Evo-Info review: Do not buy the book until…

Introduction to Evolutionary Informatics, by Robert J. Marks II, the “Charles Darwin of Intelligent Design”; William A. Dembski, the “Isaac Newton of Information Theory”; and Winston Ewert, the “Charles Ingram of Active Information.” World Scientific, 332 pages.
Classification: Engineering mathematics. Engineering analysis. (TA347)
Subjects: Evolutionary computation. Information technology–Mathematics.

… the authors establish that their mathematical analysis of search applies to models of evolution.

I have all sorts of fancy stuff to say about the new book by Marks, Dembski, and Ewert. But I wonder whether I should say anything fancy at all. There is a ginormous flaw in evolutionary informatics, quite easy to see when it’s pointed out to you. The authors develop mathematical analysis of apples, and then apply it to oranges. You need not know what apples and oranges are to see that the authors have got some explaining to do. When applying the analysis to an orange, they must identify their assumptions about apples, and show that the assumptions hold also for the orange. Otherwise the results are meaningless.

The authors have proved that there is “conservation of information” in search for a solution to a problem. I have simplified, generalized, and trivialized their results. I have also explained that their measure of “information” is actually a measure of performance. But I see now that the technical points really do not matter. What matters is that the authors have never identified, let alone justified, the assumptions of the math in their studies of evolutionary models.a They have measured “information” in models, and made a big deal of it because “information” is conserved in search for a solution to a problem. What does search for a solution to a problem have to do with modeling of evolution? Search me. In the absence of a demonstration that their “conservation of information” math applies to a model of evolution, their measurement of “information” means nothing. It especially does not mean that the evolutionary process in the model is intelligently designed by the modeler.1

I was going to post an explanation of why the analysis of search does not apply to modeling of evolution. But I realized that it would give the impression that the burden is on me to show that the authors have misapplied the analysis.2 As soon as I raise objections, the “Charles Ingram of active information” will try to turn the issue into what I have said. The issue is what he and his coauthors have never bothered to say, from 2009 to the present. As I indicated above, they must start by stating the assumptions of the math. Then they must establish that the assumptions hold for a particular model that they address. Every one of you recognizes this as a correct description of how mathematical analysis works. I suspect that the authors recognize that they cannot deliver. In the book, they work hard at fostering the misconception that an evolutionary model is essentially the same as an evolutionary search. As I explained in a sidebar to the Evo-Info series, the two are definitely not the same. Most readers will swallow the false conflation, however, and consequently will be incapable of conceiving that analysis of an evolutionary model as search needs justification.

The premise of evolutionary informatics is that evolution requires information. Until the authors demonstrate that the “conservation of information” results for search apply to models of evolution, Introduction to Evolutionary Informatics will be worthless.


1 Joe Felsenstein came up with a striking demonstration that design is not required for “information.” In his GUC Bug model (presented in a post coauthored by me), genotypes are randomly associated with fitnesses. There obviously is no design in the fitness landscape, and yet we measured a substantial quantity of “information” in the model. The “Charles Ingram of active information” twice feigned a response, first ignoring our model entirely, and then silently changing both our model and his measure of active information.

2 Actually, I have already explained why the “conservation of information” math does not apply to models of evolution, including Joe’s GUC Bug. I recently wrote a much shorter and much sweeter explanation, to be posted in my own sweet time.

a ETA: Marks et al. measure the “information” of models developed by others. Basically, they claim to show that evolutionary processes succeed in solving problems only because the modelers supply the processes with information. In Chapter 1, freely available online, they write, “Our work was initially motivated by attempts of others to describe Darwinian evolution by computer simulation or mathematical models. The authors of these papers purport that their work relates to biological evolution. We show repeatedly that the proposed models all require inclusion of significant knowledge about the problem being solved. If a goal of a model is specified in advance, that’s not Darwinian evolution: it’s intelligent design. So ironically, these models of evolution purported to demonstrate Darwinian evolution necessitate an intelligent designer. The programmer’s contribution to success, dubbed active information, is measured in bits.” If you wonder Success at what? then you are on the right track.

588 thoughts on “Evo-Info review: Do not buy the book until…

  1. Mung,

    Anyone but Rumraket and Allan Miller think they pulled the NAND gate out of a hat?

    That’s what I think? Cheers! What’s my position on the relative merits of clematis and honeysuckle? I need telling.

