704 thoughts on “Holding tank for general chatter about GAs”

  1. Geoxus: The point of scissors is to cut easily. That says nothing about what scissors are. Your “GAs” have “nothing to do with genetics” and the algorithmic aspect of them hasn’t become apparent so far, so not even the word is helping us to understand what they are.

    But I give up. Cling on to your buzzword.

    I said GAs don’t have to deal with genetics and I provided examples to support that claim.

    The point of the internal GA is to make sure the cell/ organism produces/ has the proteins required to survive.

  3. Joe G: I told you already but obvioulsy you HAVE to be an asshole. I go by the standard and accepted definitions of GPs and GAs and EAs

    Oh, no, you don’t. Here you wrote:

    Those GAs demonstrate that GAs find solutions to problems. And the computer would be the organism.

    According to the standard definition of a GA, the computer (well, the algorithm) is not an organism. It creates a population of organisms and an environment for them. Thus the computer plays the role of nature, rather than of an organism.

    Here is what Wikipedia says:

    In a genetic algorithm, a population of strings (called chromosomes or the genotype of the genome), which encode candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem, evolves toward better solutions.

    It is thus clear that you do not use the standard definition of a GA. So you need to present your own definition.

  4. olegt: Oh, no, you don’t. Here you wrote:

    According to the standard definition of a GA, the computer (well, the algorithm) is not an organism. It creates a population of organisms and an environment for them. Thus the computer plays the role of nature, rather than of an organism.

    Here is what Wikipedia says:

    It is thus clear that you do not use the standard definition of a GA. So you need to present your own definition.

    You are dense- I was talking about the “Evolving Inventions” scenario when I said the computer would be the organism.

    And again not all GAs have to be like that- my examples prove that.

    What is wrong with you?

  5. It creates a population of organisms and an environment for them.

    Not so for all GAs, as my examples prove.

    Thanks for proving that you are ignorant wrt GAs

  6. Oleg-

    Genetic algorithms are search heuristics designed to generate useful solutions (to existing problems).

  7. Joe,
    In the GA you claim exists inside the cell, what is the analogue to “population”?

    http://en.wikipedia.org/wiki/Genetic_algorithm

    In a genetic algorithm, a population of strings (called chromosomes or the genotype of the genome), which encode candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem, evolves toward better solutions.

    What encodes candidate solutions in your GA? What actually evolves in your GA?

  8. Joe G:
    Oleg-

    Genetic algorithms are search heuristics designed to generate useful solutions (to existing problems).

    Do you believe that the result (solution) is “smuggled in” somehow by the designer of the GA?

  10. Joe G: Genetic algorithms are search heuristics designed to generate useful solutions (to existing problems).

    Good start. (We all can copy and paste from Wikipedia.)

    Go on.

  11. OM: Do you believe that the result (solution) is “smuggled in” somehow by the designer of the GA?

    No- the GA solves the problems. And the GA is linked to the designer.

  12. Joe G: Elizabeth- obviously you are not following along- you don’t need to know the mutations, just what you need- what the protein needed is.

    Joe, if the GA already knows what the protein needed is (otherwise how can it be used as a target) why does the GA not just direct the cell to make that protein rather then attempt to discover it as a solution, potentially never finding it at all?

  13. Joe G: And the GA is linked to the designer.

    So how are the GAs in cells linked to “the designer” by which I mean the “Intelligent Designer” of ID?

  14. OM: Joe, if the GA already knows what the protein needed is (otherwise how can it be used as a target) why does the GA not just direct the cell to make that protein rather then attempt to discover it as a solution, potentially never finding it at all?

    It just knows what protein function it needs. Then it has to put together the proper DNA sequence to get the proper mRNA sequence.

  15. OM: So how are the GAs in cells linked to “the designer” by which I mean the “Intelligent Designer” of ID?

    The same way computer programs are linked to the programmer, duh.

  16. Joe,
    Do the solutions that the GA finds (how to make a protein etc) increase the overall specified complexity a.k.a CSI in the organism?

  17. Joe G: The same way computer programs are linked to the programmer, duh.

    And so when was this GA created? At the origin of life?

  18. Joe G: Did any of the examples in “Evolving Inventions” have a population? No.

    Of course they did. Here is an excerpt from p. 55:

    Most of the initial population of rudimentary circuits generated randomly in this way will behave nothing like a low-pass filter.

  19. olegt: Of course they did. Here is an excerpt from p. 55:

    Then the population inside the cell would be the DNA- as that is what creates the sequence for the new proteins

  20. Joe G: It just knows what protein function it needs.

    How? “It just knows” is somewhat imprecise.

    Then it has to put together the proper DNA sequence to get the proper mRNA sequence.

    But how? There does not seem to me to be much actual room in a cell left over, never mind what you’d need to create a large population you can then test against your target sequence.

    My understanding, from reading ID, is that functional proteins are isolated in possibility space and there are no pathways between these islands of functionality.

    How, then, is your GA able to find new proteins, all inside a single cell, all without it’s tools being noticed at all by any biologist?

    Then it has to put together the proper DNA sequence to get the proper mRNA sequence.

    Yes, exactly! But *how* it does that is actually the interesting part – how does it do it?

  22. Joe G: Then the population inside the cell would be the DNA- as that is what creates the sequence for the new proteins

    How many individual entities are in this population? 10’s Trillions? Somewhere in the middle?

  23. OM: How? “It just knows” is somewhat imprecise.

    But how? There does not seem to me to be much actual room in a cell left over, never mind what you’d need to create a large population you can then test against your target sequence.

    My understanding, from reading ID, is that functional proteins are isolated in possibility space and there are no pathways between these islands of functionality.

    How, then, is your GA able to find new proteins, all inside a single cell, all without it’s tools being noticed at all by any biologist?

