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Selling Stupid

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Granville Sewell’s sin is pointing out the obvious that anyone can understand. This represents a tremendous threat. As David Berlinski has observed, Darwinists — who have invested their worldview and even their careers in Darwinian storytelling — react with understandable hostility when told that their “theory” is simply not credible.

It’s really easy to figure out that the Darwinian mechanism of random mutation and natural selection cannot possibly do that with which it is credited. Life is fundamentally based on information and information processing — a software computer program and its associated, highly functionally integrated execution hardware. Computer programs don’t write themselves, and they especially don’t write themselves when random errors are thrown into the code. The fact that biological computer programs can survive random errors with remarkable robustness is evidence of tremendously sophisticated fault-tolerance engineering. The same goes for the hardware machinery of life.

One of my specialties in aerospace R&D engineering is guidance, navigation and control software. The task of designing GN&C algorithms and the associated hardware that would permit an ornithopter to land on a swaying tree branch in gusting wind is so far ahead of our most sophisticated human technology that we can only dream about such a thing. Yet, birds do this with ease.

Darwinists want us to believe that this all came about through a process of throwing monkey wrenches in working machinery and introducing random errors into highly sophisticated computer code.

In addition, they argue that because the sun provides energy available to do work, all the obvious engineering hurdles can be dismissed as irrelevant to the discussion.

This is simply not credible.

In fact, it’s downright stupid.

Selling stupid is a tough assignment.

No wonder Darwinists have their panties in a bunch.

Comments
Elizabeth, For all of your bluster (re HOX genes) there still isn't any evidence that Darwinian processes can construct new, useful and functional multi-part systems. And there isn't any evidence Darwinian processes produced HOX genes nor is there any evidence taht Darwinian processes can change body plans.Joseph
June 27, 2011
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Dr Bot: If you read in context you would see that I am specifically focussing on the equivalent of origin of body plans, and separately address origin of a self-replicating entity in a PS; which responds to a remark by Dr Liddle. The notion that in effect a hello world can be transformed into a system controller step by small step on one branch and an operating system on another, plus a video editor on a third, etc, on small random changes backed by trial and error success, is on its face highly dubious, and lacks empirical support. I repeat, the GAs and the like all show VARIATION WITHIN A HIGHLY SPECIFIED AND INTELLIGENTLY ARRIVED AT ISLAND OF FUNCTION. At most, on a generous analogy, micro-evo. Perhaps the most misleading Darwinian icon of all is the smoothly varying tree of life, once the complex information systems embedded in such life forms were identified. Your valid model of body plan origin evolution is _______? Your empirical evidence of spontaneous, un-designed origin of body plans by chance variation and culling through differential reproductive success on a tree of life type model starting with the Cambrian layers is ___________? (By contrast we can present he book publishing industry and the ICT industry as examples of intelligent design as the empirically warranted source of FSCI.) GEM of TKIkairosfocus
June 27, 2011
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But the switcheroo now happens: presto, variation within an island of function on some hill-climbing algorithm or other, is now presented as an explanation of how one gets TO an island of function in an extremely large config space.
kindly explain where either myself or Elizabeth attempt to use evolutionary processes to explain the origin of self replicating systems. We are talking about evolutionary processes which require replication with variation where the variety affects replication rates. In the case of the things I have discussed, I would argue that these are instances of evolution, but not models of biological evolution.
In that context, Dr Bot et al, the challenge that even the NAND gate that is the underlying functional element involved, becomes a highly significant demonstration of the reality of already being on an island of function by design when you begin.
Yes, we start with building blocks, in the cases I've outlined we are evolving circuits from functional logic gates, although it has been tried with transistors, capacitors, resistors etc. (real components, not simulated) And with lithography mask patterns for transistor fabrication (which are tested in an industrial simulator used for verifying integrated circuit designs)
That is why I have so often raised the issue of using monkey at keyboard equivalents to write the program modules, then once functional modules exist we can then talk about moving around on islands of function and hill-climbing to one’s heart’s content. Such a model would definitively show that one can arrive at islands of function by chance variation and trial and error; on success.
