[A new Oxymoron: The use of random numbers during CA generation] - A New Kind of Science: The NKS ForumA New Kind of Science: The NKS Forum
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A new Oxymoron: The use of random numbers during CA generation
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Posted by: Gershom Zajicek M.D.
Objective: This thread will illustrate various aspects of randomness and their implication for the modeling of biomedical phenomena with CA.
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Cellular automata (CA) provide simple models for evaluating interesting philosophical questions. Here is a simple teaser:
The definition of a cellular automaton (CA) excludes randomness. Nevertheless S. Wolfram applies random numbers as initial states for his CA. What an inconsistency! Rather he ought to use CA for generating initial states, and ban the term “Randomness” from his models. You might apply the term “Pseudo-randomness” to a given state provided that you specify the CA (or CA set) which generated it, and the number of iterations to reach it. Wolfram uses a CA for generating pseudorandom sates, yet does not specify their two crucial attributes {CA set, number of iterations}.
Why do I dislike randomness? As a physician I am flooded with medical statistics based on the Normal Distribution and its derivatives. The Normal Distribution is the hallmark of randomness in science. However, in Medicine (like in Love) nothing is really random. Life and randomness is a medical oxymoron, which causes medically induced diseases known as Iatrogenesis.
More teasers in my site: http://www.what-is-cancer.com/papers/ca/ca01.htm
G. Zajicek gzajice@what-is-cancer.com
Posted by: Jason Cawley
The distinction between "pseudo random" and "random" assumes there is a real physical process that qualifies as the latter rather than the former. Which is at best debatable. The NKS book has an extensive discussion of forms of randomness - from page 299 to 326 -
http://www.wolframscience.com/nksonline/section-7.2
The whole of chapter 6 is about the behavior of simple programs from random initial conditions. But be clear about this - the systems examined there are completely deterministic in their evolution from their initial condition. There is no "inconsistency" with "the definition" of CAs. There is no coin-flipping at each step along the way, only different starting conditions. Each step below is always exactly the same for a given starting condition.
If you want to enumerate all possible initial conditions up to a certain width you can look at those instead of random initial conditions. You will find it rather hard once you get to a modest initial width, since the number of possible initial conditions rapidly exceeds the number of particles in the universe. Inevitably, you sample to look at the behavior of wider initial patterns.
You either sample random patterns to see how wider ones typically behave, or you sample contrived ones you have generated through some more simplified procedure. In the latter case, however, you will have no idea whether the results you see are representative of the zillions of otherwise similar cases that do not have the simplified initial structure you provided them.
In NKS Explorer, you can conduct the experiments yourself and try different initial conditions. The random number seed is one of the fields you can change, and is fully displayed. The procedure used to generate the initial condition from that seed is also fully specified in Mathematica - it is based on rule 30. Provide your own copy of the program the same seed, and naturally it gives the same initial condition.
There are 133 index entries about randomness in the NKS book. Notes about it are found from page 967 to 977 and again on page 1067-6, covering the history of definitions of it, practical means used to generate it and how they actually work, and its use in models. It is a broad and interesting subject.
Posted by: Gershom Zajicek M.D.
Nature presents itself to us as change. We distinguish between two kinds of change: Change which is explained by a theory, and unexplained change, which we call Randomness. Randomness is not an inherent (ontological) property of nature. It is our way to describe it.
In linear models randomness is represented by a separate term, called error, which has to be minimized. Here R-square expresses the adequacy of a linear model. In other words, R-square stands for the fraction of the observations explained by the theory , and 1-Rsquare stands for randomness or error.
Neural Nets start from a random initial state and converge to a (non random) solution. Thus Neural Nets are processes (algorithms) which eliminate randomness. On the other hand, chaotic CA systems lack this property. If they start from a random initial state they will propagate randomness, and even amplify it. Above all, such models can not be reproduced, since being sensitive to initial conditions. For this reason their initial states ought to be non random and uniquely specified.
Life never starts from randomness. Two cells, the sperm and the ovum unite to form a (non random) zygote, which evolves into what we are. This is why Life and Randomness is a medical oxymoron, and a meaningful model of Life has to exclude Randomness.
More on this topic in my site: http://www.what-is-cancer.com/papers/ca/ca01.htm
G. Zajicek gzajicek@what-is-cancer.com
Posted by: Jason Cawley
Of course they can be reproduced. Start them from the same exact initial condition - e.g. by specifying the same random number seed - and you get the exact same pattern every time.
As for whether there is randomness in the sense of uncaused, probabilistic underlying events, it is an open philosophic and physical theory question. The NKS view is that underlying deterministic systems can produce all the apparent randomness we see, without requiring underlying stochastic processes. So far as that is your main point - that you'd like to see more use of deterministic simple program models rather than stochastic, statistical ones, particularly in biology - fine I agree with you. That is part of the point of NKS.
But NKS still speaks of randomness, not where determinism is lacking but where computational reducibility is lacking. The randomness driving the economy of Las Vegas does not depend on whether underlying physical theory is eventually grounded in a deterministic NKS type model, or a stochastic QM type model. Either way, there is phenomenal randomness, for practical purposes.
One can define the terms in various ways. It seems to me the meaning ascribed to "randomness" should not beg relevant open questions, either about what "can" exist or about what sort of model does account for phenomena we see. It should also stay close enough to ordinary usage, that what average speakers refer to as random in everyday life, are still called random.
In common speech, we call things random when our ordinary methods of analysis cannot "crack" them or exhaustively reduce their behavior to a simplified structure. We call, for instance, the digits of pi random, when they are a fully specified constant of nature that cannot be otherwise, which we can determine by any of a number of different, exact mathematical formulas.
We don't mean that we can't know the millioneth digit of pi. We just mean before we calculate it, we have no confidence it will be (say) "4" rather than "7". We wouldn't accept a bet for one rather than the other offering only 2:1 odds, if we haven't calculated the right answer beforehand. We would if the odds were 50:1 - provided the amount at stake was livable if we lost.
Following your link one question you had is whether CAs can model systems like flames, which have direction and structure as well as seemingly chaotic elements. Look at the java applet on the CA FAQ page linked below. It is using a CA to generate those images, though I don't know the underlying details enough to say whether it uses any explicit randomizing steps or not. I hope it is of some interest.
http://cafaq.com/bibliography/index.php
Posted by: Gershom Zajicek M.D.
We ought to distinguish between Random and Pseudo Random initial conditions. The first obviously cannot be reproduced. Pseudo Random initial conditions meet my requirements provided that one specifies how they were generated. I don’t recall that in his examples Wolfram specifies how the pseudo random initial conditions were generated.
While disliking Randomness, Pseudo Randomness is closer to my heart since I know how it is generated. While Randomness and CA is an oxymoron, pseudo randomness and CA, is not. My point is that in the world of CA, Randomness is meaningless, and should not be used. The same applies to biology and medicine.
I agree with you that one can define terms in various ways. However in medicine such terms have profound implication on therapy and may harm the patient. This issue is dealt with in my site under the heading: A New Kind of Medicine. (you might abbreviate it as NKM) http://www.what-is-cancer.com/paper...wmedicine0.html
Thanks for the link depicting CA flames. I would appreciate if you find out how the program looks like, particularly it’s CA portion.
G. Zajicek gzajicek@what-is-cancer.com
Posted by: Gershom Zajicek M.D.
The Central Limit Theorem (CLT) states, that any sum of many independent identically distributed random variables is approximately normally distributed. http://www.worldhistory.com/wiki/C/...mit-theorem.htm
For instance if dice are rolled repeatedly, the frequency distribution will resemble more and more the Normal Distribution. You may check it experimentally at the following site:
http://www.stat.sc.edu/~west/javahtml/CLT.html
The CLT is the hallmark of Randomness, which underlies many statistical procedures. Does it apply also to the world of CA? You may create a pseudorandom set of initial conditions, and let the CA evolve. When small they may obey the CLT, yet when larger they do not. More precisely, when the distance between the CA is such that they remain isolated, CLT works. When overlapping, it fails, and in chaotic CA it is useless.
CLT works only in linear systems whose elements do not interact and are isolated. In other words CLT thrives on Randomness which CA lack. Farewell to linear statistics.
Life also lacks the two prerequisites of CLT. Neither are its elements isolated nor independent. Unfortunately, epidemiologists ignore this common wisdom and base their statistics on the CLT. They take the human being and simplify his attributes until the CLT requirements are met. Yet this simplified creature is a far cry from that which was created in Genesis. Epidemiology thus nurtures medically induced diseases known as Iatrogenesis. By now you might understand why I dislike randomness.
To learn more on the distortions of medical statistics visit my site at:
http://www.what-is-cancer.com/paper...tsgenetics.html
G. Zajicek gzajicek@what-is-cancer.com
Posted by: Gershom Zajicek M.D.
The Random Walk is another manifestation of the Randomness concept. It is a stochastic process like Brownian motion, and serves among other to describe the stock market and exchange rates. The Efficient Market Theory says that the prices of many financial assets, such as shares, follow a random walk.
Random walk may explain why the stock market won’t make you rich. However it fails to explain why some brokers got rich. No wonder, since the stock market is more than a sum of random walks. It is a living system, and as such cannot be modeled by random walks. Economists don’t like this idea because they do not know how to model living systems. They reduce and simplify the humans which make the stock market tick, to faceless points, until they meet the prerequisites of random walks.
Yet all these amazing guys who made a fortune, are not at all faceless as economists suggest. They are simply creative, and since economists do not know how to model creativity, they ignore it. It seems as if CA might be a good tool for modeling creativity. An example of what is meant is given in my site: http://www.what-is-cancer.com/papers/ca/ca3.htm
I wonder whether a CA model of the stock market would help me to reduce my overdraft.
G. Zajicek gzajicek@what-is-cancer.com
Posted by: Gershom Zajicek M.D.
Nature presents itself to us as change. We may distinguish between rapid change, like a torrent, and a slow change, which is called variation. Prior to Darwin, variation was regarded as God’s creation. Some even believed that God whose nature is incomprehensible, presents himself to us as variation.
In 1859, Darwin published “The Origin of Species” in which he explained variation in a novel way. Variation evolves. He distinguished between three kinds of variation:
1. Spontaneous, known today as genetic mutation, or crossover.
2. The outcome of competition between species.
3. Resulting from the selection of entities which will survive by the environment, known as “Survival of the Fittest.”
Evolution is a random process. Its objects are powerless to alter their fate. They are shuffled in the hyperspace representing nature like dice. Yet life is more than that! It is creative, exclaimed Henri Bergson in his book “Creative Evolution”. http://www.what-is-cancer.com/papers/Bergson.html
He was ignored as an esoteric Vitalist. Today Darwin’s theory gained the status of a religion: “Nothing in Biology makes sense except in the Light of Evolution” said Theodosius Dobzhansky. Modern Darwinists ignore that there may be other more sophisticated ways to model evolving variation.
The crudeness of Darwin’s model is evident in Genetic Algorithms (GA) which apply it for classifying and generating various solutions,. They manipulate their objects in the same way as Darwinists would suggest. Despite some impressive achievements, GA hardly ever generalize. Above all they are not creative.
They better be called Creationistic GA, since their proper function requires a programmer god (demiurge), whose task is to select proper fitness spaces, define fitness measures, and crossover modes. GA illustrate the major weakness of Darwin’s theory, it is based on Randomness which by its very nature cannot be creative.
