it makes a very strong case for group selection, it's probably not a good example for a chapter on genetic algorithms in a text book.

-- Russ

On Fri, Jul 9, 2010 at 4:25 PM, ERIC P. CHARLES <epc2@...> wrote:

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 <sbarr2@...> 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 <tedsaid@...> 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 <nickthompson@...> 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 <a href="http://www.huffingtonpost.com/david-sloan-wilson/truth-and-reconciliation_b_266316.html" target="" onclick="window.open('http://www.huffingtonpost.com/david-sloan-wilson/truth-and-reconciliation_b_266316.html');return false;">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)

<a href="http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=auteursNom:%20%28MUIR%29" target="" onclick="window.open('http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=auteursNom:%20%28MUIR%29');return false;">MUIR W. M. ;

Revue / Journal Title

<a href="http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=listeTitreSerie:%20%28Poultry%20science%29" target="" onclick="window.open('http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=listeTitreSerie:%20%28Poultry%20science%29');return false;">Poultry science ISSN <a href="http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=identifiantsDoc:%20%280032-5791%29" target="" onclick="window.open('http://www.refdoc.fr/?traduire=en&FormRechercher=submit&FormRechercher_Txt_Recherche_name_attr=identifiantsDoc:%20%280032-5791%29');return false;">0032-5791 CODEN POSCAL

Source / Source

1996, vol. 75, n^o4, 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 (nthompson@...)

<a href="http://home.earthlink.net/%7Enickthompson/naturaldesigns/" target="" onclick="window.open('http://home.earthlink.net/%7Enickthompson/naturaldesigns/');return false;">http://home.earthlink.net/~nickthompson/naturaldesigns/

<a href="http://www.cusf.org" target="" onclick="window.open('http://www.cusf.org');return false;">http://www.cusf.org [City University of Santa Fe]

----- Original Message -----

From: Ted Carmichael

To: The Friday Morning Applied Complexity Coffee Group

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
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at <a href="http://www.friam.org" target="" onclick="window.open('http://www.friam.org');return false;">http://www.friam.org

============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at <a href="http://www.friam.org" target="" onclick="window.open('http://www.friam.org');return false;">http://www.friam.org

Eric Charles

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

============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at <a href="http://www.friam.org" target="" onclick="window.open('http://www.friam.org');return false;">http://www.friam.org
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org

Eric Charles

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