  2. Rumraket: I’m intrigued by this idea that NAND and boolean functions are not real-world concepts but just obfuscations.

    In the world of Avida, inputting numbers, calculating functions of them, and outputting the results is metabolism. If you want to explain that, knock yourself out. I’ve have about all the intrigue I can handle for now.

  3. phoodoo: So you are paraphrasing a paper, but you have no idea what it means? I have to ask someone else.

    Is that what you got from it? lol

  4. phoodoo: So you are paraphrasing a paper, but you have no idea what it means? I have to ask someone else.

    Well, whoever makes you feel that you understand surely will have told you right.

  5. Rumraket: I’m intrigued by this idea that NAND and boolean functions are not real-world concepts but just obfuscations.

    As long as the obfuscation is a boolean function it can be implemented by using a combination of NAND gates.

  6. Mung: As long as the obfuscation is a boolean function it can be implemented by using a combination of NAND gates.

    Too bad Avidians aren’t combinational circuits. (I’d love to see you subject the book to the kind of scrutiny you do comments here.)

  7. Tom English: Too bad Avidians aren’t combinational circuits. (I’d love to see you subject the book to the kind of scrutiny you do comments here.)

    It’s a gift. 🙂

  8. Rumraket: This will make sense of the Lenski paper too. When they say that they are explaining the origin of “complexity”, they’re not claiming that there is some universal cut-off where things become “complex” and they were not before. All they mean is that the system in question comes to have a greater number of interacting parts that come together to work, than it had in the beginning.

    Then they have not explained “the origin of complexity at all.” They are bullshit artists, and you fell for it.

    Complex things have their origin in simpler things. Well freaking duh. Really?

    And simpler things have their origin in more complex things.

    They’ve explained nothing.

  9. Rumraket: They do call the EQU function a “complex feature”(and it is indeed the particular one they are interested in how evolves), but also “the most complex function”, implying it’s not an absolute measure.

    So complexity is relative. Does that mean it cannot be defined? Does that make it “magic” and unscientific? I guess so.

  10. Tom English: Do you not feel obligated, if you suspect that my sinfulness has blinded me to the genius of Marks et al., to use the link I provided, and have a look for yourself? You don’t need to read the paper to see that Table 1 (screen shot attached) resembles their Table 6.3.

    Why do you think I asked if you have a beef with their table? They rather obviously have in mind a specific paper and they are not shy about which one. I’m trying to figure out what your specific complaint is about their handling of Avida in the book.

    Is it that they view Avida through the lens of a particular paper that introduced Avida to the world, or is it something else?

  11. The next section describes our experimental system, including the logic functions that digital organisms can use to obtain energy. There follows a case study of the genomic and phenotypic changes in a population that evolved an especially complex function, and then a functional-genomic analysis of the first genotype able to perform that function.

    It’s not just complex, lol, it’s “especially complex.” Got that Rumraket? It’s like relative on top of relative!

    Logic functions that digital organisms can use in order to obtain energy. How teleological. Shall we pretend as if this wasn’t programmed in to Avida by intelligent design? So it’s like a system of rewards. Pre-programmed rewards.

    Isn’t it remarkable how even though it’s not a search it still managed to find the target? The paper is all about how they experiment managed to “evolve” the EQU logic function. not just any function, but that particular, specific, function.

    Just a fancy WEASEL.

  12. Mung: Just a fancy WEASEL.

    Would that be a latching or non-latching WEASEL Mung? Apparently it makes all the difference…..

  13. Mung: Rumraket: This will make sense of the Lenski paper too. When they say that they are explaining the origin of “complexity”, they’re not claiming that there is some universal cut-off where things become “complex” and they were not before. All they mean is that the system in question comes to have a greater number of interacting parts that come together to work, than it had in the beginning.

    Then they have not explained “the origin of complexity at all.”

    If you read the paper you will see that they do in fact explain how greater complexity comes about.

    They are bullshit artists, and you fell for it.

    No, they aren’t, in fact what they say makes perfect sense. In general, evolution will make things more complex (add functional parts) if doing so is selectively favored. As in, mutations that add parts (such as duplications), will add to the degree of complexity if those mutations are some times adaptive and therefore retained by selection.

    Complex things have their origin in simpler things. Well freaking duh. Really?