I dislike Darwinism for two main reasons: 1. Social Darwinism promotes discrimination, and 2. Medicine applies Darwinism to describe cancer progression. As cancer evolves, it becomes fitter than its host (the patient), and gradually destroys him . Yet Cancer is more than that! It is a creative process operating in a creative host. More on cancer and host creativity in my site: http://www.what-is-cancer.com
G. Zajicek e-mail gzajicek@what-is-cancer.com
Posted by: Angelo Pesce
I've read your post on ANKoS forum. I think you have misunderstood randomness here. Random doesn't mean casual.
"However, in Medicine (like in Love) nothing is really random."
In fact nothing is completely random. That's why probability theory has not only uniform variables but all kinds of distributions, and that's why two different random processes can be correlated or not. I have a certain probability of getting in love, but that probability can be higher if I meet the right girl P(in love|right girl). It's a over simplification to say that random in medicine means "without any rule". In fact, Bayesian modelled diagnosis tools perform quite well, in some cases better than the human doctors that instructed it.
"Nature presents itself to us as change. We distinguish between two kinds of change: Change which is explained by a theory, and unexplained change, which we call Randomness. Randomness is not an inherent (ontological) property of nature. It is our way to describe it."
Randomness is implicit in nature. Quantum physics and the Heisenberg's indetermination principle say that.
"Neural Nets start from a random initial state and converge to a (non random) solution. Thus Neural Nets are processes (algorithms) which eliminate randomness."
Neural nets are usually deterministic you're right (mostly). But what does it mean? They still deal with randomness. The probability theory rules that we use to manipulate random variables aren't random and so? Tools can be random or deterministic, this says nothing. Neural networks are strongly based on probability theory, in fact they are derived from Bayesian classifiers. Randomness does converge, every randomized algorithm for example converges (otherwise we couldn't get d a solution) and they are fundamental in computer science. The CLT say something on that too. But this is not an argument against randomness! It just says that random does not mean that we can't get results from it, and that random doesn't mean casual, inpredictable.
"Life never starts from randomness. Two cells, the sperm and the ovum unite to form a (non random) zygote, which evolves into what we are. This is why Life and Randomness is a medical oxymoron, and a meaningful model of Life has to exclude Randomness."
??? Yes when the sperm and the ovum met they form a zygote. And so? Do they always met? No! They met with some random distribution. By the way without randomness the darwinian evolution simply does not work, so it's lucky that we have randomness all the way down :D
"Life also lacks the two prerequisites of CLT. Neither are its elements isolated nor independent. Unfortunately, epidemiologists ignore this common wisdom and base their statistics on the CLT. They take the human being and simplify his attributes until the CLT requirements are met. Yet this simplified creature is a far cry from that which was created in Genesis. Epidemiology thus nurtures medically induced diseases known as Iatrogenesis. By now you might understand why I dislike randomness."
Sometimes you can misuse a tool and what will that say? That the tool itself is wrong? No maybe it's wrong in that model, maybe the model is oversimplified but that's something that you'll find everywhere in science, we always make simplifications, with random processes and without. Determinism that you advocate is no better. Equations are not more powerful than random models, they are usually worse. Chaotic system could be but it's hard to say. Even Wolfram that was wrote a big book saying many things that where known for decades (he is not the only one, or the first, or the main, CA researcher, and CA are only a subset of all the chaotic models we could use) hasn't found a good way to use them to solve some kind of scientific problem as far as I know. He haven't applied them in the real world, they're just toys, interesting, unoriginal toys. Not a 'new kind of science'. Not even a 'new kind of model' as the model was already widely known.
"The Random Walk is another manifestation of the Randomness concept. It is a stochastic process like Brownian motion, and serves among other to describe the stock market and exchange rates. The Efficient Market Theory says that the prices of many financial assets, such as shares, follow a random walk."
See the reply above... if a model doesn't fit a problem that doesn't make the underlying framework bad. We should only elaborate a more complex model. That more complex model could be random or non random, it depends but that doesn't say anything about how good are random models in general. The fact that they are so widely used, that they are so successful and that there aren't other models in many fields should tell you that they shouldn't be so bad after all... If even with all those simplifications they manage to make good predictions, that means that there is some inherent randomness, who knows what we can make with the same framework and more accurate models!
"The crudeness of Darwin’s model is evident in Genetic Algorithms (GA) which apply it for classifying and generating various solutions,. They manipulate their objects in the same way as Darwinists would suggest. Despite some impressive achievements, GA hardly ever generalize. Above all they are not creative."
Eh!!! GA do generalize, GA are global optimizators, GA are creative! And if we don't use GA we use other random processes to solve global optimization problems, not deterministic ones! There's no useful deterministic global optimization procedure (except maybe tabu search). All the deterministic ones are local, they converge to a local minimum and fail to find a global one. We should be happy that life is dominated by the Darwinian process, otherwise we could fail in one of those local minimums and never evolve further.
"I dislike Darwinism for two main reasons: 1. Social Darwinism promotes discrimination, and 2. Medicine applies Darwinism to describe cancer progression. As cancer evolves, it becomes fitter than its host (the patient), and gradually destroys him . Yet Cancer is more than that! It is a creative process operating in a creative host."
Wrong, wrong, wrong, WRONG. Again and again the same argument. You dislike something because you find that it fails sometimes, in a particular contest (I don't know how good are Social Darwinism or Darwinian cancer evolution, I assume that they are bad, I trust you). If someone writes a bad model using linear equations would you say that linear equations are bad?
Posted by: Gershom Zajicek M.D.
Thank you for your response. Please remember that the discussion is essentially philosophical. The question is whether Randomness exists as such in (biological) Nature. I claim that it does not. This concept is applied by us for describing (understanding) Nature. Randomness exists solely in the eye of the beholder.
You have to distinguish between reality and the tools we apply to study it. To my understanding, traditional statistical tools, which you mentioned, fail in (non trivial) CA models. Therefore, if we wish to model life with CA, we have to abandon this concept. In the CA universe, Randomness is meaningless. Medicine enters a new era in which tools based on Randomness will have to be replaced with better ones.
By the way I really don’t dislike randomness, I simply ignore it. I mentioned “disliking” only to provoke you. After all, there might be a take home lesson even for you. If you happen to be treated by a doctor who applies randomness, you might ask another one for a second opinion. This is the main message of “The New Kind of Medicine” described in my site:
http://www.what-is-cancer.com/paper...wmedicine0.html
G. Zajicek gzajicek@what-is-cancer.com
Posted by: Angelo Pesce
Randomness can or can not exist in nature. I don't think we'll ever know. We are limited in what we can know about reality by our senses. We cannot know something that we haven't created, we never will (at least not if we don't find some recursion at certain point) because there will always be something more subtle or too big for us to measure. And when we can't measure the state of a thing, we don't have even to ask if there's some inherent randomness in it, it will be unknowable for us without probability. Even in probability concepts do not apply to CA (as they do not apply to many other things) when we want to apply CA to nature we have to do some approximation or we have to reason in a probabilitic way. So there's no point in asking ourselves if radomness is or isn't part of the nature, what we can't know should be modelled as a probability.
By the way you haven't posed a 'philosophical' question, you raised pratical, actual arguments against the use of probability as a modelling tool. I answered those statements.
Posted by: Gershom Zajicek M.D.
You obviously may use any tool for any kind of model, yet when choosing CA as your model you are somewhat limited. Regard modeling as a game. You start with certain rules, and play. The rules of the “CA game”, and Randomness, don’t go together. In CA the present state determines what the next state will be, and in random processes the present state has no effect on the next one. Either you stick to the CA rules, and keep away from using Randomness, or you include Randomness in the “CA game”, whereupon it ceases being a “CA game”. In other words, no CA rule generates Randomness, and vice versa. Inclusion of Randomness in CA models leads to a contradiction.
In my opening statement I wrote: “Cellular automata (CA) provide simple models for evaluating interesting philosophical questions. Here is a simple teaser . . .” I use CA to illustrate a fundamental property of Life. Each state depends on the previous one. Since statistical tools, like the Central Limit Theorem, or Random Walk require that the states of a process be independent from each other, they are inadequate for studying Life (and CA). New tools have to be invented.
More philosophical teasers in my site: http://www.what-is-cancer.com/papers/ca/ca0.htm
G. Zajicek e-mail gzajicek@what-is-cancer.com
Posted by: Angelo Pesce
Of course CA are a model and of course they're not probabilistic. They are useful and they model many interesting phenomenons. I don't argue (and haven't argued) this. But what does this tell to us about randomness and nature? You made some strong claims about that, and I replied to those.
"Since statistical tools, like the Central Limit Theorem, or Random Walk require that the states of a process be independent from each other, they are inadequate for studying Life (and CA). New tools have to be invented." Some statistical tools require independancy. Some others do NOT. By the way the fact that some tools are or aren't good doesn't tell us anything about randomness and nature.
Last but not least: "Inclusion of Randomness in CA models leads to a contradiction." LOL! Try to search google about "probabilistic cellular automata"... The fact that Wolfram doesn't mention them into his book does not mean that they don't exist! Wolfram has only made some (too) strong claims on CA, he hasn't invented them.
Posted by: Gershom Zajicek M.D.
The concept of entropy was introduced in 1865 by Rudolf Clausius According to the second law of thermodynamics the total entropy of a thermally isolated system can never decrease. In 1877, Boltzmann defined entropy as a function of the possible microstates in a system. It is a measure of the system’s disorder. In this context the second law of thermodynamics states that the disorder in an isolated system tends to increase.
Which caught the imagination of doom prophets. Since the universe is an expanding closed system, its total disorder increases. Ultimately it will reach a state in which its thermal energy will be homogenously distributed, and die a “heat death”.
Might a rising entropy account also for human death? Obviously not, since the organism is an open dissipative system. In his book “What is Life” Erwin Schrödinger suggested that the entropy of our organism remains low since it feeds on negentropy.
Following Boltzmann’s model, Claude E. Shannon defined entropy as a measure of uncertainty. In the state of randomness, entropy and uncertainty are maximal. Which brings us back to a statement made here in a previous section, that Randomness is ignorance.
Entropy is meaningless when applied to CA for two reasons. 1. In statistical thermodynamics, entropy varies between 0 and 1. Since CA and Randomness are mutually exclusive, CA entropy will never vanish (be zero). Unlike in Information theory or Statistical Thermodynamics, CA entropy is not defined over the entire [0 , 1] interval. 2. CA may be regarded as an open system. An isolated string of numbers will never change by itself. It has to be driven to its next state by a processor. While the string may be regarded as isolated, together with the processor it is an open system in which entropy is meaningless.
More on “unpleasant” properties of CA: http://www.what-is-cancer.com/papers/ca/ca01.htm
Posted by: Angelo Pesce
Mhm I can't reply your last post, but it was out of topic in my opinion. I never argued about the properties of CA. I argued about randomness and nature (the lack of the first in the second). All the other things could be right, but what do they tell to us? What does your last post tell? That CA lacks entropy, ok take that for granted, what so? It is true that randomness is ignorance, but is ignorance something that we can eliminate when we talk about nature (science) or not? I don't think so, I don't think that we could ever know a world that we haven't made down its inner workings. And there are some physical evidence that this is true too, that we can't rely on deterministic tools to study the inner workings of the matter. So the fact that CA lacks randomness is not a good thing 'science-wise' (by the way, as I told you this is NOT TRUE, there are some non-deterministic versions of CA). I don't believe that CA can ever be a new kind of science, to prove that you shouldn't try with so weak philosophical arguments, let's begin to see what they can do in some real 'production' environments...
