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Natural Selection = Vaporware


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#1 scaramouche

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Posted 07 August 2007 - 03:38 PM

It is common knowledge that Charles Darwin did not originate the idea of evolution. The Great Chain of LIfe had been around over 2000 years -- ever since the Greek philosophers. Darwin's unique contribution was the theory of Natural Selection.
Richard Dawkins himself said that natural selection is blind and has no intelligence. I add the adjectives deaf and dumb. It knows not what is advantageous or what is not. It does not know the future or the present or the past.
I think some people have a bumper sticker that explains natural selection very well - "%^$# happens". Natural selection is simply DEATH. If something lives, it has an advantage over some that is dead. Survival of the fittest is not exactly accurate. Survival of the luckiest (or the most blessed) is closer to the truth.

What are the properties of natural selection? Is is matter? Is it energy? Is it information(another basic entity of the universe which is not recognized as it should be)? Is it magic? Is it animal, vegetable, or minieral? Is it bigger than a bread box?

#2 gilbo12345

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Posted 15 June 2011 - 09:20 PM

Just bumping this thread because I'd like to hear a response from an evolutionist.

I'd also like to add how is "natural selection" measured and what is the mathematical model concerning its actions?

#3 AFJ

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Posted 19 June 2011 - 05:51 AM

It is common knowledge that Charles Darwin did not originate the idea of evolution. The Great Chain of LIfe had been around over 2000 years -- ever since the Greek philosophers. Darwin's unique contribution was the theory of Natural Selection.
Richard Dawkins himself said that natural selection is blind and has no intelligence. I add the adjectives deaf and dumb. It knows not what is advantageous or what is not. It does not know the future or the present or the past.
I think some people have a bumper sticker that explains natural selection very well - "%^$# happens". Natural selection is simply DEATH. If something lives, it has an advantage over some that is dead. Survival of the fittest is not exactly accurate. Survival of the luckiest (or the most blessed) is closer to the truth.

What are the properties of natural selection? Is is matter? Is it energy? Is it information(another basic entity of the universe which is not recognized as it should be)? Is it magic? Is it animal, vegetable, or minieral? Is it bigger than a bread box?

I hear what you're saying. I think they have classified survival of the luckiest under genetic drift though.

I think selection is real, but there is not enough attention paid to S@xual selection. I see male dominance in S@xual selection as what passes genes on more than whether a weakling dies.

But genetic drift is overrated also. If I kill 10 cockroaches, and the least fit of the nest lives, there's 10 million other nests with the same genes that will get passed. So how is that going to cause genes to 'drift?'

#4 adsummum

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Posted 19 June 2011 - 11:37 PM

what is the mathematical model concerning its actions?


Genetic algorithms? While they're not really used as models, they find more practical use in computational mathematics as a search heuristic for optimization problems. For the most basic GAs you select a population from the total set of possible states of a given system, and then evaluate the 'fitness' of any member by how well they perform by set of criteria. Then you arbitrarily select groups within that population and identify the 'most fit' individuals of each and make them 'reproduce'. The groups don't need to be disjoint; this permits exceptionally fit members to reproduce multiple times. Reproduction is performed by crossing over 'genetic material' from parents and introducing random mutations. There are many ways to go about doing this - for instance, if you are dealing with integers, you could represent each number in binary and create two children by swapping the last 10 digits of each number; mutations would just be a random chance that a 1 would appear as a 0 in a child and vice versa. Then you restart the algorithm with the second generation and so on and so forth.

http://www.stellaral...l_creatures.php
This is a program called Virtual Creature Evolution (by Lee Graham) which uses GAs to create 'creatures'. It generates a population of animals made of cuboids affixed at random points, and then uses GAs to optimize some property - distance traveled, height jumped etc. This primordial population is functionally useless. Most members do little more than twitch. It takes a loooooong time to do anything, but after a couple of hundred generations you find that the program begins to create creatures that move fluidly, and rather ingeniously ().

#5 AFJ

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Posted 20 June 2011 - 04:03 PM

Genetic algorithms? While they're not really used as models, they find more practical use in computational mathematics as a search heuristic for optimization problems. For the most basic GAs you select a population from the total set of possible states of a given system, and then evaluate the 'fitness' of any member by how well they perform by set of criteria. Then you arbitrarily select groups within that population and identify the 'most fit' individuals of each and make them 'reproduce'. The groups don't need to be disjoint; this permits exceptionally fit members to reproduce multiple times. Reproduction is performed by crossing over 'genetic material' from parents and introducing random mutations. There are many ways to go about doing this - for instance, if you are dealing with integers, you could represent each number in binary and create two children by swapping the last 10 digits of each number; mutations would just be a random chance that a 1 would appear as a 0 in a child and vice versa. Then you restart the algorithm with the second generation and so on and so forth.

http://www.stellaral...l_creatures.php
This is a program called Virtual Creature Evolution (by Lee Graham) which uses GAs to create 'creatures'. It generates a population of animals made of cuboids affixed at random points, and then uses GAs to optimize some property - distance traveled, height jumped etc. This primordial population is functionally useless. Most members do little more than twitch. It takes a loooooong time to do anything, but after a couple of hundred generations you find that the program begins to create creatures that move fluidly, and rather ingeniously ().