    Complex things begin as simpler things, yes. That alone doesn’t say how they become more complex through evolution. Nor has anyone claimed that the mere fact that complex things began as simpler things is itself an explanation. You’re confused and failing to read for comprehension.

    And simpler things have their origin in more complex things.

    They’ve explained nothing.

    Actually they have, just not in the words you use to try and mock and dismiss it. Instead you elect to write this whiny bullshit post without substance. No, the caricature you make of their work isn’t their explanation. I’ve given you an ultra-short version of it. Again, in general evolution will make things more complex (add functional parts) if doing so is selectively favored. As in, mutations that add parts (such as duplications), will add to the degree of complexity if those mutations are some times adaptive. It’s really so simple a child can understand it.

  14. Mung: Rumraket: They do call the EQU function a “complex feature”(and it is indeed the particular one they are interested in how evolves), but also “the most complex function”, implying it’s not an absolute measure.

    So complexity is relative. Does that mean it cannot be defined? Does that make it “magic” and unscientific? I guess so.

    Who says it can’t be defined or that it’s magical and unscientific? I defined it already, and it’s a measurable quality. The degree of complexity refers to the number of interacting parts, and/or the number of ways in which those parts can interact and behave.

    If it has more interacting parts, it’s more complex. Is A more complex than B? Count the number of parts and the number of ways they can interact to find out.

    This is a rather intuitive definition of complexity that happens to also be at least in principle quantifiable. We can count the number of parts. Genes, nucleotides, amino acids, organelles and so on. I don’t see why this can’t be directly transferred to an analysis of the complexity of a digital organism. It’s going to have a genome consisting of individual segments that interact, which refers to specific functions. The number of them and the number of ways they interact is the measure of the complexity of the organism. If this number increases over multiple generations, then it is evolving greater complexity.

    You have to do some work to explain to me what problem you have with this, if any.

  15. Mung: The next section describes our experimental system, including the logic functions that digital organisms can use to obtain energy. There follows a case study of the genomic and phenotypic changes in a population that evolved an especially complex function, and then a functional-genomic analysis of the first genotype able to perform that function.

    It’s not just complex, lol, it’s “especially complex.” Got that Rumraket? It’s like relative on top of relative!

    Yes, it’s relative. I don’t see why we have to focus on whether they think it’s “especially” complex. What matters is whether it is more complex than the organism that began the experiment, and if it is, how much more complex is it and how did that organism evolve?

    Forget about the adjective and focus on the substance. How do things become more complex through evolution?

    Logic functions that digital organisms can use in order to obtain energy. How teleological. Shall we pretend as if this wasn’t programmed in to Avida by intelligent design?

    Of course it was programmed into Avida by intelligent design. Avida is an instance of evolution, it is not supposed to constitute an example of the origin of life.

    The program has been designed to contain at least one organism that has itself been designed to be able to gain energy so it can reproduce itself. The program has not been designed to determine how such an organism might come to exist without intelligent design.

    So it’s like a system of rewards. Pre-programmed rewards.

    In some runs, yes. In those cases the avida program can be set up such that some functions are artificially defined to be rewarding (aka, adaptive, favored by selection). Actually they seem to have run the program in at least three modes.
    In one mode where all additional functions were artificially rewarded.
    In one mode where only some of them were (so that some of the intermediates, while functionally more complex, were selectively neutral).
    And one mode where none of the additional functions were artificially rewarded.

    The runs were repeated many times in all three modes.

    The results should not be surprising. In the cases of the artificial rewarding of all additional functions, EQU evolved and did so the fastest compared to the other modes.
    In the case of the run where only some of the additional functions were rewarded, EQU still evolved, though this time through selectively neutral (non-rewarded) but still more complex functions. This was also slower of course.
    And lastly in the case of no artificial rewards, EQU did not evolve in the alloted time. Some more complex functions still did though.

    If new functions are not artificially rewarded, the adaptive behavior of a function is emergent (whatever the function accomplishes for the organism happens to give it competitive advantage through how it interacts with the simulated environment), not pre-programmed.
    You can run the program without artificially defining particular functions as rewarding (as I have been saying many time snow). If you do this, you will discover that more complex functions still do evolve, but since their evolution is due is emergent, whatever selective pressure favors their emergence is transient and eventually the ability might be lost again. Interestingly, there is nevertheless some trend towards new, more complex functions even when the program is run without artificially rewarding the new functions. You can try it yourself and let it run for a few hours and you will discover new functions will have taken hold of the population even when you remove all artifical rewarding of new functions.