Posted by: Gershom Zajicek M.D.
The issue at stake is whether a model that one applies is consistent. To my mind constructing or analyzing CA models with tools based on randomness leads to conflicting conclusions. This precisely is happening daily in Medicine, and I use CA to illustrate what I mean. For instance, most statements by medical epidemiologists suffer from this inconsistency. You can’t trust most medical statistics.
More on this topic in http://www.what-is-cancer.com/papers/bewareofgene.html
Posted by: Angelo Pesce
Yes, but I didn't reply you on the point of using or not randomness on CAs. This is possible, and it's not a bad idea for me, but this is not what I wanted to say. I replied you about the usefullness of randomness and about the random aspect of the nature.
Medical statistics can't be trusted just because they are often made by non-statisticians, but seriously done ones are useful, some are VERY useful (for example the Bayesian Inference). Also discardings statistics in medicine would mean to discard almost all modern medicine. I've read a couple of your papers. They are really disappointing to me, you are telling the false in most of them, oversimplifying many things, you 'tell your truths' but you fail to prove them. For example, the 'beware of the gene' paper wants to make us believe that a model of diseases entirely based on genetic dynamics is wrong. But *of course it is*! I don't think that anyone believes the contrary, and this doesn't make the g.d. approach wrong. It's only a part of the whole story, of course, as human body is too complex to be explored as a whole we usually analize only some aspects and then combine them to have the full picture. Gene dynamics are fundamental, but of course you're a fool if you try to analyse body dynamics with only their aid, we don't know much about g.d. theirselves, how he can pretend to explain all the diseases by looking at only the smaaaall portions of g.d. we know? But we know they are useful, if an individual has some genetic variations then it's more probable that he will have some diseases or some others. More probable, not sure!!!
But it's when you talk about CA that you make the biggest errors in my opinion. I found pages like http://www.what-is-cancer.com/papers/ca/ca4.htm or http://www.what-is-cancer.com/papers/ca/ca6.htm to be completelly useless. What are you doing here? You're showing some pictures of CA and saying that under strange assumptions they resemble some aspect of diseases. How cool! And what should this supposed to be? The same pictures could resemble 1000 other things. Trying to find some concepts in CA like you do is not SCIENCE, it's NUMEROLOGY.
Posted by: Gershom Zajicek M.D.
Hi Angelo,
Now that we know each other for some ASCII lines, allow me to be somewhat personal. With your permission I shall apply a concept favored by the philosopher Imanuel Kant, the Thing in Itself (Das Ding an Sich). Since we cannot comprehend the Thing in Itself we do not know whether it is random or not. All my arguments center about our comprehension of the Thing in Itself. As you have noticed I am an amateur philosopher (but a good physician), and use the narrative to convey my ideas. Like the philosopher Epictetus, I am not interested in the truth as such, but what people think of it.
You may regard my site as CA-comix illustrating interesting ideas: http://www.what-is-cancer.com/papers/ca/ca01.htm
All the best
Gershom
Posted by: Angelo Pesce
I don't doubt that you're a good physician. About philosophy, it's an hard matter and I don't think that we can give a solution to those problems, I just gave my 5c. About science, I don't know if you're a good scientist, maybe the text on your site should be interpreted more on the philosophical side than on the pratical, scientifical one. But even if that's the case I still think that you oversimplify many things on your site. You seem to approach CA for what they imply philosophically and in fact they can tell us something about reality. But they're not the only tool, they're not even the main tool and I doubt that it's possible to build a new science on them, and I doubt that it's possible to make a science without probability.
Posted by: Vasile Gheorghiu
We cannot invoke arguments such as Kant's "Das Ding an Sich" because, in the long run, such of arguments are useless. The concept of the thing in itself ultimately states that we cannot know the world how really is, we can know only its appeareances(phenomena). But one of the main metaphysical assumption of the science and of Wolfram's too is: we can achieve knowledge about our world through our Reason.
The real philosophical problems in your discussion is: the world is inside or outside us ? There is something we call Reality which exists independent of our Reason or that Reality is only a projection of our scientifical models in use ?
Two consequences of these main outlooks are the separation of philosophers into two principal groups:
the first one(the positivists, Searle etc.) believes that "an objective reality" really exists and the science "discover" it step by step by its own procedures. These people strongly believe in objectivity of science, in the aristotelian theory of truth as correspondence between facts and statements and in values like progress. The other group(Putnam, Davidson, Rorty, Derrida etc.) says that objectivity is not really important because in fact we are using scientifical models. These guys believe in the theory of truth as coherence between opinions. For them reality is not discovered but created. All we have to do is to create functional scientifical models. Science is the best way in modelling our reality.
So...it is not important if randomness really exists, we cannot prove neither existence or non-existence of randomness as we can't find reasonable arguments to prove the existence of the thing in itself. This is a death viewpoint and we have to drop it. Much more important is how we could use these concepts and apply them for people sake even they are real or not. I am not agree with the opinion that CA's tell us something about nature or not, much more important is their social praxis. In what measure these models are useful for people ?
I don't know if cellular automata are real "laws of nature" or not but I am sure they could give us a verry different perspective on the world(as calculus, computer, network,) and I analyze this. I think that philosophy has no influence on science.
Posted by: Gershom Zajicek M.D.
I learned from Kant that metaphysics is not something existing out there. It is rooted in us, guides our reasoning, and may be applied for examining inconsistencies like the oxymoron mentioned above.
http://www.what-is-cancer.com/papers/ca/ca01.htm
Posted by: Vasile Gheorghiu
If we analyze this concept in an analytical manner we can easily see its inconsistencies. "Thing in Itself" is only a mental posibility of our mind.
My reproach was connected to this kind of argument. You said that in NKS terms [a CA has a definite rule that's why it is not random] we cannot speak about real Randomnes but Wolfram does.
For Wolfram something is random when we cannot find any regularities which means that "we cannot find a shorter description"[NKS, p.552]. This process in closely related to our perception and analysis methods. If we make use of the arguments like "Das Ding an sich" we'll never know if there is real Randomness or not because we are not gods. We need a divine eye to see if things that seems random are random indeed or not. Wolfram realized that we are humans(IoI) and purposed a human criterion to detect Randomness. His criterion is more practical: our perception and analysis powers. Personally I think is a very decent criterion even is disputable in its epistemic aspects.
To answer to the question of existing or non-existing of real Randomness in nature is an abuse of Reason. We cannot prove such of statement neither its opposite and we cannot use it as an argument. To invoke this kind of sophism is an abuse in thinking. We have to search for useful and reasonable concepts and Wolfram's concept of Randomness is pretty reasonable and is a very practical one.
Immanuel Kant himself had found that there is no posibility to know the things in itselves only their appearences(phenomena). Why should we believe that our nowadays science discovers "things in itselves" ?; and if not, then are not sciences ?
I don't think that the definition of Randomness is the most important for NKS. Randomness is just a concept which we have to treat it as a convention as Wolfram did. I believe that problem of Consciousness is more complicated that Randomness in NKS.
Posted by: Gershom Zajicek M.D.
Randomness (noise) has an unpleasant mathematical property. By definition, it cannot be generated by a program, otherwise it would be called pseudo-randomness. In other words there does not exist a transformation that generates noise. Which distinguishes it from other mathematical objects which may be generated by a transformation.
Randomness reminds of another_object with unpleasant mathematical_properties, the zero. One is not allowed to divide by it._0/0 is indeterminate, and 1/0 is undefined.
Might Randomness be the “zero” of complexity? Since no transformation generates noise, what is Noise/Noise?
Shouldn’t we shy away from Randomness_when breading CA?
http://www.what-is-cancer.com/papers/ca/ca0.htm
Posted by: Karl Smith
Originally posted by Gershom Zajicek M.D.
Randomness (noise) has an unpleasant mathematical property. By definition, it cannot be generated by a program, otherwise it would be called pseudo-randomness.
In other words there does not exist a transformation from noise to noise. Which distinguishes it from other mathematical objects which may be transformed (are transformable).
Randomness reminds of another object with unpleasant mathematical properties, the zero. One is not allowed to divide by it. 0/0 is indeterminate, and 1/0 is undefined.
Might Randomness be the “zero” of complexity? Since no transformation generates noise, Noise/Noise is indeterminate, and 1/ Noise is undefined.
Shouldn’t we shy away from Randomness when breading CA?
http://www.what-is-cancer.com/papers/ca/ca0.htm
Randomness is most certainly transformable in the sense that I can take one random variable and transform it into another random variable with different properties.
Furthermore there is really no magic to randomness. You have to break out this thinking that you are dealing with "reality" whatever that might be.
You are dealing with observables. If you have a variable and you don't know what it is now but you will know what it is later, then its a random variable. Pure and simple.
It doesn't matter in the slightest whether the process that created the variable is "truly random" or not, whatever that might mean. All that matters is whether or not you as the observer know or can know its value prior to some time T.
When I say Zt is a psuedo-random variable all I mean is that there exists an observer Adam who does not know the value of Zt at time T. However, there can exist an observer Bill who does know the value at time T because Bill knows the variable came from Newton's Method applied to a non-zero root function or whatever other random simulator I have.
If Bill could not in theory exist then the variable would be random.
Posted by: Gershom Zajicek M.D.
Randomness is a property of a set (collective) and not of a single number or a variable. You may call your variable random and I may regard it as non-random, and we shall both be right since talking about a single number. You don’t have a randomness test for a single variable. Even when programming you don’t have the option to define a variable as random. It might be an integer, a real, or complex, but never random. Even the Random[] function is not random. It is pseudo-random!
Randomness (noise) is not transformable!
By the way, who is talking about reality? I regard mathematics as a language, and its models as narratives, with which you can spread illusions and just so stories, like the notion that your variable which you just conjured is random.
http://www.what-is-cancer.com/papers/ca/ca0.htm
Posted by: Karl Smith
Originally posted by Gershom Zajicek M.D.
Randomness is a property of a set (collective) and not of a single number or a variable. You may call your variable random and I may regard it as non-random, and we shall both be right since talking about a single number. You don’t have a randomness test for a single variable. Even when programming you don’t have the option to define a variable as random. It might be an integer, a real, or complex, but never random. Even the Random[] function is not random. It is pseudo-random!
Randomness (noise) is not transformable!
By the way, who is talking about reality? I regard mathematics as a language, and its models as narratives, with which you can spread illusions and just so stories, like the notion that your variable which you just conjured is random.
http://www.what-is-cancer.com/papers/ca/ca0.htm
Well in mathematics we talk a lot about random variables. We think of random variables as being drawn from a distribution. I am not sure if thats what you mean by random set.
However, the distribution is not "random" in the sense that I don't know what it is. I know what the Standard Normal distributiion is and its properties are completely deterministic.
If I take a draw from the Standard Normal I may not know what the value of that random variable is. I know certain properties of that variable because they are determined by the distribution. For example, the variable has an Expected Value of 0.
My point is that treating a modeled variable as random is not the same as saying that it was created by a process that is somehow "fundementally random."
You don't even have to believe in "fundemental randomness" to use the mathematics of random variables. Personally, I am not even sure that "fundementally random" is a valid statement, though I use random variables on a near daily basis.
Posted by: Gershom Zajicek M.D.
