Genetic algorithm basin question

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bugman

#16 Post by bugman »

Flash wrote:[
Do you have a link to what you're reading about the Nash equilibrium?
no, it's very loose and undisciplined reading, still getting over the flu

that fucking a beautiful mind book followed up by wiki pages on nobel economists and other internets dreck

still can't decide if i want to learn more and really depress myself or not

edit: i expect some of my antipathy came from dredged-up memories of my ex-brother-in-law, this guy:

http://home.earthlink.net/~hipbone/

it took me a long time to figure out a lot of game theory [and the game he invented] was really crap, it wasn't just me being thick

and it's crap that's killing people, yippee!

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mahaju
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#17 Post by mahaju »

nooby wrote:He had too high expectations based on the Term Programming over the part of teh forum. He thought us experts on programming on the University level like Teachers at a Doctorate level?
It's not that
I just find the people in this forum more helpful
Other forums are mostly full of trolls
I am just hoping that if somebody has any idea about this thing he/she will be able to help

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Moose On The Loose
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#18 Post by Moose On The Loose »

mahaju wrote:
nooby wrote:He had too high expectations based on the Term Programming over the part of teh forum. He thought us experts on programming on the University level like Teachers at a Doctorate level?
It's not that
I just find the people in this forum more helpful
Other forums are mostly full of trolls
I am just hoping that if somebody has any idea about this thing he/she will be able to help
As I see it, there are two main problems with any system that attempts to optimize something.

(1) How you define "better" can be tricky. A classic example of a very bad definition is the case of a city dumping its sewage into the river. The sewage is taken away and is no longer a problem for the city so from one point of view it is a very goo answer to what to do with sewage. If you are in the city down stream you would disagree.

(2) Even with a good definition of "better" you can fall into a "better" but not "best" dip in the curve. If the curve happens to look like a hill with a well at the peak. Sliding down hill doesn't get you to the best result. Unless your random mutation happens to hit the well exactly, you won't ever get there.

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Dougal
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#19 Post by Dougal »

bugman wrote:mathematics does not belong in economics either
Mathematicians don't have a particularly high opinion of economists...

A friend at uni went to do a PhD in game theory (under the supervision of a Nobel winner).
The reason he chose game theory: because it's easy... (I think of it this way: it's a new discipline, so they're doing the basic, easy parts now.)

He's now doing his post-doc in Cambridge (or is it Oxford?).
When it was heard he was accepted, he'd meet old professors in the hall and they'd say:
"I heard you're going to do a post-doc in Cambridge"
He'd reply:
"Yes, in the economics department"
"Oh", they'd say and walk on, having lost all interest.
What's the ugliest part of your body?
Some say your nose
Some say your toes
But I think it's your mind

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mahaju
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#20 Post by mahaju »

As I see it, there are two main problems with any system that attempts to optimize something.

(1) How you define "better" can be tricky. A classic example of a very bad definition is the case of a city dumping its sewage into the river. The sewage is taken away and is no longer a problem for the city so from one point of view it is a very goo answer to what to do with sewage. If you are in the city down stream you would disagree.

(2) Even with a good definition of "better" you can fall into a "better" but not "best" dip in the curve. If the curve happens to look like a hill with a well at the peak. Sliding down hill doesn't get you to the best result. Unless your random mutation happens to hit the well exactly, you won't ever get there.
Genetic Algorithm doesn't guarantee to give the best answer
That is the reason it needs a large solution space and a lot of training time to converge towards the most optimal solution (may or may not be the best answer) but I have read that because of the way genetic algorithms treat it's parameters, the algorithm usually converges to the best solution in a large pool of possible solutions.
I need a reference where this has been proved (mathematically or experimentally or in any other way)

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