    Isn’t it remarkable how even though it’s not a search it still managed to find the target?

    The paper is all about how they experiment managed to “evolve” the EQU logic function. not just any function, but that particular, specific, function.

    That was an arbitrarily picked benchmark of complexity, but yes it was in effect the target of the experiment. In so far as it evolved, the purpose of the experiment was to see how and why it evolved. Interestingly, no two runs were the same. Even when all the functions were artifcially rewarded, EQU evolved through a different path every time.

    Just a fancy WEASEL.

    I actually agree, if you artifically reward every new function, you’re doing a sort of WEASEL.

  16. phoodoo: What luck!

    Take five letters, L, U, C, K, Y. Mix and match them at random until they spell LUCKY. Ain’t evolution grand! Look how we evolved something complex from something simple!

  17. Mung,

    You clip this

    Tom English: Do you not feel obligated, if you suspect that my sinfulness has blinded me to the genius of Marks et al., to use the link I provided, and have a look for yourself? You don’t need to read the paper to see that Table 1 (screen shot attached) resembles their Table 6.3.

    from my comment, and indicate that you are terribly confused:

    Mung: Why do you think I asked if you have a beef with their table? They rather obviously have in mind a specific paper and they are not shy about which one. I’m trying to figure out what your specific complaint is about their handling of Avida in the book.

    Is it that they view Avida through the lens of a particular paper that introduced Avida to the world, or is it something else?

    Before I say anything more to you, you are going to say straight out that you cannot tell from the full comment, copied below, what Marks, Dembski, and Ewert have gotten wrong.

    ________________________________

    Mung: Do you dispute their Table 6.3? Do you dispute they are referring to a specific paper?

    Do you not understand that I quoted from that specific paper, and highlighted text to call your attention to what was most important?

    Replication efficiency is the ratio of an organism’s genome length to the SIPs [units of energy] used during its life cycle. Computational merit is the total reward obtained over an organism’s lifetime for performing logic functions. Each genotype’s expected replication rate, or fitness, equals the product of these quantities.

    –Lenski, Ofria, Pennock, and Adami, “The Evolutionary Origin of Complex Features,”

    Do you not recognize what I emphasized in my quotation of Marks et al. above as a summary of their Table 6.3?

    The fitness used by Avida for performing operations is a function of the number of NAND gates needed for its minimal representation. If G is the number of gates used in a minimal representation, the fitness assigned by Avida is f = 2^G.

    Do you not feel obligated, if you suspect that my sinfulness has blinded me to the genius of Marks et al., to use the link I provided, and have a look for yourself? You don’t need to read the paper to see that Table 1 (screen shot attached) resembles their Table 6.3. You need only read the caption to see that

    The reward for computational merit increases with 2^n, where n is the minimum number of nand operations needed to perform the listed function.

    Now reread the first quote. Is your impulse to look for a way to make Marks et al. right, no matter that they are obviously and egregiously wrong? Do you think it was clever for them to say absolutely nothing about energy in Avida (except when they quoted Lenski et al. referring to energy)? Do you think they did better in their published paper, “Evolutionary Synthesis of Nand Logic: Dissecting a Digital Organism“?

  18. Rumraket: Interestingly, there is nevertheless some trend towards new, more complex functions even when the program is run without artificially rewarding the new functions.

    This is extremely important, as a response to Marks, Dembski, and Ewert. They respond to Tierra, labeling it a failure because it did not exhibit the proliferation of complexity that Ray had hoped it would, and make no mention of later work in open-ended evolution.

  19. Tom, I am asking for you to present not a litany of of objections, but one objection, so that I may try to answer it.

    If it takes five NAND gates to construct EQU and the reward is 32 and 2^5 = 32 then your complaint is what?

    If it takes four NAND gates to construct NOR and four NAND gates to construct XOR and the reward is 16 and 2^4 = 16 what is your complaint?

    Is it your contention that logic functions which require more NAND gates are not given greater rewards than logic functions which require fewer NAND gates?

    No, that can’t be it, because the authors explicitly state that is the case! The table is reproduced from the actual paper.