The random variable is a somewhat obscure object. Take for instance the definition in Wikipedia: “A random variable can be thought of as the numeric result of operating a non-deterministic mechanism or performing a non-deterministic experiment to generate a random result. For example, rolling a die and recording the outcome yields a random variable with range { 1, 2, 3, 4, 5, 6 }. Picking a random person and measuring their height yields another random variable.” http://en.wikipedia.org/wiki/Random_variable
You perform the random experiment and are told that there are two kinds of distribution, discrete and continuous. You prefer the continuous and become confronted with the central limit theorem (CLT) which states that whenever a random sample is taken from any distribution with a mean and variance, then the sample mean will be approximately normally distributed. The larger the sample size, the better the approximation to the normal.
You satisfy yourself that it works for dice, coins and roulette. Then you start measuring the height of randomly selected people and become somewhat uneasy. The distribution is skewed. You continue sampling and it remains so for ever. Height is obviously randomly distributed, and you chose the persons randomly. What went wrong?
In fact, in medicine all observed randomly distributed variables are skewed, and nothing is distributed normally! Nevertheless medicine ignores the skew, attributes it to chance, and regards all its phenomena as normally distributed. Which introduces bias in all its statistical (epidemiological) statements.
http://www.what-is-cancer.com/papers/bewareofgene.html
http://www.what-is-cancer.com/paper...icmedicine.html
But the skew is real. Why not say that random variables may have two kinds of distribution, non-skewed, and skewed ? This is a mathematical blasphemy, since it undermines the generality of the CLT. By analogy with geometry you might say that there are at least two kinds of Randomness: So called “Euclidean-Normal”, and “Non-Euclidean-Skewed”. Both with equal rights!
With all these heretic thoughts rushing through my mind I turned to Wolfram’s book, and lo and behold this Gaussian Randomness is everywhere. However, in the world of CA randomness is meaningless, and even if you regard CA as random variables, they disobey the CLT. CA are “Non-Euclidean-Skewed”.
I decided therefore to present this issue from a somewhat unusual perspective, e.g., Oxymoron, Randomness is a zero of complexity, etc. It seems to me that in order to really grasp complexity you have to get used to the notion of many kinds of randomness, whatever it means.
http://www.what-is-cancer.com/papers/ca/ca0.htm
Posted by: Karl Smith
But the skew is real. Why not say that random variables may have two kinds of distribution, non-skewed, and skewed ? This is a mathematical blasphemy, since it undermines the generality of the CLT.
There is nothing at all blasphemous about this. Indeed "skew" is measurable statistic. For a distribution with a zero mean I think it is just the third moment.
About the distribution of heights. There is nothing in the CLT that says that height is normally distributed. It simply says that if our height measurements are iid(Independent and Indentically Distributed) then the means of the samples of height will be normally distributed.
Now are our measurements iid? No, especially not if our sampling technique involves getting people who are probably related, exposed to the same nutrition, etc.
However, if we take a "pseudo"-random generator and cross that into our population then we have a iid random variable. Why?
Because the process that generated the random number is uncorrelated with the determinates of height in our population. So even if both random variables have some sort of "bias", using that term loosly, it will be cancelled out in the cross.
I don't know about Medicine but in most stastical applications assumptions about normality are not taken lightly. There is a lot of work that goes into getting statistics that are unbiased or at least consistent under different error processes.
Posted by: Gershom Zajicek M.D.
With heights it’s not so simple. Even if you sample the heights with a pseudo random generator and make the samples iid (Independent and Identically Distributed), the means of the samples will not be normally distributed. You have to deal with (many) non random outliers at one side of the mean. They will not vanish with additional sampling. These will make the distributions of the mean-heights skewed, while the normal distribution is symmetric.
You may try it on samples of non symetric CA with different rules.
The normal distribution model is simply inadequate to deal with heights.
http://www.what-is-cancer.com/papers/ca/ca0.htm
Posted by: Karl Smith
I'd like to see that. Do you have any data? I might try scouring the web for some.
Posted by: Gershom Zajicek M.D.
I doubt that you will find an adequate data set of heights, or other biological variables.
You might examine this issue on Wolfram’s class-4 CA.
1. Generate a set of class-4 CA.
2. Iterate one step.
3. As long as CA are not chaotic go to 2.
4. Generate “iid” and sample ‘n’ CA. Compute the mean and store it.
5. Iterate one step.
7. Compute the mean of the set of means and store it.
8. go to 4
Each new mean will oscillate chaotically. Farewell to the Central Limit Theorem.
Statistics started as an experimental science, and gradually were formulated analytically. NKS and its CA, introduce a new era in statistical experimentation.
http://www.what-is-cancer.com/papers/ca/ca0.htm
Posted by: Gershom Zajicek M.D.
In a previous section I mentioned that noise (randomness) cannot begenerated by a transformation. http://forum.wolframscience.com/sho...15&pagenumber=2
However noise has an additional property which might be useful for evaluating complexity. Noise * Noise = Noise. Which is also the property of the digit one. 1 * 1 = 1;
Whenever we multiply noise by itself it does not become more complex. Thus noise cannot generate complexity. We may therefore regard noise as a unit of complexity. Noise has an additional property. Its components are independent from each other, or uncorrelated. Let r be the correlation coefficient of an auto-correlation function of a set of random numbers. By definition r[noise] = 0.
http://www.itl.nist.gov/div898/hand...ion3/eda35c.htm
One may generate complexity by making numbers dependent on each other. Dependency is proportional to correlation. We may thus express complexity of a set by correlating it with noise. In this context ‘r’ becomes a complexity measure.
What happens if we add (accumulate) noise? Still noise + noise = noise. No complexity is gained (r = 0). Might this measure improve the classification of CA complexity?
http://www.what-is-cancer.com/papers/ca/ca0.htm
Posted by: Philip Ronald Dutton
If you take noise and mirror it then you have something that is not pure noise.
For example, geometrically speaking (of a 2d rectangle filled with random noise) just mirror the rectangle about the far end (axis)... now you have one rectangle placed right next to the other with an axis of symmetry down the two touching edges. Now with the symmetry it is no longer noise.... (mind you i am thinking loosly, abstractly, and artistically).
The symmetry adds some kind of complexity (because now there is relation due to the symmetry axis) wouldn't you say?
Posted by: Gershom Zajicek M.D.
Your example consists of three steps:
1. You take (infinite) noise and create a demarcation. Result: The new structure is more complex than just noise.
2. You take a rectangle full of noise and mirror it. Result: A new rectangle full of noise. The same complexity as before.
3. You place the two rectangles side by side. Result: The new system is more complex, since you got two rectangles.
Once you add structure to noise you can make it more complex. Border is a structure. By placing noise within a rectangle you created a demarcation which makes the new structure more complex than just noise.
http://www.what-is-cancer.com/paper...tscomputer.html
Posted by: Ray Donald Pratt
Noise might lack predictable frequencies, but not necessarily texture. For example, the static of a radio while tuning it has a crackling texture of sputters and pops that changes as you turn the tuner. This noise often has as much "texture" as any coat of paint.
Thus, calling such sound "noise" in the sense of pure randomness is not entirely true, for it would otherwise possess no discernible texture if it were truly and entirely random.
When I play Keno, I find that shapes will continue to repeat themselves on the Keno board over many games -- blocks, lines, horseshoes, L's, scatter patterns, or whatever specific pattern has been showing up on the Keno board.
I usually have not been able to figure out exactly where and when the next pattern will show up, although I sometimes RUN to the ticket counter when I KNOW. But if I see blocks, I certainly don't play line patterns, or L patterns, etc., although I most often lose regardless.
Is the game of Keno truly random simply because it does not have the sort of statistical regularities that define nonrandom events? I don't think so, and I think that it might be worth someone's time and money to quantify and explore the statistical recurrence of visual patterns on the Keno board, i.e., the recurrence of geometric "texture."
I envision a day when I might know enough math and physics to deduce when and how the Keno balls might show up on a Keno board after watching a few games, but the recurring patterns on Keno boards already tells me that the 'combinatorial' texture stays the same over a great many games.
I see that same quality of recurrence of texture in a great many games, and I think it's a fundamental quality of any physical system where a fixed number of elements are subjected to a regularized process of shuffling. For example, I shocked myself in how often I was able to call the specific, 'non-probable' combinations that showed up as upsets in a couple of nationally-televised poker games after I watched the hands play out long enough -- and I don't play poker.
The patterns reveal themselves in Poker despite the rough washes and rough shuffling processes because that 'roughness' is itself a regularized texture.
I don't have a lot of faith in noise.
Very Respectfully,
Ray Donald Pratt
Posted by: Gershom Zajicek M.D.
By definition Randomness lacks any texture. Not every noise may be really random. When I use noise as synonym for randomness I mean random noise without texture. Nevertheless when observing this random noise you still may perceive a texture, because your mind projects texture on the observed.
Nature is not random. Randomness is an abstract term , like a point which also does not occur in nature. Any observed point when magnified turns into a blob. While randomness is useful in physics, in bio-medicine it has many drawbacks.
http://www.what-is-cancer.com/papers/ca/ca0.htm
When you play Keno and observe texture, the game may not be as random as claimed. In order to win you need a strategy, or better a model. Some renown mathematicians, known as quants, made it in Vegas and now they try their best in Wall Street.
http://www.tc.umn.edu/~upad0004/QuantFinance.pdf
Posted by: Ray Donald Pratt
Thank you, I did read the 'quants' article, and the medical link led to a list of contents regarding randomness that promises some good reading down the road.
In the article regarding the 'quants,' I saw the same sort of issues that come up regarding gambling, e.g., whether simple probability calculations capture the true cyclic opportunities and dangers in gambling games.
When I was 20 years old (I'm now a crusty 46), I worked for about 8 months as a Market Quotation Terminal Operator on the Options Trading Floor of the Pacific Stock Exchange. The job entailed standing among the traders at a given trading post and constantly listening for and entering (on a Quotron terminal) the highest current bids and the lowest current offers on the puts and calls for all the stock options being traded at that post. (As an aside, the job left me with a temporary ability to understand multiple conversations at the same time as an extension of what my job required: sorting out the highest bids and lowest offers among a crowd of shouting traders.)
It didn't take long for me to figure out that the value of the stocks and derivatives was a rather volatile mix of marketing hype, greed, gambling, and a lot of smoke and mirrors. And, believe me, most of the pressure-cooker characters in the room fit the picture.
My fear regarding investments in the stock market revolves around the United States baby boom of the '50's: specifically, I fear that retiring baby boomers will cash in on their investments and depress the market exactly when I, as a fellow retiring baby boomer, would most likely need to tap into the accrued value of my own investments for retirement.
A possible rosy scenario is that productivity will increase worldwide and that foreign capital will flow into our markets and offset the effects of the United States baby boomers cashing out of the market, and that may indeed happen, but the question is: "Do you want to bet your life savings on it?"
Gambling, on the other hand, offers the opportunity to study and beat the games now, although the long-term prospects may be just as 'iffy' as the stock market -- assuming that an advantage at casino gambling can even be had.
Of all the descriptions in the 'quant' article regarding a correct model for the stock market, Mandelbrot comes the closest to describing my actual experience with similar effects in gambling where most large wins accrue in relatively rare streaks.
That might seem dismissable as simple probabilities, but that would ignore how often it's possible to watch and follow the supposedly unknowable cycles occurring in a game.
Such an awareness of cycles might be dismissed as a simple mental projection on a random event, but that's the real challenge of gambling, investing, or the taking of any risk: separating your projected desires from what's truly in front of your eyes.