But you just said this:
The pivotal issue is: exactly what one is modelling, and what does this signify? If we were doing a valid model that correctly simulated something and accurately said what it simulated with what limitations
Your proposed model is of random noise, it accurately simulates random character generation, but I suspect it would have a skewed distribution. If you want to establish if chemistry - the laws of physics - can get to an island of function then you need a model that represents these laws, interactions and contingencies.DrBot
June 27, 2011
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PS: Origin of cell based life with metabolism integrated with an information based von Neumann self-replicator is of course simply the first case of body plan origin to be explained. While it is credibly at lest 100x the 1,000 bit threshold for FSCI, it is in turn actually far simpler in information origin terms than origin of body plans for complex organisms with specialised organs, which requires credibly 10 - 100+ MILLION bits of information dozens of times over for the dozens of main body plans. The hiving off of OOL as thought that is the special case that has not been solved, but hey, here's our wonderful branching tree of life model that allows us to see smoothly varying populations giving rise to body plans is yet another bait and switch in the teeth of the observed fossil evidence that body plans originate suddenly, and show stasis on basic form.kairosfocus
June 27, 2011
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Indium: FYI, on odds, I was probably working with models (electronic ckt design h-parameter models are models, for just one instance [e.g. tell me how the AC ground and bypass capacitor lo freq rolloff are integrated to model a full amplifier . . . ] . . . and the classic kinetic theory of gases is a model, even, the Newtonian point-particle is a model [recall his reduction of a spherical planet to a particle equivalent; what is the density of a point-mass?], etc) when you were still in nappies. So, kindly, do not poison the atmosphere by presuming or suggesting ignorance or stupidity etc -- a la Dawkins and ilk. The pivotal issue is: exactly what one is modelling, and what does this signify? If we were doing a valid model that correctly simulated something and accurately said what it simulated with what limitations:
(all models are strictly false but exploit the peculiarity of the implication operator that a strictly false antecedent can under limited conditions entail correct consequences; hence the need for validation and rationalisation . . . ),
. . . that would be one thing; but what is happening here is that the "model" is being claimed to be a case of the real thing. What is actually being modelled is that: within an island of function, there can be successful adaptation of a complex functional information based entity on intelligent direction and arguably chance variation and differential success; i.e. at most microevolution. That is not in dispute, not even by young earth creationists. But the switcheroo now happens: presto, variation within an island of function on some hill-climbing algorithm or other, is now presented as an explanation of how one gets TO an island of function in an extremely large config space. [And, just to underscore the point, this is a cut down version of the phase space model used in statistical thermophysics and even in mathematics.] In that context, Dr Bot et al, the challenge that even the NAND gate that is the underlying functional element involved, becomes a highly significant demonstration of the reality of already being on an island of function by design when you begin. If you look at a hardware NAND, it is practically impossible to arrive at an island of function by chance on the gamut of the solar system's resources. When you move to a software NAND, which depends on the underlying hardware NAND or near-equivalents in several ways to make it go [as in how do you actually construct registers and the arithmetic and logic unit that is used to execute instructions], the same injection of huge dollops of design is there in the background. So, the validity of the claimed models, as touching the issue of arrival at islands of complex and specific function, is in immediate and serious doubt. That is why I have so often raised the issue of using monkey at keyboard equivalents to write the program modules, then once functional modules exist we can then talk about moving around on islands of function and hill-climbing to one's heart's content. Such a model would definitively show that one can arrive at islands of function by chance variation and trial and error; on success. But the problem is of course that 73 ASCII characters worth of functional information is beyond the resources of our solar system and 143 the observed cosmos. At the same time, 63 or even 125 bytes of information carrying capacity are impossibly