    Did DEM get it wrong that XOR requires four NAND gates while AND only requires two?

    http://www.electronics-tutorials.ws/logic/logic_5.html

    ok, let’s see what we can AGREE on. Let’s try that. Logic functions which require fewer NAND gates are given fewer rewards and logic functions which require a greater number of NAND gates receive a greater number of rewards. That what the paper says. It shouldn’t be in dispute.

    What do they mean by rewards and why did they adopt that particular scheme for doling out awards?

  20. Rumraket: That was an arbitrarily picked benchmark of complexity, but yes it was in effect the target of the experiment.

    Let’s emphasize that you’re not saying that the target was determined arbitrarily. The experimenters selected the “target” to suit Avida with the default instruction set. (What’s arbitrary is the preference for NAND over NOR in the instruction set. With the latter, the experimenters would have defined the energy payoffs for metabolic functions in terms of the NOR complexity, instead of the NAND complexity, of the functions. The function with the greatest NOR complexity is XOR, not EQU.)

    As I emphasized in the OP, the “conservation of information” math of Marks et al. does not apply. Marks et al. say in the preface (freely available online — click on the link at the top of the post):

    Since Avida is attempting to solve a moderately hard problem, the writer of the program must have infused domain expertise into the code. We identify the sources and measure the resulting infused active information.

    But the measure of “active information” means nothing, because the ostensible problem is not determined independently of the evolutionary process, and the “conservation of information” math thus does not apply. What I see Marks and Ewert doing already, in Discovery Institute outlets, is to move on to new claims. They know that “conservation of information” is a pig. I think they’ve known it for quite some time. They’re culture warriors, not legitimate scholars. They glopped together their little pieces of shit, and devised rhetoric to make the whole seem like a giant scoop of chocolate ice cream to faithful readers.

    Swallowing Mount Fecal — good title for a sociological study of creationists.

  21. A digital organism (daAND01) “evolves” a logic function which can perform AND logic. It receives twice as many “rewards” as a digital organism (daNOT01) that “evolved” only a logic function that can perform NOT logic. What is the effect of that?

    Will daAND01 leave more “offspring” than daNOT01, and why should that be the case?

    To what end is daAND01 rewarded with more “computational merit” than it’s unlucky counterpart?

    The question answers itself. The entire setup is TELEOLOGICAL.

  22. Rumraket: Complex things begin as simpler things, yes. That alone doesn’t say how they become more complex through evolution. Nor has anyone claimed that the mere fact that complex things began as simpler things is itself an explanation. You’re confused and failing to read for comprehension.

    No one disputes that “complex things” are composed of “simpler things.” That’s pretty much a given isn’t it? Yet their paper claims to demonstrate that complex things come about by the aggregation of simpler things. Well freaking duh!

    Who ever thought otherwise?

    The only thing of interest is the subtext. That whatever they have chosen to represent complexity could arise without intelligent design. Here, they failed, miserably.

  23. Rumraket: Who says it can’t be defined or that it’s magical and unscientific? I defined it already, and it’s a measurable quality. The degree of complexity refers to the number of interacting parts, and/or the number of ways in which those parts can interact and behave.

    So it’s a simple matter of combinatorics? Take binary, for instance.

  24. Mung,

    I am frustrated with you. It seems now that you are genuinely confused. You don’t like hearing that. But I’ll make it clear enough in a while. First I’m taking a short break for attitude adjustment.

  25. Mung: A digital organism (daAND01) “evolves” a logic function which can perform AND logic. It receives twice as many “rewards” as a digital organism (daNOT01) that “evolved” only a logic function that can perform NOT logic. What is the effect of that?

    Will daAND01 leave more “offspring” than daNOT01, and why should that be the case?

    To what end is daAND01 rewarded with more “computational merit” than it’s unlucky counterpart?

    The question answers itself. The entire setup is TELEOLOGICAL.

    Oh, so you’ve gotten the memo from the Discovery Institute. New talking points. Go ahead and say, “TELEOLOGICAL FINE TUNING.” Because you most definitely should not go into the details of the glopped-together turds Ewert and Pals just published.

  26. Rumraket: I don’t see why we have to focus on whether they think it’s “especially” complex. What matters is whether it is more complex than the organism that began the experiment, and if it is, how much more complex is it and how did that organism evolve?

    None of the members of the initial population could perform any logic function. Shouldn’t they all have the same “fitness”?