Again, thank you for the links.
Very Respectfully,
Ray Donald Pratt
Posted by: Gershom Zajicek M.D.
In a previous section we have realized that randomness cannot generate complexity. Creativity is somehow linked with complexity. It may be regarded as an unexpected rearrangement of complexity, or a creation of a novel structure. Since randomness cannot generate complexity it cannot be creative.
http://www.what-is-cancer.com/papers/ca/ca3.htm
Randomness does not exist as such in nature. It is applied by the exact sciences to understand nature and contributed to some important theories, like statistical thermodynamics. It fails however to account for creativity which is the hallmark of life. Take the theory of evolution, whose cornerstone is random variation. However, when observing the complexity of our brain, one starts wondering whether it really evolved by random events?
http://www.what-is-cancer.com/paper...ismDecline.html
The more you think about it the greater your doubts despite the fact that life had about ten billion years to evolve. Such doubts were raised by the philosopher Henri Bergson in his “Creative Evolution”. http://www.what-is-cancer.com/papers/Bergson.html Unfortunately this important treatise was dismissed by enlightened reductionists which still dominate biomedicine today.
Randomness can perturb a complex system to make it creative. By itself it is not creative.
Genetic Algorithms (GA) illustrate the inadequacy of Darwinism. Since applying randomness they are destined to approach their solutions asymptotically. GA hardly ever generalize, and above all they are not creative.
Creationism bans randomness altogether which makes it so appealing: “In the beginning of creation, when God made heaven and earth, the earth was without form and void, with darkness over the face of the abyss. . .” (Genesis). The abyss was not at all random. Neither was the formless earth. They served as initial condition for life.
I prefer another version of creationism: In the beginning there was a cell which arrived from outer space (panspermia). From then and on, life evolved by recreating itself and its own environment known as Gaia.
http://www.what-is-cancer.com/paper...erspective.html
Posted by: Gershom Zajicek M.D.
What we observe and perceive is change. We wonder weather this change has a cause, or not? The first kind of change we call deterministic and the other random. We tend to regard them as complementary. If it is random it does not have a cause. However, with cellular automata we can generate change which appears to be random and is nevertheless deterministic. This change is called pseudo-random. It is somewhat frustrating that we cannot distinguish between genuine and pseudo randomness. Pseudo random numbers meet all statistical requirements of randomness, and Mathematica software applies a cellular automaton to generate random change (numbers).
Life also presents itself to us as a change which seems to be random, yet differs from the above kinds of randomness. Since cells always emerge from cells (omnis cellula ex cellula) each cell inherits its complexity form its predecessor which includes also the change which seems to us random. Yet it is neither random nor pseudo-random. It is a change typical of life. It is somewhat frustrating that we cannot distinguish between the three kinds of change, randomness, pseudo randomness, and the change generated by life. There is however a profound difference between the change created by life and the other two. Life is creative, while the other two are not.
Heraclitus (500 B.C.) created a powerful metaphor for change. He said: ”You never step twice into the same river.” We, his humble followers, add: “You never meet twice the same individual.”
v. “The Streaming Organism”
http://www.what-is-cancer.com/paper...eamorganism.htm
Posted by: Gershom Zajicek M.D.
Nature is change. The nature of change always preoccupied humankind. Since change may be hazardous, Babylonians searched for signs associated with favorable and unfavorable change. The art of association is highlighted in Astrology.
Next, Aristotle said that any change has a cause. An idea which was more useful than the associative method of the Babylonians, since one could intervene in the chain of causes. Western religions preferred to deal with the first cause. Leonardo de Vinci on the other hand, showed that in order to build useful machines one ought to manipulate change.
Cause is central to Newton’s laws. It is a comforting concept which led Laplace to believe that the present state of the universe is the effect of its past and the cause of its future and this change is governed by eternal laws.
Then came Poincare and showed that Newton’s laws do not suffice to forecast the outcome of even three interacting bodies. The outcome is chaotic. Suddenly humankind was stripped of its optimistic belief in cause and effect. Here you have a change which obeys Newton’s laws and nevertheless is unpredictable.
Hitherto noise was the sole source of unpredictability, suddenly we are confronted with another one, chaos. In reality neither noise nor chaos exist as such in nature. Both are constructs for describing change. The role of noise is discussed in previous sections. Chaos is characterized by a sensitivity to initial conditions. If a change is insensitive to initial conditions it is not chaotic. Like the flying canon ball.
Nature is an ongoing process devoid of any initial conditions. How can we know if a change is chaotic? We can’t. Like noise, chaos makes little sense when applied to change associated with life.
We are back to square one. Our tool remains the Babylonian association between events and phenomena. You might wonder why all this fuss about the nature of change? Medicine is still enchanted with Laplace’s paradise and the consequences affect your daily life. What about smoking? Does it cause cancer? Or is it merely associated with cancer. Think of your genes. Some diseases are manifested by genetic changes. Do these changes (mutations) cause disease, or are they merely associated with a disease? It is the interpretation of change which today plagues medicine.
Cancer and metphysics
http://www.what-is-cancer.com/paper...physics200.html
New Kind of Medicine.
http://www.what-is-cancer.com/paper...wmedicine0.html
Posted by: Gershom Zajicek M.D.
Nature is neither complex nor simple
Nature is perceived by us as change. In order to survive we try to make change comprehensible, focusing on the beneficial and avoiding the risky. For this purpose we group change into positive and negative phenomena. Although Nature is perceived as complex and incomprehensible, grouping and classification makes it livable.
Complexity is a metaphor. We feel its meaning and are not able to define it. Any definition which concretizes this feeling is arbitrary. It’s like in object oriented programming. You have a superclass called complexity which contains attributes and methods. When you create a complexity object it inherits some of the features from the complexity metaphor (class), however it cannot inherit all its features since it is not uniquely defined.
Any complexity definition is therefore arbitrary, which applies also to class-4 in Wolfram’s book (p. 231). First we note that Wolfram’s complexity can be easily simplified. You generate a CA set which displays calss-4 complexity and apply the following transformation. For every state, sum up its elements, and you will get a number. In this way you may simplify any evolving CA in Wolfram’s book into a series of numbers.
This kind of reasoning fails when applied to life. You cannot transform or simplify any state because the states are not given. Any grouping of phenomena in an evolving living system into consecutive states is arbitrary and leads to inconsistencies. Take for instance age, which is also a metaphor. By stating that the age of your friend is 40y, you actually simplify the complex age metaphor and represent it by a number which results in the following inconsistency. You observe two individuals with the same age. One looks younger and the other older. Officially both age at the same rate, since each year they age by one year. However the older looking one ages somewhat faster than the young looking, and should be placed in an older group.
Chronological time does not capture real aging. It segments the complex aging process into arbitrary states and places in each individuals with different biological ages. In order to simplify aging into “pure” age states you need a different age measure, called biological time. It matches your intuitive age metaphor, and does not group individuals with different biological ages together.
More on Biological time : http://www.what-is-cancer.com/papers/ca/ca7.htm
Complexity is an evolving process. This example illustrates the fundamental difference between Wolfram’s complexity and the real thing. In Wolfram’s complexity the states are given and it can uniquely be simplified, while in life whose states are not given any simplification is arbitrary
Posted by: Gershom Zajicek M.D.
You are invited herewith to play with a CA applet.
http://www.what-is-cancer.com/papers/ca1/ca139.htm
Posted by: Gershom Zajicek M.D.
Intelligent design (ID) is a new theory opposing Darwin's theory of evolution.
Darwin's theory may be summarized as follows:
-- Observation:
Living organisms reproduce.
Offspring inherits traits from it progenitors.
There is variability of traits.
-- Deduction: Some traits will facilitate survival and other will hinder it.
The first difficulty of this theory is linked with the following query:
-- How are these various traits generated?
1. Darwinism: By random changes (mutation) of the inherited traits (genes)
2. H. Bergson: Traits are generated creatively.
The scientific community accepts only the first explanation and rejects the second. It is regarded as a dogma of a new scientist belief (religion) called Neo-darwinism. Yet we have seen in previous sections that randomness as such does not exist in nature. http://forum.wolframscience.com/sho...15&pagenumber=3
Which highlights a fundamental inconsistency of Neo-darwinism. The second inconsistency is linked with the notion that evolution operates solely on genes. Neo-darwinism ignores the fact that:
1. Life on earth is structured along food chains, and evolution operates on entire food chains.
2. Life evolved within a super-organism called Gaia.
http://www.what-is-cancer.com/paper...erspective.html
In other words while Neo-darwinism is essentially a linear theory, the existence of food chains requires a non-linear explanation. http://www.what-is-cancer.com/paper...ismDecline.html
We are led thus to examine a new theory called Intelligent Design (ID). Life on earth is extremely complex, and non-linear. Neo-darwinism lacks some essential concepts to tackle this complexity. Let's return to the above question: How are the various traits generated?
1. According to ID: Variation is controlled by an intelligent agent like God or an alien force.
2. It is proposed here that what we perceive as an intelligent design is a property of complex systems like Emergence.
In my studies I demonstrated that simple CA models can generate behavior which cannot be explained by Darwinism, and since the model evolves by itself, it does not require an intelligent agent to control it. This model manifests a wisdom, called Wisdom of the Body (WOB). After reaching maturity it maintains a steady state (homeostasis) and returns to it following a perturbation.
http://www.what-is-cancer.com/papers/ca/ca93.htm
Posted by: Vasily Shirin
Is it hard to conduct an experiment that could unambiguously show that mutations are not random? I regard darwinism as modern opium for the masses; based on any probabilistic considerations, emergence of human being within short period of time seems more fantastic than any religius dogma, but my question is: is it really hard to experimentally disprove darwinism? Or, maybe, this experiment cannot be conducted just because of ideological bias of current generation of "scientists"?
Within my memory, genetics and cybernetics were banned in USSR as contradicting marxist's theory; can it be that something similar happens with any alternative theory of evolution?
[ As an aside, I'm surprised to see how biased the academic world is. Is there any visible personality in biology that could dare exclaim: the king is naked! I wonder: how can anything radically new emerge in this environment? ]
Posted by: Gershom Zajicek M.D.
Karl Popper distinguished between falsifiable and non-falsifiable theories. The first he regarded as scientific, and the last as non-scientific. Psychoanalytic theory, for example is non-falsifiable, and cannot be regarded as scientific. It might be some kind of an ideology. Yet this criterion seems somewhat naïve. Take for instance a theory of a multi-dimensional complex system. While in some dimensions it may be falsified, in others not. Since it is so complex you may never expose the falsifiable dimensions. Also Darwinism is non-falsifiable. It should be regarded as a model of evolution which served its purpose for some time, and now has to be augmented.
This blind belief in Neo-Darwinism is called by Houston Smith, Scientism which must be differentiated from science. http://www.uu.edu/centers/science/b...eview.cfm?ID=37
Biology is dominated by Scientism with some characteristics of the ideologies which dominated science in the USSR. They make you believe that mutations drive evolution and even cancer, which to my understanding is sheer nonsense. And all this happens in the strongest democracy on earth, the USA.
http://www.what-is-cancer.com/paper...wmedicine0.html
Posted by: Vasily Shirin
I'm not sure it's really unfalsifiable.
How much do we know about mutations? I suspect - next to nothing.
Is it hard to conduct an experiment with microorganisms to observe
statistical properties of mutations?
Did anyone observe the emergence of new species as a result of
unusual conditions (like radiation)?