small to implement any serious software process. Pointers that make something else do the heavy lifting DO NOT COUNT. (And FYI, that is what the so-called genomes in GAs do; real genes store specific control info for assembling proteins, and to regulate that assembly. Yet another point of relevantly inapt analogy.) In short, we have inappropriate extrapolation of a model beyond its generously plausible limits [micro-evo] to something it is profoundly and patently dis-analogous to, the claimed spontaneous origin of body plans by chance variation and differential reproductive success [body plan level macro evo]. (And if you want to play the card that macro is micro accumulated, that needs to be shown not asserted, on pain of bait and switch. Beyond that, the attempt to say that only skeptics speak in these terms so the terms are invalid is either devastatingly ignorant of the facts or outright irresponsible and/or willfully dishonest, cf the UD weak argument correctives.) Sorry, in fact Weasel was inappropriately used to persuade the general public and a lot of the scientific community that computer simulations were a valid way to model and present the unobserved macro-evolution. this was deceptivce, as Dawkins himself admitted and/or directly implied. Subsequent efforts have been poisoned by that underlying assumption or belief. The models, consistently show instead what intelligent design of a program, setting up on an island of function based on knowledge and skill, and exploiting the capacity of hill-climbing as a way to make explicit the peaks of designated functions on spaces surveyed is. The whole exercise is wrong-headed, and is further poisoned by an initial action that was plainly wrong hearted too. That is why we need to look back at Gil's point in the original post, and soberly reflect on it. GEM of TKIkairosfocus
June 27, 2011
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Well, in a sense Avida is a model, but in another sense it's a perfectly real, potentially useful code-writing tool. And other GAs really are - they aren't written as a "model of" evolution, they are "modeled on" evolution, precisely because evolutionary processes (namely, replication with random variation that affects the probability of reproduction) is a superb way of generation novel and ingenious solutions to real world problems! I entirely take the point that this doesn't explain how self-replicators that replicate with variation that affects the probability of reproduction got started, in life, in the first place, but it seems to me Darwin is getting all the misplaced stick here. Darwinian evolution clearly works, as Avida shows. It can generate useful, functional information. The as yet unsolved problem is how the first minimal self-replicator got there in the first place.Elizabeth Liddle
June 27, 2011
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Somehow I get the impression that neither Mung nor kf understand the concept of a "model".Indium
June 27, 2011
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KF@68 We are discussing how evolutionary processes can generate novel solutions. All the examples I have given re logic gates illustrate how evolutionary mechanisms can generate novel designs.
Those who imagine Avida is an example of evolution: have you ever designed and built a NAND gate circuit? Do you know what is involved in getting a transistor made and working? In making sure you do not “let the smoke out” of same? Do you understand what is involved in making a flip flop, or how that is involved in counters, registers, and other processing units such as are involved in a computer? Do you know what is involved in setting up a simulation of same and getting it to run on a specific hardware machine?
You appear to be arguing that that the people who design and use these simulations of logic circuits, or the people who use GA's to evolve live electronics do not know anything about creating simulations or working with live electronics. This makes no sense - they are the ones actually writing the simulations and using real electronics, how could they do this if they had no understanding of simulations and electronics, how could they get results - real results.
If you do not, please listen to those of us who have done these things, and things far more complex than that.
We have done these things, we have used evolutionary processes to design real electronics, create better antenna, even to search for better transistors by evolving micro-lithography mask patterns. Don't tell us that something that has been done can't be done :)
They may show how one may, on terms of an existing design, one may move around within an island of fucntion by using hill climbing algorithms or the like, but that is a very different matter.
Yes, that is the topic we are discussing - EVOLUTION - the effect of selection on a population of imperfect replicators - which are, by definition, functional as replicators.
