[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 operates under the guidance of the Central Dogma of Molecular Biology. Information flows irreversibly from DNA to RNA to protein and the mapping from DNA to protein is one to one. Recent discoveries reveled that this mapping is actually one to many. With alternative splicing one gene may serve as template for many proteins. Recently discovered micro RNAs control the way messenger RNA copies the DNA gene, increasing the repertory of proteins which are coded from one gene even more. The mapping is one to exponentially many.
The reason for the excitement with the Book of Life was the naïve belief that it will inform us about diseases and their cure. Molecular biologists claim that diseases are gene aberrations. You take the genome of a sick person spread it on a DNA chip which is an array of gene products, and compare it with the DNA chip of a healthy one. With special dyes you make the deviant genes shine , and you can uniquely define a disease. To your dismay you find out that many genes lit up. You are dealing with a fairly large set of aberrant genes, and wonder, which one should be replaced in order to cure the patient?
When the first genes were discovered, geneticists believed that the so called genetic diseases are caused by a change of a single gene. Soon they realized that most if not all diseases are caused by changes in many genes. Diseases are polygenic. How come that they still attempt to replace single genes? Since they regard the changes in other genes as negligible or irrelevant.
http://www.what-is-cancer.com/paper...icmedicine.html
Molecular biology is dominated by the complexity demon:
http://www.what-is-cancer.com/paper...lexitydemon.htm
Posted by: Gershom Zajicek M.D.
While there are several ways to generate complexity, our main concern is its reduction or simplification. Like how to capture the quintessence of a complex system like the brain? The following story will reveal some unpleasant side effects of this venture.
In the heart of the scientific revolution lies the insight that phenomena in nature can be explained rationally. Phenomena are represented by simple concepts which are then handled rationally. For instance a moving body is represented by its center of mass and its trajectory is a trajectory of the center of mass. Generally, Newton’s laws apply solely to similar representations and therefore cannot be regarded as laws of nature. Fortunately such representations are adequate to handle our daily activity and keep us happy.
The main problem of science today is how to represent complex and interacting phenomena like the stock exchange. It is unfortunate that the plethora of stock market representations suggested by experts does not make us rich. The pessimists claim that the random walk is the best representation of the stock exchange which does not explain why some still get rich. http://www.what-is-cancer.com/paper...ness.htm#cadont
Nerve cells in the brain form a complex network through which they communicate by electric signals called action potentials. Some neuroscientists assume that like bits, these action potentials are elementary units of the brain computer. Decode them and you gain access to our secret thoughts. Some even believe that these action potentials are our thoughts. In reality they are no more than representations of the brain activity.
Several years ago a neuroscientist named Benjamin Libet decided to study the relationship between our will and these action potentials. He asked subjects to move their finger, and report when they decided to move it. Libet found that the nerve impulse from the brain to the finger was on its way before the subjects reported having made their decision. His conclusion was amazing. It is not they who decided to move their finger, it was their brain. Soon distinguished neuroscientists and philosophers joined him to announce that we lack free will. The brain decides for us.
This false conclusion was initiated by the assumption that action potentials are the essence of our brain activity while in reality they are arbitrarily chosen representations. Measuring other representations, and there are many, one might conclude that our free will still kicks as before. Yet there is more to it. The brain is part of the nervous system which interconnects all cells in the body. Every cell in our body has a dedicated nerve fiber with which it connects to the brain. When neuroscientists speak of the brain as a complex network they mean only cells in the brain and ignore the neural network in the body which may be even more complex than the brain itself. The brain is like a mushroom which belongs to a huge network of hyphae permeating the soil. It is embodied in the nervous system and in us.
http://www.what-is-cancer.com/paper.../embodyment.htm
Posted by: janos
You write:
"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. "
My question is: How different the protein assembly lines are ?
Or asking otherwise: How universal are the protein assembly lines ?
Is it possible to generate different proteins by feeding different DNA to the same assembly line ?
How different the proteins would be if the same DNA would be fed to different assembly lines ?
This last one probably can be tested by the existing cloning technices, that is extract the cell own DNA from the cell and inject a foreign one and measure what kind of proteins are generated.
CellularAutomation looks to me like an universal "protein" assembly. You can give it different "DNA" - rule numbers - and it cranks out the "protein" - the actual CA.
J‡nos
Posted by: Gershom Zajicek M.D.
Nucleotide: elementary DNA unit
DNA: linear set of nucleotides (universal)
Codon: a nucleotide triplet
RNA: mapping of a codon to an amino acid (universal)
Start-codon Stop-codon define the domain of RNA mapping. They are also the initial conditions of RNA mapping
Gene: A linear set of codons
Protein: A linear set of amino acids.
Protein conformation: Mapping of the linear protein into a coil. Given a sequence of amino acids, each coil is a different protein
Alternative splicing: A shift of the start and stop-codons (new domain) so that the gene sequence is mapped into different amino acids.
Mutation: A change of a codon which is then mapped into a different amino acid.
microRNA: Modifies RNA mapping (by silencing genes) so that the same gene (domain) may be translated into a different set of amino acids.
Each gene is a source (initial condition) of a protein assembly process. Amino acids that are formed from a gene stream away and grow into chains which incorporate other molecules. Later on they coil (become different protein) and finally die (are broken into molecules) . In the healthy organism, for each dead protein a new one is born which is known as steady state condition.
streaming proteins: http://www.what-is-cancer.com/paper...g/proteins.html
A simple illustration with cellular automata (CA)
The gene is a CA string which serves as an initial state for future iterations. The CA is born when the initial state has been specified.