Isn't this working under the assumption that these mutations will cause fixed traits? But what they found in the E. coli bacteria was problem with revertants--the inability to fix new traits permanently.

#6 Fred Williams

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Posted 20 June 2011 - 04:23 PM

Genetic algorithms? While they're not really used as models, they find more practical use in computational mathematics as a search heuristic for optimization problems. For the most basic GAs you select a population from the total set of possible states of a given system, and then evaluate the 'fitness' of any member by how well they perform by set of criteria. Then you arbitrarily select groups within that population and identify the 'most fit' individuals of each and make them 'reproduce'. The groups don't need to be disjoint; this permits exceptionally fit members to reproduce multiple times. Reproduction is performed by crossing over 'genetic material' from parents and introducing random mutations. There are many ways to go about doing this - for instance, if you are dealing with integers, you could represent each number in binary and create two children by swapping the last 10 digits of each number; mutations would just be a random chance that a 1 would appear as a 0 in a child and vice versa. Then you restart the algorithm with the second generation and so on and so forth.

http://www.stellaral...l_creatures.php
This is a program called Virtual Creature Evolution (by Lee Graham) which uses GAs to create 'creatures'. It generates a population of animals made of cuboids affixed at random points, and then uses GAs to optimize some property - distance traveled, height jumped etc. This primordial population is functionally useless. Most members do little more than twitch. It takes a loooooong time to do anything, but after a couple of hundred generations you find that the program begins to create creatures that move fluidly, and rather ingeniously (https://www.youtube....h?v=l-qOBi2tAnI).


GAs are essentially glorified tral&error experiments that have nothing to do with evolution, they can't generate new information without information to cull it. Plus, GAs use truncation selection, something that has zero, zippo, evidence that it occurs in nature.

Fred

#7 gilbo12345

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Posted 21 June 2011 - 02:48 AM

Genetic algorithms? While they're not really used as models, they find more practical use in computational mathematics as a search heuristic for optimization problems. For the most basic GAs you select a population from the total set of possible states of a given system, and then evaluate the 'fitness' of any member by how well they perform by set of criteria. Then you arbitrarily select groups within that population and identify the 'most fit' individuals of each and make them 'reproduce'. The groups don't need to be disjoint; this permits exceptionally fit members to reproduce multiple times. Reproduction is performed by crossing over 'genetic material' from parents and introducing random mutations. There are many ways to go about doing this - for instance, if you are dealing with integers, you could represent each number in binary and create two children by swapping the last 10 digits of each number; mutations would just be a random chance that a 1 would appear as a 0 in a child and vice versa. Then you restart the algorithm with the second generation and so on and so forth.

http://www.stellaral...l_creatures.php
This is a program called Virtual Creature Evolution (by Lee Graham) which uses GAs to create 'creatures'. It generates a population of animals made of cuboids affixed at random points, and then uses GAs to optimize some property - distance traveled, height jumped etc. This primordial population is functionally useless. Most members do little more than twitch. It takes a loooooong time to do anything, but after a couple of hundred generations you find that the program begins to create creatures that move fluidly, and rather ingeniously ().


Here is one such trial of these creatures



Please note

1) That the only selection factor is being able to jump the highest.. Life is MUCH more complicated than having just one variable to consider. Where Life is an amalgam of many thousands of variables each of which would reduce the selection capability of each other since they'd interfere with what traits the others were selecting for.

2) halfway through the parameters were changed which lead to a massive increase in the population fitness, (this is what was claimed in the video)

3) These points shows that the parameters and selection guild lines are designed hence by definition they defy the evolution model due to evolution showing that things don't come from a design, yet a designed approach is required to demonstrate this....

4) As Fred said, GA's do not simulate real life.

#8 Tirian

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Posted 23 June 2011 - 06:53 AM

Genetic algorithms? While they're not really used as models, they find more practical use in computational mathematics as a search heuristic for optimization problems. For the most basic GAs you select a population from the total set of possible states of a given system, and then evaluate the 'fitness' of any member by how well they perform by set of criteria. Then you arbitrarily select groups within that population and identify the 'most fit' individuals of each and make them 'reproduce'. The groups don't need to be disjoint; this permits exceptionally fit members to reproduce multiple times. Reproduction is performed by crossing over 'genetic material' from parents and introducing random mutations. There are many ways to go about doing this - for instance, if you are dealing with integers, you could represent each number in binary and create two children by swapping the last 10 digits of each number; mutations would just be a random chance that a 1 would appear as a 0 in a child and vice versa. Then you restart the algorithm with the second generation and so on and so forth.


The genetic algorithm is an efficient way of doing trial and error for certain problems within a well defined solution space. Like selecting the shortest route for a travelling salesman. But why do you think genetic algorithms have anything to do with natural selection? There is nothing natural about how a genetic programs calculates the best fitness for its members. That calculation is solution specific, i.e. depending on what kind of optimization problem you would like to solve you have to write different functions to calculate the fitness.

As I mentioned in another thread there is another problem when comparing genetic algorithms and the proposed darwinian mechanism. A genetic program has its instructions of what to do separated from where processed data is stored. That means that the genetic program can not evolve since it's instructions never change. The genetic program will keep producing whatever it was designed to produce.

By the way, do anybody know what Fred meant by truncation selection?




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