There is a massive bait and switch game going on
Yes indeed, we are discussing evolution, now you have moved the goalposts to biogenesis. We are discussing how a population of imperfect replicators can evolve, not the origin of those replicators. This is what the term evolution applies to when talking about biology and GA's - replication with error leading to variable replication rates in a population - it doesn't refer to the creation of self replicators, or the physical world. Equivocation: A fallacy based on the use of the same term in different senses. Avida is an example of evolution.DrBot
June 27, 2011
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mung@37
DrBot:
Generally speaking any search has to have a target or it isn’t a search …
Thank you, thank you, thank you. I can’t believe how often I have to argue over this very simple fact (MathGrrl comes to mind).
I said:
Generally speaking any search has to have a target or it isn’t a search, but ‘targeted’ means something more specific – pre-specified and unchanging
Which is where your argument with mathgrrl comes from - she was using the correct terminology in the context of discussions about search algorithms. If you say 'I am searching' then that implies you are searching for something - it would make no sense to say 'I am searching for nothing' unless you meant 'I am not searching' - so in this general sense any search, including random search is looking for something, and we can call that a target. The phrase 'targeted search' is more specific and refers to having an explicit, pre-specified goal, rather than a set of dynamic criteria to match. Think about it this way - if all searches have to, by definition, have some form of 'target' in the loosest sense then arguing that they are therefore all 'targeted searches' is pointless semantics - the word 'targeted' is redundant because they are all searches and by definition there have to be targets of some kind. The inclusion of the word 'targeted' is there to indicate reference to a subset of search evaluation criteria, namely those that are explicitly defined and fixed in advance.DrBot
June 27, 2011
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Mung:
So if it meets a target or goal, specified in advance, programmed in advance, it gets rewarded.
If it performs some function, specified in advance, it gets rewarded. It's important to be clear about the difference between a genotype that is rewarded for performing a function (cf being able to jump), and being rewarded having a specific genotype (as in WEASEL). The genotypic configuration that are rewarded are not specified in Avida - indeed they are not even known, and may not even be a finite set. In other words, the is target defined by the problem to be solved, not the solution that will solve it, of which there are a large unknown number.
Why do some logic functions get rewarded more than others, i.e., why do some logic functions have more “computational merit” than others?
Because that's how life is. Some functions are only marginally advantageous, some more so.Elizabeth Liddle
June 27, 2011
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From the Wikipedia link cited above:
Intelligent design is the proposition that "certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection." It is neo-creationism, a form of creationism restated in non-religious terms. It is also a contemporary adaptation of the traditional teleological argument for the existence of God, but one that deliberately avoids specifying the nature or identity of the intelligent designer. Its leading proponents—all of whom are associated with the Discovery Institute, a politically conservative think tank—believe the designer to be the Christian God.
Does this include the agnostic David Berlinski? And Moonie Jonathan Wells? Are there others?NZer
June 26, 2011
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F/N: Collins English Dictionary: equivocation [??kw?v??ke???n] n 1. the act or an instance of equivocating 2. (Philosophy / Logic) Logic a fallacy based on the use of the same term in different senses, esp as the middle term of a syllogism, as the badger lives in the bank, and the bank is in the High Street, so the badger lives in the High Street Collins English Dictionary – Complete and Unabridged © HarperCollins Publishers 1991, 1994, 1998, 2000, 2003 --> equivocation is a fallacy, not always a willful deception --> However, insistent refusal to correct error in light of what one knows or should know can convert error into willful deception, so we must beware fallacy [?fæl?s?] n pl -cies 1. an incorrect or misleading notion or opinion based on inaccurate facts or invalid reasoning 2. unsound or invalid reasoning 3. the tendency to mislead 4. (Philosophy / Logic) Logic an error in reasoning that renders an argument logically invalid [from Latin fall?cia, from fallax deceitful, from fallere to deceive] Collins English Dictionary – Complete and Unabridged © HarperCollins Publishers 1991, 1994, 1998, 2000, 2003 --> Such fallacies, plainly, may involve simple error, not just willful deception --> Pardon, too: I seem to be especially typo prone these past couple of days.kairosfocus
June 26, 2011
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From the Nature PDF cited above: Our experiments demonstrate the validity of the hypothesis, ?rst articulated by Darwin and supported today by comparative and experimental evidence, that complex features generally evolve by modifying existing structures and functions. Some readers might suggest that we ‘stacked the deck’ by studying the evolution of a complex feature that could be built on simpler functions that were also useful. However, that is precisely what evolutionary theory requires, and indeed, our experiments showed that the complex feature never evolved when simpler functions were not rewarded. Our experiments also show that many different genomic solutions produce the same complex function. Following any particular path is extremely unlikely, but the complex function evolved with a high probability, implying a very large number of potential paths. Although the complex feature ?rst appeared as the immediate result of only one or two mutations, its function invariably depended on many instructions that had previously evolved to perform other functions, such that their removal would eliminate the new feature.NZer