    Let’s imagine a digital world where no digital organism is rewarded based upon some criterion chosen by The Designers. Let it evolve for some number generations. Pull out the most complex organism and explain why it is more complex than the others. Explain why that particular “complexity” was not rewarded yet it “evolved” in spite of that fact.

    Write a paper. Write a book. Become famous for testifying at a trial that it was all done without intelligent design.

  27. Tom English: I am frustrated with you. It seems now that you are genuinely confused. You don’t like hearing that. But I’ll make it clear enough in a while. First I’m taking a short break for attitude adjustment.

    I don’t mind hearing that I am confused. If I hear nothing at ll, that is a cause for concern. 🙂

    I thought I asked some pertinent questions. How did they arrive at their system of rewards? It seems to me to be based on the number of NAND gates needed to implement the particular logic function.

    So let’s start there.

  28. Rumraket: The program has been designed to contain at least one organism that has itself been designed to be able to gain energy so it can reproduce itself. The program has not been designed to determine how such an organism might come to exist without intelligent design.

    No, this is simply incorrect. Didn’t you read the paper? Organisms don’t need to “gain energy” in order to reproduce.

    They are provided with a reproductive advantage if they evolve certain predefined features. It’s like having a big god in the sky declaring who will leave more offspring.

  29. Mung: It’s like having a big god in the sky declaring who will leave more offspring.

    Given that’s what you believe, I’m not sure what your objection is. Surely that makes it more like reality?

  30. Mung: Become famous for testifying at a trial that it was all done without intelligent design.

    Conflate much Mung?

  31. Mung: Let’s imagine a digital world where no digital organism is rewarded based upon some criterion chosen by The Designers. Let it evolve for some number generations. Pull out the most complex organism and explain why it is more complex than the others. Explain why that particular “complexity” was not rewarded yet it “evolved” in spite of that fact.

    Write a paper.

    Odd how you are encouraging others to write a paper. Why don’t you do it? You know that evolution is wrong, but can’t quite say why. A paper would be the perfect platform for you.

  32. Mung: Write a paper. Write a book. Become famous for testifying at a trial that it was all done without intelligent design.

    “TELEOLOGICAL FINE TUNING.”
    “TELEOLOGICAL FINE TUNING.”
    “TELEOLOGICAL FINE TUNING.”
    “TELEOLOGICAL FINE TUNING.”
    “TELEOLOGICAL FINE TUNING.”
    “TELEOLOGICAL FINE TUNING.”
    “TELEOLOGICAL FINE TUNING.”

  33. Mung: Take five letters, L, U, C, K, Y. Mix and match them at random until they spell LUCKY. Ain’t evolution grand! Look how we evolved something complex from something simple!

    I don’t think anyone would say that. Rather, they’d say something functional and/or meaningful (to us) has evolved from something nonfunctional/meaningless.

    And it wouldn’t so much be by “mix and match at random”. It’d be through random permutation at one or a few sites at a time, and selection for being comprehensible.

  34. Tom English: Rumraket: That was an arbitrarily picked benchmark of complexity, but yes it was in effect the target of the experiment.

    Let’s emphasize that you’re not saying that the target was determined arbitrarily. The experimenters selected the “target” to suit Avida with the default instruction set.

    Of course. They didn’t just pick from the set of anything imaginable. They picked something the program could at least in princple evolve.

  35. Mung: A digital organism (daAND01) “evolves” a logic function which can perform AND logic. It receives twice as many “rewards” as a digital organism (daNOT01) that “evolved” only a logic function that can perform NOT logic. What is the effect of that?

    Will daAND01 leave more “offspring” than daNOT01, and why should that be the case?

    To what end is daAND01 rewarded with more “computational merit” than it’s unlucky counterpart?

    The question answers itself. The entire setup is TELEOLOGICAL.

    I actually agree with this. If you artificially reward certain logic operations with more resources (which in turn go towards reproduction), and if those logic operations are likely to result from the process of mutation, you have in effect constructed a path towards something.

  36. Mung: Rumraket: Complex things begin as simpler things, yes. That alone doesn’t say how they become more complex through evolution. Nor has anyone claimed that the mere fact that complex things began as simpler things is itself an explanation. You’re confused and failing to read for comprehension.

    No one disputes that “complex things” are composed of “simpler things.” That’s pretty much a given isn’t it?

    Yes I think it is. And that is part of the definition of complexity, as phoodoo asked for. That’s why I tried to define it. And I did define it, and here you are agreeing with me. I’m glad.

