(old)Puppy Linux Discussion Forum

Hello
Does genetic algorithm always converge towards and optimal solution? Are there any papers or articles that have proved this mathematically or empirically?
The process or crossover preserving genes that are closer to optimal sounds somewhat logical, but couldn't an improper mutation completely diverge the solution away from optimal?

Thanks in advance.

By 'genetic algorithm' do you mean random mutation followed by natural selection? If so, what is optimal?

i don't personally believe that mathematics is particularly useful in the life or social sciences, apart from trends and probabilities

i also don't think trends or probabilities are particularly useful

who cares if smoking is likely to cause cancer or heart disease if i get cancer or heart disease and i don't smoke?

and i see the 98-year-old on tv who smokes a pack a day?

bugman wrote:who cares if smoking is likely to cause cancer or heart disease if i get cancer or heart disease and i don't smoke?

The people whose tax dollars are used to treat those cancer patients.

rcrsn51 wrote:

bugman wrote:who cares if smoking is likely to cause cancer or heart disease if i get cancer or heart disease and i don't smoke?

The people whose tax dollars are used to treat those cancer patients.

i live in the u$, no worries, eh?

but now you're discussing economics rather than biology

bugman wrote:... now you're discussing economics rather than biology

No, he's discussing whether the government has a legitimate interest in regulating smoking. Since the government winds up paying for the care of many people who have illnesses strongly associated with smoking, the answer is clearly yes. (Unless you like your tax dollars going to subsidize tobacco companies, which don't pay for the damage they cause.)

Just as the government has a good reason for telling motorcycle riders they have to wear protective headgear. Guess who winds up paying for the care of many of the people whose brains were addled when they wrecked a motorcycle while not wearing a helmet?

And I might extend the argument to a nation that is contemplating building nuclear power plants. When the damned things blow up, the contamination is not confined within the borders of the plant, or even the borders of the nation responsible.

Flash wrote:

bugman wrote:... now you're discussing economics rather than biology

No, he's discussing whether the government has a legitimate interest in regulating smoking. Since the government winds up paying for the care of many people who have illnesses strongly associated with smoking, the answer is clearly yes. (Unless you like your tax dollars going to subsidize tobacco companies, which don't pay for the damage they cause.)

the government pays for the care of people? in the u$?

really? i'm quite ill and had no idea . . .

Are you forgetting about state governments?

Guys don't get me wrong now. I easily derail any thread even my own.

What about the code that learn from it's own mistakes? Such a neat idea.

They have shown Robots that learn to walk by endlessly falling and falling for weeks or months on end and not giving up and in the end they run like a Sprinter and will one day beat any athlete on the Olympic Games

Go back derailing I don't mind. I am not the Mod either. *Friendly Smile*

But the thread is really intersting. Could one set up a kind of software that learned to be a very good assembler Puppy that was optimised for every hardware it came upon? Some 3MB big and could do what Puppy do now

I go to sleep now and in my dreams I teach such a program to make a lean and mean small puppy with assembler code. Fast and strong.

Hello friends
This thread is going completely off topic
I need to give a report on implementing network intrusion detection system based on genetic algorithms, so that the system can learn from a database of network intrusion patterns, whether a given activity at a given time is a possible intrusion or not
The work is still in it's initial phase and I am studying the basics of genetic algorithms for this. It was stated in a book (which only had a sort of introductory chapter on Genetic algorithms) that due to the genetic operators used in the algorithm, the optimal solution is always preserved through the generations as the possible solution evolves. The book didn't mention any references for it's proof. I was hoping I would get an answer to this.
Don't get me wrong, I have read all the replys to my question and it's a very interesting discussion but I need to write my report as well

Flash wrote:Are you forgetting about state governments?

i suppose that depends on the state you live in, here we're derailing, but not as quickly as others

i would amend my previous statement [whatever it was] to boot

mathematics does not belong in economics either

currently reading about john nash, the nash equilibrium, and its contribution to the current mess

mahaju , I guess you ahve to find a forum for Genetic programming. Where they do such things daily and them would know how you could proceed.

This Puppy forum and very few are doing genetic programming at all.
Maybe no a single person of all users. I doubt that there is one doing it.

bugman wrote:...mathematics does not belong in economics either

I would agree.

...currently reading about john nash, the nash equilibrium, and its contribution to the current mess

Do you have a link to what you're reading about the Nash equilibrium?

Nooby, if Mahaju had replied immediately to my first post, perhaps the thread would have stayed on track. What a difference a day makes, eh?

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?

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!

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

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.

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.

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)