June 26, 2011
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This has been a fascinating discussion, and so much more refreshing than the nastiness seen on other forums. Keep at it folks -- keep creating more light than heat!!! Personally I would like to see some documented examples of what GAs have been able to accomplish so that we can evaluate the best that they can produce.NZer
June 26, 2011
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Mung (and Dr Liddle): Besides which [as was already pointed out], a physical NAND gate or even a computer simulation running on a machine in turn dependent on such instantiations or the like, is already a context so deeply embedded with complex designs that the whole exercise is one in suspension of knowledge in the interests of a fantasy. In short Avida is fatally compromised from teh outset. It is no more a true representation of chance variation and blind trial and error giving rise to increasing complex, specific functional order than is Weasel. Which, as you pointed out, was a sly rhetorical fraud. (The very name is a hint of that . . . ) I think Dr Liddle as a great many others, is being taken in by a clever fraud that has so pervaded our intellectual climate that many of us cannot see the obvious as just what it is. There is an equivocation in the system, I suspect rooted in the fraud of a few, but now embedded in the way of thinking of the many. And when engineers, applied scientists and software engineers familiar with what is being glossed over try to point out what is wrong, we are often dismissed out of hand. Those who imagine Avida is an example of evolution: have you ever designed and built a NAND gate circuit? Do you know what is involved in getting a transistor made and working? In making sure you do not "let the smoke out" of same? Do you understand what is involved in making a flip flop, or how that is involved in counters, registers, and other processing units such as are involved in a computer? Do you know what is involved in setting up a simulation of same and getting it to run on a specific hardware machine? If you do not, please listen to those of us who have done these things, and things far more complex than that. Long befoe you get tothe sort of demonstration toy program like Avida that is being showcased as an example of evolution by chance variation and natural selection, a cumulatively huge amount of design and testing was involved to get to an island of function. Avida et al are actually examples of how real world limited variation can be programmed into complex designed systems, by their designers. We must not allow evolutionary materialism promoting rhetoric to distract us from that. On the evidence to date, computer simulations inherently can provide no conclusive evidence of the power of chance variations and natural selections to originate complex, specific function. They may show how one may, on terms of an existing design, one may move around within an island of fucntion by using hill climbing algorithms or the like, but that is a very different matter. There is a massive bait and switch game going on, and if we play by the rules of those who set it up to begin with, we will be taken in. And, Mung, you are right to highlight how Dawkins gave the game away with some weasel words he knew would not be heard amidst the beguiling spectacle of seeming evolution in action:
It . . . begins by choosing a random sequence of 28 letters ... it duplicates it repeatedly, but with a certain chance of random error – 'mutation' – in the copying. The computer examines the mutant nonsense phrases [i.e. they are non-functional!], the 'progeny' of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection [on non-functioning phrases rewarded by a designed so-called fitness function that ignores that inconvenient fact], and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection: about a million million million million million years. This is more than a million million million times as long as the universe has so far existed . . . . Although the monkey/Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. [So, why was it used at all?] One of these is that, in each generation of selective 'breeding', the mutant 'progeny' phrases were judged according to the criterion of resemblance to a distant ideal target, the phrase METHINKS IT IS LIKE A WEASEL. [so Dawkins KNEW that this was not a rewarding of increments in function . . . ] Life isn't like that. Evolution has no long-term goal. There is no long-distance target, no final perfection to serve as a criterion for selection, although human vanity cherishes the absurd notion that our species is the final goal of evolution. In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success. [i.e. there must first be function before one can hill-climb, the very point of the objection that the real challenge is to get to the islands of function] [TBW, Ch 3]
Deception by distraction, AKA bait and switch. QED GEM of TKIkairosfocus
June 26, 2011
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From the outset, Darwin realized that “organs of extreme perfection and complication”, such as the eye, posed a difficulty for his theory. Such features are much too complex to appear de novo, and he reasoned that they must evolve by incremental transitions through many intermediate states, sometimes undergoing changes in function.