In general, has anyone done any quantitative research?
I can imagine how much buzz would be generated if there was any
statistical result in favour of darwinism. Since I haven't heard
this buzz (just preaching), I figure that nothing really is known.
Understandably, no one in Academy will finance any research which goes
against party line, but why there're no independent organizations
willing to do so? All this puzzles me a lot.
You may say that no matter what arguments are produced in experiments,
darwinists can dodge them by inventing more and more fantastic
counter-arguments. That's true, but after a couple of rounds the jury
will stop accepting these counter-arguments. In a word, darwinism will
be falsified when public stops believing in it.
Posted by: Gershom Zajicek M.D.
Intelligent design (ID) is a new theory opposing Darwin's theory of evolution. The main drawbacks of Neo-Darwinism were summarized in a previous section. In a nutshell, Neo-Darwinism applies linear arguments to explain evolution, while in reality evolution is a non-linear process. Neo-Darwinism should be regarded as a model of evolution which served its purpose for some time, and now has to be augmented. Which is virtually impossible since Neo-Darwinism attained a status of a religion which cannot be challenged.
This attitude to Neo-Darwinism is a manifestation of a new trend in science called Scientism (v. previous section), whose hallmark is the following statement by Theodosius Dobzhansky. “Nothing in Biology makes sense except in the light of Evolution.” Change one word and you get the ID credo: “Nothing in Biology makes sense except in the light of the Creator.”
Neo-Darwinists boast that among the numerous studies on Darwinism there is hardly any study refuting it. No wonder since Scientism dominates the scientific journals. For this reason scientists tend to jump on the ID band wagon hoping to topple Neo-Darwinism and pave the way for new paradigms. Indeed ID is a new paradigm, however its main drawback will be illustrated by the following example.
Collective intelligence of social insects
Ants build elaborate mounds whose size may reach several meters. Some ant societies form bridges and raid specific areas for food as a group.
http://www.bylandwaterandair.com/au...dying_ant_mound These mounds appear as if designed by an intelligent agent, yet all that is needed for building them is a collective intelligence, known also as swarm intelligence. http://www.sce.carleton.ca/netmanage/tony/swarm.html
Each ant may be regarded as an independent process interacting with other processes by chemical means like pheromones.
Evolution operates in the same way. Myriad interacting processes drive evolution to a rising complexity. Without two attributes of life a rising complexity would be impossible:
--Living organisms reproduce.
--Offspring inherits traits from it progenitors.
What actually evolves is the complexity of life together with its surroundings, collectively known as Gaia.
Such a distributed evolution can be conveniently simulated with CA.
http://www.what-is-cancer.com/papers/ca/ca93.htm
Posted by: Vasily Shirin
I don't understand your idea. Could you translate it to the language of computer engineering? In other words, do you believe there's a separate invisible computer that organizes individual ants into super-organism, or this is a fully distributed system? If the latter is true, is the behaviour of this system fully defined by ant's DNA? When you say their behaviour can be simulated by CA, do you mean they are in fact CAs, or what? And what's gaia - another invisible computer running CA, or what? You cannot just say "gaia", it's just a word with no meaning. How does this gaia work? By analyzing pheremones emanating from everything on Earth? I admit I have difficulty understanding your posts - it seems you believe in just everything: yoga, gaia, CAs, healers, etc.
Posted by: Gershom Zajicek M.D.
Swarm intelligence - (SI) is an artificial intelligence technique based around the study of collective behavior in decentralised, self-organised, systems. It is a set of interacting agents, each with a constant number of parameters. Initially it was applied to simulate the behavior of ant societies.
http://en.wikipedia.org/wiki/Swarm_Intelligence
When you replace each agent with a CA you get a swarm intelligence of processes. Such a swarm intelligence model evolves in a non-darwinian fashion.
Gaia theory is a group of scientific theories about how life on Earth may regulate the planet's biosphere. It was conceived by James Lovelock and augmented by Lynn Margulis
http://en.wikipedia.org/wiki/Gaia
Gaia started its existence with the appearance of the first organism on earth, and from then it evolves. While Neo-Darwinists claim that life evolved independently of the biosphere, I believe that life evolves as part of the biosphere.
http://www.what-is-cancer.com/paper...ismDecline.html
As to your questions:
>>In other words, do you believe there's a separate invisible computer that organizes individual ants into super-organism, or this is a fully distributed system?
-- It is a fully distributed system.
>> is the behavior of this system fully defined by ant's DNA?
Ants’ DNA are the parameters of each agent. The system is fully defined by these parameters and by its initial conditions.
>>When you say their behavior can be simulated by CA, do you mean they are in fact CAs?
--Indeed each agent may be replaced with a CA, and the model of agents turns into a model of processes.
>> And what's gaia
--Gaia is defined above.
>>I admit I have difficulty understanding your posts - it seems you believe in just everything: yoga, gaia, CAs, healers, etc.
--I don’t believe in these entities, I study them in order to help patients to live with cancer in peace. Since computer science is interested in biological metaphors, I try to arouse your curiosity about biological phenomena.
http://www.what-is-cancer.com/
Posted by: Vasily Shirin
So, you have one truth for your patients, another for yourself? I guess your
patients won't be very excited to hear the news that they are just collections
of memory cells driven by cellular automation. This kind of belief can make a
healthy person ill. So, at least in the context of medicine, the idea is, let's
put it this way, inconvenient.
Poincare wrote a number of articles where he showed that scientific theories are
accepted or rejected depending on how convenient they are in comparison with
competing theories. I can just refer to his works. Convenience of idea
"universe and everything in it is CA" has never been demonstrated.
Inconvenience of this idea was demonstrated by yourself - it makes your patients
even more miserable than they are under the circumstances.
I was a cancer patient myself, underwent quite debilitating treatment. I
decided not to work during treatment (my work of a programmer is almost as
debilitating as chemotherapy, so I just couldn't sustain these two experiences
at the same time). Instead, I made it a rule for myself of going to bookstore
every day and reading popular (non-fiction) books on just everything: quantum
physics, molecular biology, cosmology, etc. This really kept me alive. What
you get from these books is a sense of mystery surrounding us; although we
cannot make any sense of it, we certainly feel that there's some sense, which we
cannot understand. And maybe, the best we can do is to leave it this way - for,
any specification of meaning of life would destroy that very meaning.
I just want to bring up one extra point here. Suppose there're 2 groups of
people: one believes that everything is CA, another follows some traditional
religion, with its principle of "pru u'rvu" (in English translation, if my guess
is correct, it's "be fruitful, and multiply"). The problem is that first group
doesn't want to raise children, and population declines. The second group
multiplies with great enthusiasm and eventually drives the first group extinct.
"Survival of the fittest" in action.
Traditional religions are terribly obsolete. They offer collections of fairy
tales. I was never able to make any sense of them; you certainly need specific
genes in your DNA for this, which somehow went missing in my cells. However,
for religious people, life has meaning. For some reason, this makes a
difference for human being, no matter whether he is a healthy person or cancer
patient. Any theory that questions the belief that life has meaning has a
remarkable property of defeating itself by elimination of it's own supporters.
If you a fan of a theory "Universe is a computer", not only your life has no
meaning, the very expression "my life has meaning" is a nonsense - there's no
such thing as "my life" there. Everything is just a set of bits communicating
with each other; you cannot take some subset of them and say "it's me":
everything is interconnected. Suppose you are running a program that randomly
generates all sequences of characters, and eventually it comes across the
formula "E=mc^2". Would it be reasonable if a group of memory cells containing
these letters will claim that it made scientific discovery? So, whenever
Wolfram says he discovered this and that, and, among other things, that Universe
is a CA, I know that he doesn't believe in his own theory. For, within CA,
there's no Wolfram, and no Vasily Shirin, there's just a single clockwork
mechanism.
I don't quite understand how so big an intellect as Wolfram can make so bad
mistake. I've given a little bit of thought to it, and came up with a theory
that every man of talent is a revolutionary; he has an irresistible urge to
break something to pieces. The bigger the talent, the bigger this "something"
should be. More modest talent would be satisfied with proving that some
coefficient in some obscure equation by 0.1% differs from what it's believed to
be. Bigger talent would focus his efforts on proving that the equation itself
needs to be amended with extra parameter. Talent of Wolram's size wouldn't
settle for anything smaller than Everything, smashing the whole worldview. But
which worldview should be targeted - for, there're many? Somehow, he decided to
target religious worldview, which, I think, is purely accidental and has
something to do with the fact that western intellectual elite lately (I mean,
last 50 years or so) is engaged in a struggle against religion. Had he been
born in Soviet Russia, my bet is that he would hate atheism, marxism and
materialism as much as he hates religion, and would focus his efforts in
different direction.
There's a demand for meaning of life in western civilization right now, but
there's no supply. There're some "genetically engineered" substitutes, but they
are all fake. That's why you are at a loss while treating your patients.
Posted by: Gershom Zajicek M.D.
Dear Vasily
The name of the game in this thread are CA. Are they interesting? Are they pleasant, pretty, noisy or complex? You may even regard them as a kind of music Why not discuss some of the problems which you raised by phone and leave the CA at the center of stage. After all they are so cute!
http://www.what-is-cancer.com/papers/ca/ca01.htm
Posted by: Gershom Zajicek M.D.
Time is the foremost illusion of science. Long time ago Parmenides taught that it is indeed so. Then came Newton who believed that time is as real as space. Both are containers for events and are as real as the object they contain. Despite the teaching of Leibnitz that time is a way to describe change, modern physics regards time as an independent ontological entity which really exists and controls us.
What we perceive is change. In ancient civilizations astrologers studied change in heaven and discovered the way of heavenly bodies. They were interested also in the rate of change, which they expressed in terms of days, seasons or years. Yet these heavenly clocks were crude. Then one day the first water clock was invented and the measurement of the rate of change of events improved. With time this and other clocks became an essential factor in the evolution of knowledge.
Descartes introduced a mathematical framework within which change is studied. Three space and one time axis. The last differs inherently from the other since it is supposed to drive events, which is deeply rooted in the differential calculus. Take the metaphysical fraction ds/dt known as infinitesimal and try to invert it to dt/ds which looks like nonsense, Why? Since only time drives events. Whoever observed space to drive anything? The creation of ds/dt bred the time illusion which dominates science today. Serious truth lovers were even ready to accept that Newton’s time flows also backward. Why should Newton’s laws make such a contra-intuitive suggestion? Simply because eliminating the back flow of time from his equations would introduce an unpleasant discontinuity which Newton did not bother to handle. After all discontinuities are the main threat to the differential calculus.
And then came entropy with its time arrow directed forward. Entropy has two disturbing properties: It disobeys Newton’s laws and its rate cannot be measured with Newtonian chronometers. Might these two representations of time be united under a more general one? After all these theories are only two models for interpreting change, and there are more, each with its individual time and clock. Like the relativity theory which may be regarded as a set of instructions how to set your clock when traveling
Yet for some physicists, relativity theory has an unpleasant aspect. Time travel back in time is somewhat compromised. Fortunately it can be easily resolved with additional dimensions. With nine dimensions at hand and a brane, time travel is as easy as it can be. Or take Stephen Hawking’s A Brief History of Time. Shouldn’t it be broadened a bit and tell us about the History of Clocks in Time?