    Yet their paper claims to demonstrate that complex things come about by the aggregation of simpler things. Well freaking duh!

    No, they don’t claim to demonstrate THAT complex things come about by the aggregation of simpler things. They claim to demonstrate WHY i does this WHEN it does, through the evolutionary process of random mutation and selection.

    They are attempting to explain HOW it is that evolution can produce entities with great complexity. They demonstrate this by showing that, if some of the intermediates are adaptive, they will be retained and serve as further building material for later increases too.

    How those things got to be adaptive in the first place is actually besides the point.

    It is supposed to be an analogy to real biology. How did somethingvery complex with lots and lots of parts, like the bacterial flagellum evolve? Well, if we look at avida, we can show how this can happen if there are adaptive steps along the way. They don’t ALL have to be adaptive, and they don’t all have to be the same as the final function. Some of them can be neutral, even slightly deleterious, and contribute to different functions along the way.

    THAT is what they are in fact demonstrating.

    The only thing of interest is the subtext. That whatever they have chosen to represent complexity could arise without intelligent design. Here, they failed, miserably.

    No, they did not.

  37. Mung: So it’s a simple matter of combinatorics? Take binary, for instance.

    I don’t know what exactly is meant by the term combinatorics. I’m giving an intuitive definition of complexity, not a rigorous mathematical one. And I wouldn’t claim we can practically apply it in all imaginable cases or that it would be easy to do.

    Nevertheless, I claim that we can use that intuitive definition to make sense of real and digital biology and measure the complexity of some systems. In some cases even down to single components. Compare two proteins. One is 172 amino acids long. Another is 411 amino acids long. My definition would say the 411 amino acid one is more complex. Unless the 172 amino acid one has many many more interactions with other cellular entities than the 411 amino acid one. We’d have to find out of course, to actually determine which is more complex. But at least we could in principle do that.

    And it would make sense. It’d be a definition of complexity even ID proponents could agree with. Because under this definition, a bacterium with a flagellum would be more complex than the same bacterium without. And a bacterium with two flagella would be more complex than the same bacterium with only one flagellum. And a multicellular organism made of a thousand cells would be less complex than a multicellular organism made of a trillion cells. And so on. And we could even quantify the degree of complexity here. The trillion-cell organism would be a billion times more complex than the thousand-cell organism.

    So a bacterium would clearly be less complex than a human being. And a human being would probably be more complex than a house cat. But as I said, in some cases it might be hard to determine. Is a human more complex than a large tree? That might be very hard to answer practically. I’m not claiming to have discovered the universally applicable quantifiable definition of complexity. I’m claiming that there is a colloquial, intuitive sense of the word that we can use that also makes sense of some ID proponents ideas. Such as Behe’s Irreducible Complexity.

  38. Mung: Rumraket: This is a rather intuitive definition of complexity that happens to also be at least in principle quantifiable. We can count the number of parts. Genes, nucleotides, amino acids, organelles and so on. I don’t see why this can’t be directly transferred to an analysis of the complexity of a digital organism. It’s going to have a genome consisting of individual segments that interact, which refers to specific functions. The number of them and the number of ways they interact is the measure of the complexity of the organism. If this number increases over multiple generations, then it is evolving greater complexity.

    You have to do some work to explain to me what problem you have with this, if any.

    Show me how it applies to Avida.

    I think the most direct way it applies is to the number of gates that make up an avidian. If it has more gates that contribute to the function of the organism than another one has, then it is more complex than the other one.

  39. Mung: Rumraket: The program has been designed to contain at least one organism that has itself been designed to be able to gain energy so it can reproduce itself. The program has not been designed to determine how such an organism might come to exist without intelligent design.

    No, this is simply incorrect. Didn’t you read the paper? Organisms don’t need to “gain energy” in order to reproduce.

    Sorry but it is you who is incorrect. The basic avidian, before any evolution has occured, must reproduce by using energy. That’s just how it works. Reproduction has a “cost”. The organism must consume CPU time and memory space for reproduction to occur. So for the organism to even be able to reproduce at all it must come with the ability to use CPU time and memory. It has a pre-defined basic ability to do this.