Next time someone complains that Darwin is being taken out of context refer them to this paper. They fail to mention that Darwin didn't really think "organs of extreme perfection and complication, such as the eye" posed any difficulty for his theory. By the way, I think that complexity here is a bit of a red herring. The issue isn't just complexity, it's how everything works together to accomplish a purpose. Now it's wonderful how Avida can evolve an EQU function. But what goal does that serve?Mung
June 26, 2011
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Elizabeth Liddle:
Avida is indeed sets up an “evolutionary” process, where “evolutionary” is being used in its original Darwinian sense of being a process by which a population of organisms reproduce with random variation, and those that are most successful in surviving the environment replicate most often.
I'd like to thank Elizabeth for providing a link to the paper. http://myxo.css.msu.edu/papers/nature2003/Nature03_Complex.pdf ...and those that are most successful in surviving the environment replicate most often.
...digital organisms compete for energy and, depending on the environment, can obtain energy by performing logic functions... ...Each digital organism obtained ‘energy’ in the form of SIPs at a relative rate (standardized by the total demand of all organisms in the population) equal to the product of its genome length and computational merit, where the latter is the product of rewards for logic functions performed.
See Table 1 Page 140. So if it meets a target or goal, specified in advance, programmed in advance, it gets rewarded. Why do some logic functions get rewarded more than others, i.e., why do some logic functions have more "computational merit" than others?Mung
June 26, 2011
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And I suggest that the reason it looks as though I am saying something that to you doesn’t make sense isn’t because I am equivocating, but because you are “steeped in a way of thinking” that prevents you from seeing the simple truth of what I am saying
Well, there's a slight flaw in your reasoning. :) If that were so, I wouldn't be pointing out the different ways of looking at what you were saying, would I? So I see what you're saying just fine, thank you. I've rarely (though not never) charged you with making no sense. Rather, what I say is, what you are saying can be taken in more than one sense. Then you don't say no, it can only be taken in one sense. Rather, you typically tell me I misunderstood the sense in which you meant it. I disagree of course, though I may not bother to argue about it. I likely remind you that you are the one telling us you are striving to be clear and precise and unambiguous.Mung
June 26, 2011
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Mung:
You are certainly not immune from the charge of taking out GA’s and using them as proof of what evolution can do.