I started contemplating time, when realizing that medical doctors measure events in the body with a wrong time piece, the Newtonian clock, while in reality our clock is different. Take two of your friends with the same age. One looks younger, and the other somewhat older. Their Newtonian ages are the same, yet their biological clocks tic at different rates. http://www.what-is-cancer.com/papers/ca/ca7.htm
Since doctors measure disease progression with Newtonian clocks their prognosis is generally wrong particularly in cancer when some doctors assure their patients that their time is running out, while the patient’s inner clock disobeys their verdict http://www.what-is-cancer.com/papers/deathdenial.html
Long before Newton and Parmenides, Hindu philosophers realized that time is an illusion. The almighty Brahman is timeless, and lets his assistant by the name of Maya to spread the illusion of time.
Posted by: Gershom Zajicek M.D.
Since our life is controlled by the day and night cycle, it appears as if processes in the body are synchronized. Some chrono-biologists spread the illusion that circadian rhythms control processes in the body and make us believe that the body operates like a computer with a central clock. In reality each process in our body has its own clock ticking at a different rate. This asynchronicity is modulated by the day and night cycle.
I designed a two CA system in which each CA ticks at a different rate. One CA proceeds from state to state at a constant rate, and stands for a linear clock. In the other CA progression from state to state is proportional to its size. This clock ticks in a non-linear fashion.
Our organism consists of a myriad non-linear processes, each with its own clock. Take a seemingly simple biochemical reaction: A + B = C. In order to produce C, two proteins A and B have to interact. Yet A and B are states of two processes whose origins are at the gene site from which they stream toward the interaction site. Both are asynchronous, and in order to interact they have to adjust their clocks which depend on their streaming velocity. Time in the organism is even more relative than in Relativity theory. It is bounded chaotic.
http://www.what-is-cancer.com/papers/ca1/ca169.htm
Posted by: Vasily Shirin
If something looks like a spatial dimension, and smells like a spatial dimension, and behaves like spatial dimension, it IS a spatial dimension.
So, we have to conclude that there's one additional spatial dimension, let's call it w. Why we don't perceive it as a spatial dimension? Because it's compact (wrapped) - in other words, looks like a pipe. Why it's wrapped? I don't know. Maybe, inside this pipe, there's a massive rod that keeps the pipe rolled with gravitational pull, or something. It may not even matter, because the geometry of pipe is the same as that of plane. The trick is: our clocks tick not when we move along "w" axis by, say, 1 m, as you could expect - no! They tick when we move by 1 m in the whole 4-dimensional space. So, what is time then? It's an arc parameter:
dt=ds. That's why coordinates are transformed by strange formulas in SR.
That was my reasoning. It occured in my mind sponteneously. But it's probably wrong. Still, if someone can make any sense of it, feel free to use it in your theories of Universe, it's open-sourced under GPL. Please read more about terms and conditions of GPL here:
http://www.gnu.org/copyleft/gpl.html
As for biological time, my advice is: if you want to look younger, cut down on your travels in 4-dimensional space.
Posted by: Livin
nothing is random
Posted by: Gershom Zajicek M.D.
There are two approaches for understanding reality: The Cartesian and phenomenology. The first was introduced by Rene Descartes (1596-1650 ) who applied rationality to understand reality. His declaration: “I think, therefore I am” implies that thinking is rational. Three centuries later Heidegger (1889-1976) realized that Descartes’ seemingly straight forward declaration, which seems to us so obvious, conceals a stumbling block. He therefore asked, what does Descartes mean by his “am”? and concluded that reality ought to be studied from the “am” perspective, known as phenomenology. The term was coined by his teacher and friend Edmund Husserl ( 1859-1938).
Medical significance of Phenomenology
http://www.what-is-cancer.com/paper...enomenology.htm
Modern medicine still trots the Cartesian way, with unpleasant consequences as illustrated by the following example on the relationship between effort (E) and heart rate (H). It is linear H(E) = H(0) + b*E + error. H(0) stands for the resting heart rate, b, for the slope of the line. The error term accounts for the fact that observed data are spread around the ascending line. In previous sections of this thread it was shown that “error” or noise does not exist as such in nature. It is a (rational) construct to understand nature. Yet the error term actually conceals some vital heart characteristics which ought to be expressed by a separate function f(x) so that H(E) = H(0) + b*E + f(x). Since f(x) is non-linear and chaotic, medicine lacks means to handle it and ignores it. This is where phenomenology steps in.
v. Iatrogenic Medicine: http://www.what-is-cancer.com/paper...icmedicine.html
The first encounter of the exact sciences with phenomenology was shocking. The first fractal, the Koch snowflake (1904) was regarded as a monster curve. Later on it gained its respectability within Mandelbrot’s fractal geometry (1975). Then came Chaos, whose name reflects the horror of a physicist who is barred from reducing it to some elementary whatsoever. Why call it Chaos when in reality it is a manifestation of Heidegger’s “Dasein” and may be understood only by phenomenology.
Then came Wolfram (2002) who conjured all kinds of complexities with CA. Apparently he is not aware of the phenomenology trap which lures even in his reductionistic NKS book. He classifies his constructs into four classes of behavior (p.231), which is clearly a phenomenological approach. Yet why only four? His class four is an Eden of fascinating structures (monsters). Why didn’t he classify it further? Since he was anxious to avoid the slippery slope leading to phenomenology. His credo is “I generate complexity therefore I understand!” Does he really? In view of the fact that the real issue is how to reduce complexity without losing its meaning.
v. Autopoiesis: http://www.what-is-cancer.com/papers/ca1/ca174.htm
Posted by: Gershom Zajicek M.D.
This year AI celebrates its 50th anniversary. Its first task was to represent reasoning by rule-based systems. John McCarthy (1956) coined the name AI. Ted Shortliffe created expert systems for inference in medical diagnosis and therapy. It was the first attempt to formalize medical reasoning. Despite intensive effort in the so called computer assisted diagnosis, its relevance to the physician’s reasoning was marginal. Representing reasoning by a computer program is simply hopeless. Man is neither a machine as Descartes believed nor can his reasoning be reduced to logical elements.
Even in robotics this machine reasoning failed. The performance of robots equipped with sophisticated expert systems was disappointing. In the 1980s Rodney Brooks revolutionized robot reasoning with subsumption architecture. Robot behavior was stratified into layers of increasing abstract and complex behaviors. These studies paved the way to embodied AI dominating robotics today. We may thus distinguish between pre-embodiment AI of the founding fathers, and today’s embodied AI.
Intelligence requires a body. Embodiment is the way in which human reasoning arises from the brain's and body's state. It is an attribute of life and operates even in an ameba. Even the environment in which the body operates is part of the embodiment since triggering its state. Embodiment marks the entry of phenomenology into the exact sciences. Heideggers Dasein (explained in the previous section) is the hallmark of embodiment.
In my studies I represent embodiment by the Wisdom of the Body (WOB) metaphor.
http://www.what-is-cancer.com/papers/ca/ca93.htm
CA are essentially embodied since the entire state determines its subsequent state. However Dasein is more than that. It includes also the environment which CA generally ignore. Embodiment means also interaction, which depends on the number of neighbors (r) involved in the computation of the subsequent state. The greater ‘r’ the more environmental cells are involved in the computation of the subsequent state. Most CA in Wolfram’s book are more or less isolated (lonely) like the class-4 structures (p. 282).
In the previous section I explained why Wolfram classified CA only into four classes. We may now add the fifth, consisting of embodied CA which completely interact with their neighbors. Yet they have an “unpleasant” quality. This class-5 cannot be reduced to its elements and may only be treated phenomenologically.
Embodied CA:
http://www.what-is-cancer.com/papers/ca1/ca167.htm
Posted by: Gershom Zajicek M.D.
Cellular automata (CA) are an ideal tool for examining interesting philosophical ideas particularly those relating to the complexity of nature. However not all CA are suitable for this purpose. For instance, although Wolfram’s NKS generates all kind of complexities, they are somewhat inadequate. More precisely NKS can handle only a reductionistic philosophy and fails when confronting phenomenology. In order to be philosophically interesting and even intriguing, CA have to interact.
Take a simple two CA system by the name of proliferon.
http://www.what-is-cancer.com/papers/ca1/ca167.htm
You plant two zygotes and they evolve into mature non interacting CA. Already these simple structures illustrate some profound ideas like emergence which drives the system to its first attractor. Now, manipulate their output rates and let them interact. The system evolves toward a new attractor. Is it chaotic, or only bounded chaotic? Sensitivity to initial conditions is the hallmark of chaos. Yet you did not change any initial conditions. You watch a phenomenon or behavior which does not have a name yet. More, has chaos any meaning in a continuous process which by definition lacks initial conditions. ( Like our weather where the butterfly effect was discovered)
Injury of one CA is responded by the entire system which after a while settles at a new attractor. You wonder what is the relationship between injury and the new outcome. Cause and effect? Or might this phenomenon be explained only with Aristotle’s four causes?
http://www.what-is-cancer.com/papers/ca/ca3.htm
As you play with this proliferon you suddenly realize that you are unable to explain its behavior. You cannot foresee how it will react to injury. From your past experiments you know that it will always settle at an attractor, yet how? Or why did it choose this particular attractor?
You might conclude that the proliferon has an Aristotelian soul. Aristotle taught that plants and animals have a soul which controls their operation (metabolism) and is mortal. When the plant dies its soul dies with it. Our proliferon soul is not a separate entity. It is part of the system and emerges with the system’s interacting CA.
http://www.what-is-cancer.com/paper.../blindlady.html
Posted by: Gershom Zajicek M.D.
Memory is our faculty to remember past events. Yet where is this memory stored? In the brain is the obvious answer. Yet there is more to it. Suppose that you learn to ride a bicycle. Initially you have to concentrate on your movements and remember how to act. While you think of riding, myriad unconscious processes adapt to it. Certain muscles become stronger and require more blood which is also directed to the brain regions which control riding. More blood means also a higher demand for oxygen. Breathing and heart rate get faster and so on.
With time you ride automatically, and your organism adapts more efficiently since remembering how to properly operate. We may thus distinguish between conscious memories residing in the mind (brain) and unconscious memories embodied in the entire organism (WOB). Suppose that you stopped bicycle riding and after many years you decide to start again. Your mind memory remembers that you know how to ride, yet your body does not respond so well. Muscles became weak, the heart does not pump enough blood and breathing requires an extra effort. In short your organism forgot how to ride well and you have to train again. The distinction between mind and embodied memory is artificial, since our entire memory is embodied.
http://www.what-is-cancer.com/paper.../embodyment.htm
The elastic band is a simple example of an embodied memory. After being stretched it remembers its initial state to which it returns when stretching is released. Memory is embedded in the entire band.
While computer memory stores data, embodied memory stores actions. Which is illustrated in a simple CA with a period of 46 states. Each state represents a different action memory which may be triggered by injury.
http://www.what-is-cancer.com/papers/ca/ca82.htm
Properties of a complex system memory:
1. Embodied in the entire system
http://www.what-is-cancer.com/papers/ca1/ca143.htm
2. Stores actions
http://www.what-is-cancer.com/papers/ca/ca12.htm
3. Recall is activated by an external trigger which may be regarded as its reading head.
http://www.what-is-cancer.com/papers/ca1/ca148.htm
4. Each state can store many memories (actions), whose recall depends on the nature of the trigger.
http://www.what-is-cancer.com/papers/ca1/ca148.htm
5. Memory is a process which may gradually fade away. In order to remain alive it requires an external trigger.
http://www.what-is-cancer.com/papers/ca1/ca171.htm
6. An external event may initiate an action (reading) or modify an action (writing)
7. Memory is a doublet {state, trigger}.
8. An isolated system has no memory since its states cannot be read or modified. They do not meet the doublet requirement. An isolated system is simply a pile of bits (matter). It does not matter whether its entropy (information) is high or low. In its splendid isolation it will remain dumb for ever.