    Yes, exactly! But *how* it does that is actually the interesting part – how does it do it?

    LoL- as if you have read anything on ID that was written by IDists.

    As for “how”- we have been asking that of evotards for over 150 years and we get nothing.

  24. OM: How many individual entities are in this population? 10’s Trillions? Somewhere in the middle?

    Whatever the genome is. duh

  25. So you go from:

    Did any of the examples in “Evolving Inventions” have a population? No.

    to:

    Joe G: Then the population inside the cell would be the DNA

    without blinking?

  26. Joe G: Whatever the genome is.

    How does your GA delineate each individual in this “population”?
    If you are mutating the genome, how do you put it back to it’s original state when the GA has completed it’s run?

  28. My understanding, from reading ID, is that functional proteins are isolated in possibility space and there are no pathways between these islands of functionality.

    Do you believe that or not Joe? It’s directly relevant to your claim.

  30. OM: How does your GA delineate each individual in this “population”?
    If you are mutating the genome, how do you put it back to it’s original state when the GA has completed it’s run?

    Evotards think that I need all the answers when it is obvious that their position doesn’t have any answers.

  31. OM:
    Joe,
    When your GA finds a new protein, does CSI increase overall?

    It all depends on the starting information.

  32. Joe G: It all depends on the starting information.

    Can you give an example?

    You yourself said that your GA finds new proteins. My understanding is that proteins have measurable CSI, according to ID. A new protein therefore *must* add to the sum total of CSI that was present before it was there?

    How could it not?

  33. Joe G: Evotards think that I need all the answers

    No, Joe, it’s rather that they way you talk you give the impression that you have all the answers.

    If the population of your GA is the genome, when your GA starts chopping it up to use as the population in your GA how can the cell continue to function?

  34. Joe G: In this case the word “population” is ambiguous.

    Really? What did you understand by “population” when you said the example did not have one then?

  35. Joe G: It all depends on the starting information.

    Could you expand on what you mean by “starting information”?

    It seems to me that if this GA finds 1 or 100 new proteins that were not there before regardless of any “starting information” considerations, the CSI (as ID defines it) has increased.

    The only way you can claim it did not is if the protein that is found is already known and stored by the GA. But if that’s the case (and you indicate that it is as you say the GA sets a specific protein as the target) then why not just use the target as the new protein rather then going through the charade of “looking” for it and all the energy that would entail?

    So, Joe, you’ve said too much this time and a case can be built using only your arguments that negate those same arguments.

  36. If you find something after looking for it that would imply that you did not have it in the first place.

    Yet if CSI exists it *must* increase when something containing CSI is added, no? that’s only logical? And if you already have it, why look for it?

  37. Joe claims that his GA can design new proteins.

    Dembski says differently.

    Why Natural Selection Can’t Design Anything

    http://www.leaderu.com/offices/dembski/docs/NATSELEC.pdf

    Joe says that his GA is generating new information and genuinely solving the problem, not using information that has been smuggled in.
    Dembsky says differently

    But invariably we find that when specified complexity seems to be generated for free, it has in fact been front-loaded, smuggled in, or hidden from view.

    Seems you are at odds with Dembski in many ways Joe. Perhaps you should write your own book!

  38. OM:
    Joe,
    In the GA you claim exists inside the cell, what is the analogue to “population”?

    http://en.wikipedia.org/wiki/Genetic_algorithm

    What encodes candidate solutions in your GA? What actually evolves in your GA?

    OK now I see what happened- my mind was totally blown by the total ignorance of OM’s questions because the answer is right there in his C&P job-

    As I said with my scenario a GA would be directing the duplications, insertions, deletions, recombinations, as well as controlling exon shuffling and recombinations.

    This is in line with Dr Spetner’s “non-random evolutionary hypothesis”

  39. Joe G: Information hasn’t been “smuggled” in- it was put there intentionally.

    What information would that be?

  40. Joe G: As I said with my scenario a GA would be directing the duplications, insertions, deletions, recombinations, as well as controlling exon shuffling and recombinations.

    And what evidence do you have for that?

  41. Joe G: OK now I see what happened- my mind was totally blown by the total ignorance of OM’s questions because the answer is right there in his C&P job-

    No Joe, in *your* example what represents the population of candidate solutions?

  44. Joe G: My scenario means new proteins came about by design- ie as per the GA.

    But your GA is not designing them directly is it? It’s evolving a solution.

    Therefore evolution can design and you’ve just disproved the entirety of ID.

  45. Joe G: What do you know about evidence?

    It’s what you provide when you make a claim to support it. If you don’t then the claim is unsupported.

    So I ask again, what actual evidence do you have that your GA is directing duplications, insertions, deletions, recombinations, as well as controlling exon shuffling and recombinations as you claim?

  46. OM: No Joe, in *your* example what represents the population of candidate solutions?

    Different DNA sequences – it searches them trying to get one of the right solutions. Its start with MET

  47. Joe GWhat do you know about information?.

    It’s what you are claiming was put there intentionally. I’m asking you how you know that.

  48. Joe G: Different DNA sequences – it searches them trying to get one of the right solutions. Its start with MET

    So your GA is in fact a index card reader, looking up predefined solutions that are in a library of such solutions?

  49. OM: It’s what you provide when you make a claim to support it. If you don’t then the claim is unsupported.

    So I ask again, what actual evidence do you have that your GA is directingduplications, insertions, deletions, recombinations, as well as controlling exon shuffling and recombinations as you claim?

    So you don’t know anything about evidence.

    Got it…

    OR perhaps you could present some from your position so we can find out?

  50. Joe G: My scenario is intelligent design evolution.

    Yes. And it’s using something that is not a GA, by your own admission.

    You don’t need a GA if you already have a predefined set of solutions to choose from.

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