No, indeed. I think they are an excellent example of what evolutionary processes can do. And I suggest that the reason it looks as though I am saying something that to you doesn't make sense isn't because I am equivocating, but because you are "steeped in a way of thinking" that prevents you from seeing the simple truth of what I am saying :) Anyway, I appreciate at least the courtesy you have extended me of granting that it is possible that I am honest ;) Kf: thank you also for your clarification: however, I must still rebut the charge. I do not equivocate, if equivocate is defined as Mung does above. I'm off to bed now. Sleep well guys :)Elizabeth Liddle
June 26, 2011
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equivocate – to use ambiguous or unclear expressions, usually to avoid commitment or in order to mislead; prevaricate or hedge Perhaps you're the exception that proves the rule Lizzie. :) Let me be clear that I'm not saying you have those motives. I frankly believe you're steeped in a certain way of thought and that comes out in your posts as unreflective statements in which you use terms in a particular way because that's how you are used to using them. I'm trying to show you how that use can make it appear like you are saying something other than what you intended to say. For example, when you point out the wonderful things humans can create using "selection" without in any way trying to contrast the sorts of results that intentional/intelligent selection can bring about with those which non-intelligent and un-intentional "selection" can bring about, someone could well think you've made a valid point about what non-intelligent and un-intentional "selection" can do. But if they did so, it would be because of the equivocation involved, whether intentional on your part or not. At least Dawkins, when describing the Weasel program, told us, but evolution doesn't work that way. Which makes us wonder what the point was of the whole exercise. To me, it was exactly so that people would think that's how evolution works. The proof is certainly in the pudding, as they say. You are certainly not immune from the charge of taking out GA's and using them as proof of what evolution can do.Mung
June 26, 2011
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PS: Avida is exactly NOT a metabolising, reproducing organism, that then evolves on differential reproductive success in the context of competition for scarce resources. The term evolution may have persuasive value in this context, but it is being used in two very different senses without due notice of the difference being made.kairosfocus
June 26, 2011
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Dr Liddle: Pardon, I am not accusing, I am observing. Evolution is being used in drastically different senses in a context where that difference in sense is material. GEM of TKIkairosfocus
June 26, 2011
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PS: Do you know how much functional specificity is involved in building a real NAND gate (as opposed to a simulation, which BTW requires the real deal to build the computer circuits)? 1: The saturable active element, e.g. a bipolar junction transistor [BJT], which requires a thin lightly doped base, sandwiched between emitter and collector with specialised contacts to give the electrical inputs and outputs. 3: this needs to be characterised as to its behaviour [especially parameter BETA or ALPHA, which are related], so we know when it moves to saturation zone. 4: A bias supply, from a DC power supply or a battery, itself a complex and functionally specific object. 5: A circuit with input and load resistors, of specific values, and the right polarity. 6: Here, we need two BJTs in series for the easiest design, each controlled by an input circuit. 7: Controlled inputs, to deliver the controlled outputs. If I were to see a NAND gate, I would immediately infer to design as its best explanation. Actually, just the transistor or a resistor alone would be enough.kairosfocus
June 26, 2011
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kf: I have to say, I'm getting a little fed up of being constantly accused of "equivocation", especially if it is defined as Mung just defined it. I may be unclear; I may be mistaken; I may be confused; but I do not ever, ever, deliberately write to evade or obfuscate. Avida is indeed sets up an "evolutionary" process, where "evolutionary" is being used in its original Darwinian sense of being a process by which a population of organisms reproduce with random variation, and those that are most successful in surviving the environment replicate most often. The environment is simply an analog of an real life environment in which survival is a contingent of the ability to extract energy from it. My planned simulation is not, however, an evolutionary algorith, or, at least, it won't start that way. I hope one will emerge, and evolution will proceed from there.Elizabeth Liddle
June 26, 2011
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Dr Liddle: The use of the term "evolutionary" in this context is an equivocation. GA's and the like can make hill-climbing tours of islands of function they were set up on, but the result is in no wise even relevant to the issue of creating 500+ bits worth of functionally specific complex information out of chance variations filtered by trial and error; as opposed to an intelligently designed algorithm. In your pending simulation, please make sure you do not tumble into that error. GEM of TKIkairosfocus
June 26, 2011