Posted by: Gershom Zajicek M.D.
In the previous section on the properties of complex system memory I mentioned two:
1. Memory is a doublet {state, trigger}.
2. An isolated system has no memory since its states cannot be read or modified. They do not meet the doublet requirement. An isolated system is simply a pile of bits (matter). It does not matter whether its entropy (information) is high or low. In its splendid isolation it will remain dumb for ever.
How does this relate to information theory with its tools to measure the information capacity of any system? According to Claude Shannon (1948) all information has a "source rate" that can be measured in bits per second. Information theory knows how to measure information capacity even of an isolated system yet does not specify its meaning. A dumb system may have a great capacity to store information. As long as it is isolated this information is meaningless.
The information of a message is inversely proportional to its entropy. The greater the information, the lower its randomness, and hence the smaller its entropy. Information is a measure of the freedom of choice with which a message is selected from the set of all possible messages.
In complex systems memory is a doublet {state, trigger}. In an isolated system the trigger does not exist and its Information (or entropy) can be precisely determined. Yet when the trigger is activated information changes. Therefore Information depends on the trigger. While information theory measures information in isolated channels, in a complex system information is a component of a doublet { Information, trigger}. Since complex system memory is embodied, information theory is of little use.
Hermeneutics
Hermeneutics is a theory for the interpretation of messages. During the Reformation hermeneutics came into being as a special discipline concerned with biblical interpretation and criticism. Yet what is meant by a proper understanding of a text? How can we find out what the intention of the author of the text was? We can’t! Since the text is a component of a doublet {text, trigger} and the reader is its trigger, hermeneutics depends on us.
In the search for the attributes of complex systems I discovered Aristotle. A biologist impressed with the complexity of nature, although the notion of complexity as we have it was unknown to him. In order to understand Nature we need four arguments, which he called Four Causes. Their relevance to complexity, and CA are explained in a different section.
http://www.what-is-cancer.com/paper...ndaristotle.htm
Aristotle’s concept of the soul is particularly interesting. Plants and animals have a soul which is an integral part of their structure and dies when they do. How may we understand it. The organism is a set of processes which interact and control each other. This overall control is perceived by us the as a soul of the system. I call it the Wisdom Of the Body (WOB). It is closely related to embodiment.
Soul: http://www.what-is-cancer.com/paper...dcomplexity.htm
WOB: http://www.what-is-cancer.com/paper...omofthebody.htm
Embodiment: http://www.what-is-cancer.com/paper.../embodyment.htm
This is my hermeneutics of Aristotle’s great ideas. Does he turn now in his grave? Not necessarily. If accepting the notion that his work and me are a doublet of a complex system, he may rest in peace.
p.s. By the way all this babble is phenomenology
http://www.what-is-cancer.com/paper...fcomplexity.htm
Posted by: Gershom Zajicek M.D.
1. And the Lord observed matter.
2. Then He found it better
3. to give it a kick
4. and it started to tick,
.
5. Out of this mess
6. grew a process.
7. Then it split in two
8. and divided anew.
9. They started to combine.
10. Interact, intertwine,
11. and the Lord found it fine.
12. The thing in itself
13. aware of herself.
14. Started to feel,
15. and a soul to reveal.
16. Astonished to find,
17. the beauty of her mind.
18. I think therefore
19. I am, and more
20. Myself I adore!
G. Zajicek
http://www.what-is-cancer.com/papers/ca/complexity.htm
----------------
Legend
1. Matter is eternal (Aristotle)
2. Creation started with the initiation of movement. (Big Bang)
3. God is the self-moved being that causes all motion (Aristotle).
4. Nature sets the time.
5. Life originates in a process.
7. Renewal is the prerequisite of life
9. Evolution of complexity involves interaction.
11.God does not interfere with Nature.
12. Kant
13. Differentiation of the thing in itself.
14. Sensation is essential for survival.
15. Soul is a property of a complex system (Aristotelian Soul)
18. Descartes
20. Post-modern vanity
Posted by: Gershom Zajicek M.D.
We perceive nature as change and if change is extremely slow it is regarded as constant. In other words constancy is an extremely slow change. This insight is summarized by Heraclitus’ statement: “Nothing endures but change”
http://en.wikiquote.org/wiki/Heraclitus
Heraclitus (535 - 475 BC), know as “The Obscure” created some profound metaphors which are relevant even today. Stated in a modern way he regards nature is a complex process and says: ”The sun is new every day.” Since the sun changes extremely slowly it appears invariant. However the sun is a process which burns itself to death and from our viewpoint is rejuvenated every morning. Note how poetic this metaphor is. The sun-process is not at all a random birth-death process, since randomness does not exist in nature ( http://www.what-is-cancer.com/papers/ca/randomness.htm). The sun is a bounded chaotic process. It is like a river which flows and does not stand still.
Since “nothing endures but change” , and “everything flows, nothing stands still”, “you could not step twice into the same river; for other waters are ever flowing on to you.” The last metaphor is known as “panta rhe” .(All streams). It implies the modern notion of Chaos. Scientists at UC Santa Cruz found chaos in a dripping water faucet. Unfortunately they did not bother to establish chaos in the Santa Cruz river which would convince them that one cannot experience twice the same chaos.
The river metaphor implies also that despite being chaotic you still recognize the Santa Cruz river as a river, since its chaos is bounded by the river bed. Bounded chaos is illustrated by an interesting CA experiment.
http://www.what-is-cancer.com/papers/ca/ca126.htm
However since “nothing endures but change” the river bed is also chaotic, and we are fortunate that its chaos changes very slowly. Like the newborn sun.
In another fragment Heraclitus adds to the river metaphor: “No man ever steps in the same river twice, for it's not the same river and he's not the same man.” Processes in our organism continually stream, and we are bounded chaotic. Therefore one never meets the same individual twice.
http://www.what-is-cancer.com/paper...sstreaming.html
Posted by: Philip Ronald Dutton
Is a river flowing in or flowing out? Is it a sink or a source?
Is a Cell in a CA grid a sink or a source? If it just recently turned "on" then it is a source? Or is it? If the cell is "on" after recently being "off" then maybe it is still a sink since this new "discrete" change just arrived INTO the grid? How do we know which way the "change" is "flowing" in these CA grid cells?
Posted by: Gershom Zajicek M.D.
The spring might be regarded as its source and the sea as its sink but they are in some remote regions. The river is neither flowing in nor out. We can appreciate only the change of its structure, which we interpret as flowing. It has never been turned on since the river is nourished by rain which started pouring on the primordial soup eons ago. The river is a metaphor for a process. All processes in our organism are interconnected. They neither have a source nor a sink and we can’t determine the direction of their flow, which to my understanding is irrelevant.
CA are discrete and I apply them to illustrate the above features of an interconnected complex system. Click on the proliferon and watch it evolve. It may change its position in space, however its structure does not reveal where it is flowing to. Its previous states seem to flow backward however if you reduce the CA to one state its past memory will vanish.
http://www.what-is-cancer.com/papers/ca1/ca167.htm
Posted by: mohammed1
Is this a diary entry ?
many people talk about too many things ? too many things at one point only is not useful.
i
Posted by: Gershom Zajicek M.D.
By now you may have realized that there is something which philosophy has to offer particularly when dealing with complexity and you wonder what it may be? Examine again the two CA system called Proliferon.
http://www.what-is-cancer.com/papers/ca1/ca167.htm
Raise the output rates. click on ‘infection’ and watch its behavior. It is driven by rule #600, and despite its simplicity, you don’t really understand its behavior, or its intentions. Clearly the system is driven by simple mathematics, yet you lack any mathematical tools which might help you to predict its trajectory. Not even differential equations or multivariate statistics will help. You have to search for new tools, but how and where? So you turn to philosophy for new ideas which hopefully might be translated into some kind of new mathematics.
Bergson is usually dismissed by the exact sciences as a somewhat irrational philosopher. He regarded the world dualistically, divided into two disparate realms, life and matter. While life evolves and climbs upward, matter falls downward and its entropy rises. The exact sciences succeeded to harness matter and energy for our benefit, yet lack the capability to explain what drives life. Bergson called it life force (élan vital) which differs inherently from Newtonian forces. No wonder that physicists ridiculed him as a Vitalist. It turns out that this élan vital is also a property of complex systems like the Aristotelian soul or the WOB.
WOB: http://www.what-is-cancer.com/papers/ca/ca93.htm
Soul: http://www.what-is-cancer.com/paper...dcomplexity.htm
Bergson was the first to recognize the shortcoming of Darwinian evolution. Life does not adapt passively to changes of the environment, rather it utilizes them creatively. Evolution is a creative process.
Bergson’s time which he calls duration (la durée) is particularly relevant to complexity. We conceive now and past as two mutually exclusive events. Each time unit is discrete and isolated. It follows its predecessor in the same way as the number two follows one. Time is a mathematical succession of static states. On the other hand duration is an amalgamation of the present with the past. This difficult concept may be illustrated by the proliferon. Its present state cannot be isolated from its past since its structure was shaped by previous states which continue to act in the present. In other words the past flows into the present and cannot be distinguished from the present. The proliferon is a one dimensional structure (worm) which changes continuously. Although the program enables the observer to store past states and display them sequentially the proliferon cannot store and display its past states. We are confronted here with two kinds of time: Observer time which is chronological and proliferon duration which is not. Duration is called here biological time.
Biological time : http://www.what-is-cancer.com/papers/ca/ca7.htm
The proliferon illustrates also two ways to interpret phenomena. Zeno and the Eleatic school maintained that there are things and no change, while Heraclitus and Bergson maintained that there ware changes but no things. In the present experiment the observer controls a thing and may freeze it at will, while the proliferon experiences only change. The fact that the proliferon proceeds through discrete states is irrelevant to the above distinction. Simply imagine this worm as a flux.
WOB is a set of interacting processes each with its individual time (duration). Process time is more relative than Einstein’s time. Relativity theory provides a traveler with a formula with which he sets his clock when observing different systems. No such formula exists for a traveler (trajectory) in the process set.
Additional reading
Bergson and medicine http://www.what-is-cancer.com/papers/Bergson.html
Posted by: Gershom Zajicek M.D.
About three years ago the human genome was mapped, and named The Book of Life. It appeared as if life started revealing some of its secrets. Soon diseases will be uniquely defined and in the future their faulty genes will be replaced with healthy ones. Investors rushed to reap the new discoveries only to find out that the Book fails to deliver the goods they hoped for. Actually the Book is not smarter than a telephone directory. Why then invest in a list of names?
Epigenesis: http://www.what-is-cancer.com/paper...genesisinca.htm
True the Book is a blueprint of the organism. Each gene is located at the origin of an assembly line of proteins. Unfortunately the mapping of gene to protein is not one to one as molecular biologists claim. It is one to many
Streaming proteins: http://www.what-is-cancer.com/paper...g/proteins.html
First of all there seems to be no correlation between the number of genes in the Book and the complexity of an organism. While the human genome consists of 25000 genes a worm has 19000. and a plant has 26000 genes. The complexity is generated all along the protein assembly line. Yet molecular biology still operat