    From the paper: “Experiments began with an ancestor that could replicate but could not perform any logic functions. All organisms were identical and obtained equal energy to execute their genomic programs, including the copy commands by which a genome replicates itself one instruction at a time. Copying is subject to errors, including point mutations, insertions and deletions. Each mutation alters the genome and may change an organism’s phenotype, including its replication efficiency, computational metabolism and robustness. Thus, genotypes vary in their expected reproductive success. As in nature, selection in Avida depends on the phenotypic effects of a mutation in its genetic context and in relation to the organism’s environment; the researcher does not specify a distribution of selection coefficients. Most mutations in Avida are deleterious or neutral, but a small fraction increases fitness20.”

    My emphasis in bold.

    They are provided with a reproductive advantage if they evolve certain predefined features. It’s like having a big god in the sky declaring who will leave more offspring.

    Yes, I agree. The program can be set up like that, and that is one of the modes in which the experiment was run.

    But the program can also be set up NOT to give artifical rewards to certain features. And it was in fact run in that mode. And some of the organisms evolved greater complexity anyway, though they did not evolve the EQU function. Though even when the EQU function did evolve, it was not because every single mutation was rewarded with additional resources.

    Case-study population
    The ancestor could replicate but could not perform any logic function. However, an organism that evolved one or more of nine logic functions would obtain further energy. The benefit increased exponentially with the approximate difficulty of each function (Table 1). Functions could be performed in any order during an individual’s life, but no extra energy was obtained by repeatedly performing the same function. No single mutation in the ancestor can produce even the simplest of these functions. Instead, several mutant instructions must appear in the same lineage, and such that they are coordinately executed, to perform even a simple function. Nonetheless, this population (and many others) evolved the capacity to perform EQU, the most complex of these functions.”

    So greater complexity can and does evolve in Avida, it just doesn’t necessarily come in the form of particular logical functions.

  40. Rumraket,

    Do you mean a bacterial flagellum could develop through adaptive advantages, if say the P Ring had an adaptive advantage? And the L Ring, in exactly the right place would have a selective advantage? And the hook part of the flagellum, if that just so happened to mutate at exactly the right time, at exactly the right place, well the flagellum was still forming, and if it also had a selective advantage BEFORE the whole network was finished, then this of course would help the bacteria with it have a reproductive advantage? And the MS ring, that would also have a selective advantage? Especially if it was exactly in the spot where it would be needed when it helped to form a gasket later?

    And they stators, they also would have a selective advantage, before a flagellum was fully formed? And the rod which sits exactly in the middle of the different rings, which make up perfect symmetrical cam shaft like bodies, that can spin and brake at high speed, that rod would have needed to have a selective advantage, with or without the rings already positioned exactly where they need to be, and spaced exactly the right distances from each other, is that right? So both the rings and the rod, they were both very useful as a reproductive advantage, long before they were assembled together.

    Haha, haha….this evolution story sure is entertaining.

  41. Rumraket,

    So greater complexity could come in the form of like say, 100 grains of sand instead of five grains of sand-would that be more complexity? Or like say if we started with human, and then gave that human 600 different mutations, would that human then by definition be more complex then a human without those 600? Or like a cancer cell that has metastasised, that is more complex than a benign tumor cell right?

  42. phoodoo: Do you mean a bacterial flagellum could develop through adaptive advantages, if say the P Ring had an adaptive advantage? And the L Ring, in exactly the right place would have a selective advantage?

    Sure.

    And the hook part of the flagellum, if that just so happened to mutate at exactly the right time, at exactly the right place, well the flagellum was still forming, and if it also had a selective advantage BEFORE the whole network was finished

    I don’t see any reason to believe the hook part of the flagellum developed before the rest. In fact I don’t buy into the particular chronology you come up with here.

    But besides that, sure, the general principle is that mutations that happen to have a selective advantage is are retained. Not that the flagellum functioned as a flagellum all the way from start to finish, that’s the whole point of the argument against irreducible complexity. And that argument was supported by the Avida experiment by Lenski et al.

    I get that you ask these questions because you think the whole thing appears to you preposterous. That much is obvious. What is lacking is the why? As I said before. This is all you do, you do a performance. An act. You play the part of someone who finds the whole thing ridiculous. You never get around to showing why it is.

    Great job phoodoo, you’re really showing us with your reason and logic.

    Haha, haha….this evolution story sure is entertaining.

    This part of your social signaling act isn’t an argument either. But yes, congratulations, you’ve made it clear to your cohorts that you’re like them and you reject the whole thing.

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