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F/N: The EDM dissection of Avida is here. As background for the onlooker, NAND and NOR gates, in combination, can express any logic function, including memory [by incorporating digital, cross-coupled feedback, i.e the Flip Flop], and minimisation to express a function most economically is -- or has been -- a fairly common digital exercise. Avida seeks to implement various logic functions using a 'sea" of interconnected NAND gates. This is of course quite remote from the real-world task of a metabolising, von Neumann self-replicator based living cell. The term "organism," is little more than a sales gimmick, as is the claim that we are looking at "evolution." (Unfortunately, this seems to have been got away with over in Dover PA in 2005.) Sample clip:
Chips containing a sea of gates [6], [11], [13], all nand, are therefore capable of universal logic. This property allows evolutionary development of logic functions using the nand gate as the single logic component [1], [12], [25], [26], [32]. Avida [16], illustrated in Figure 1, performs logic synthesis using only the nand gate. The motivation behind Avida is not engineering design, but is rather to [16] “... show how complex [biological] functions can originate by random mutation and natural selection.” Avida generates an output equal to a logic combination of the inputs, X and Y. The logic operation under consideration that requires the most nand gates (five) is the XNOR. This is the ultimate goal of the search . . . . Avida uses a small alphabet of instructions (see Table I) to import the inputs, perform manipulation, and export the output. The instruction tape runs in a continuous loop. The number of entries can change during the search process . . . . Like choosing letters from the alphabet to form a sequence of words that will pass a spell check, the goal of Avida is to search for a sequence of instructions that has meaning with respect to the logic functions in Table II. The question is - how difficult is it to generate the logic functions in Table II [a table of 9 combinational logic functions] using the N = 26 instructions in Table I in a sequence of instructions?
While EDM give a more detailed analysis, the irrelevance, simplified and strawman nature of the task in view are readily apparent to the onlooker.kairosfocus
June 26, 2011
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kf 54: yes, I know. I was addressing a different point - whether evolutionary processes can result in the writing of code. They can. It is, demonstrably, possible to have a computer program that writes good code, all by itself - in other words the code that is written by the computer program evolves - it is not input by the designer of the program. I quite agree that that does not address the problem of where the underlying code (the code in which the whole thing is written) came from, but that was not what I was claiming to provide in this thread. That is the subject of a project I hope to get started on in the next couple of weeks.Elizabeth Liddle
June 26, 2011
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Avida is an example of an evolving population of algorithms that perform a function, using code. That code gets written, by Darwinian mechanisms, during the course of a run. Obviously the code in which the Environment is written doesn't evolve, nor does the code in which the organisms are written, but the code that the actual organisms contain is written, if not "by itself" by the process of random variation and replication with natural selection. Each digital organism, at the end, includes code that was not there at the beginning, and is there at the end, and performs a complex function. Who wrote it? I say evolutionary processes wrote it, and as those evolutionary processes were coded in the first place (by the AVIDA writers) then what they did was write code that wrote its own code - not the code that it was written in, duh, but the code that is created during the course of the run. BTW, I'm hoping for an response from you on the tennis thread, before the night is out :)Elizabeth Liddle
June 26, 2011
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Dr Liddle: I am sorry, but the context of the concerns expressed should be quite clear after these many weeks. GA's and the like START within islands of very intelligently created function, and go through hill climbing exercises per design, basically uncovering implicit information already built in. The real issue is to get to islands of function by chance variation and selection on emergent function. Avida, the program most centrally discussed in the linked paper, is a case in point of the concern. GEM of TKIkairosfocus
June 26, 2011
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The circuits they evolved were also cleaner and simpler than those designed by humans – I believe no one had ever managed to design a circuit like this where the fault checking was integral to the logic function rather than a separate circuit (that couldn’t detect faults in its self)
Actually you've described how they just did manage such a thing. Via the genetic algorithm they designed. Humans get the credit. Genetic algorithms give answers that we couldn't have come up with without their aid. But then so do algorithms that calculate the millionth digit of pi or report the millionth prime. There is nothing special about GA's in and of themselves. They are a tool that helps us realize the designs we are after, and couldn't possibly exist without our intelligent designing of them. But then so is a hammer, when it comes to building a house. We don't give hammers undeserved credit, so why GA's?Matteo
June 26, 2011
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