CA rule is the RNA
CA structure is the protein
Alternative splicing: Applying the same rule to different initial states (domains)
A gene set generates different CA (proteins) which interact as they go.
The life of a CA is finite. For each dying CA a new one is born (steady state conditions)
Example http://www.what-is-cancer.com/papers/ca/ca36.htm
Answers to your questions:
DNA code is universal
Different proteins are determined by the DNA domain (initial conditions), and RNA silencing. The DNA itself does not change.
You may generate different clones only by modifying the RNA or its domain. The DNA remains invariant
In your last sentence replace DNA with RNA and your conclusion will be correct.
Posted by: Gershom Zajicek M.D.
The greatest challenge of modern science is complexity simplification. How to extract the quintessence of a complex system. Or better what is the quintessence representation of a complex system. Hitherto we have been busy collecting information on complex systems and storing it in databases. Yet how to transform this information into a model representing what actually goes on? Scientists attempt to simplify by reducing information to elements (atoms), yet databases are full of elements. Think of the myriad DNA sequences stored in huge databases? Most of them deserve to be called “Junk DNA” since they obscure the essence. Why not study how our organism handles complexity?
The organism has two kinds of memory: Action memory and orientation memory. The newborn is equipped only with the first. It moves its extremities erratically, yet even this movement is highly coordinated. When bending its arm some muscles are contracting and others relaxing. This coordination is stored in an action memory. Breathing requires a more refined coordination. The heart adjusts its pumping rate to the breathing rate. Heart rate is adjusted also to the erratic arm movements. Whatever the baby does has to be coordinated by all systems in the body. This knowledge or action memory is called here Wisdom of the Body (WOB).
WOB is stored in the entire baby and not only in its brain. It is stored in its structure. This concept is nicely illustrated by the proliferon.
http://www.what-is-cancer.com/papers/ca1/ca167.htm
An isolated CA oscillates through 46 states. Each state stores the information how to generate the subsequent one. This information is stored in its entire structure. Each state is an action memory. When interacting with the environment, like following injury (infection), each state serves as action memory generating a process which is triggered by the infection. In the interacting CA, action memory is a doublet {CA structure, trigger}.
When the brain of a frog is removed, it continues living and displays many functions of the newborn. It may even jump when triggered. This simple experiment illustrates that many action memories in our organism do not require the brain and they are embodied.
The baby’s erratic movements indicate that it exerts its own will (free will) otherwise it would not budge. Its will is stored in its entire structure. It is embodied. The baby’s purpose is to coordinate its senses and create its orientation memory.
http://www.what-is-cancer.com/paper...ryofcomplex.htm
Neuroscientists claim that our memory resides only in the brain. It stores images like an ongoing movie and operates like a computer memory. These naïve metaphors obviously do not apply to the brainless frog. Unlike these metaphors the action memory concept may be applied to handle the “Junk DNA" which permeates our databases. Given a set of DNA sequences. How to define an action memory that will generate them all?
More on CA memory
http://www.what-is-cancer.com/papers/ca/ca82.htm
http://www.what-is-cancer.com/papers/ca/ca83.htm
http://www.what-is-cancer.com/papers/ca/ca30.htm
Posted by: Gershom Zajicek M.D.
The organism has two kinds of memory: Action memory and orientation memory. The first is explained in a different chapter
http://www.what-is-cancer.com/paper...ctionmemory.htm
The newborn is equipped with an action memory, its task is to create an orientation memory and it starts to move. First it moves its extremities some time later, its head, then its body and so on. Movement is the prerequisite for creating an orientation memory since it rescues the baby from isolation and enables it to interact. Movement and interaction generate knowledge.
The baby is equipped with many (really many) sensors and the purpose of orientation memory is to associate between sensors and movement. Pain is the most important sensor. The baby lies on its back and feels the pain caused by a small toy in the crib. Since lacking an orientation memory it cannot relieve its pain and starts crying, which mobilizes the orientation memory of its mother to relieve its pain.
Orientation memory is an ongoing process. It is volatile and emerges. It has inputs and outputs. Inputs are provided by the senses. Outputs are either fed into the action memory or destroyed. The conscious part of orientation memory is in the mind, the unconscious part, in the WOB (Wisdom of the Body).
Suppose that you decide to become a piano player. First you store the keyboard image in your orientation memory. Then you consciously place each finger at the proper place and push. Your first task is to create in your orientation memory a sub-process which will associate between finger position sensors and movements. As you practice, more and more such associations are output into the action memory. Improper fingering will be destroyed and removed from orientation memory. During your first performance, action memory handles the playing while orientation memory of your mind controls its quality.
Neuroscientists make you believe that the concerto is stored in the brain like a movie and performed frame by frame. However, action memory does not store images. It stores structure that generates actions, similarly to what the proliferon does:
http://www.what-is-cancer.com/papers/ca1/ca167.htm
The isolated CA oscillates between 46 states. Each state is an action memory which “knows” how to generate the subsequent state. Now imagine that the 46 states are a CA concerto. As the CA performs, it does not remember the entire score. It plays only its present structure which instructs it also how to generate the subsequent one.
This capability to generate the next tune from the present one is called in psychology association. Take the following definition provided by Answers.com: Association is a connection between different sensations, feelings, or ideas by virtue of their previous occurrence together in experience. As an exercise rephrase this definition in terms of action and orientation memory and flavor it with Bergson’s duration.
http://www.what-is-cancer.com/paper...dcomplexity.htm
This story illustrates how our organism simplifies and stores a complex concerto. It seems to me that CA are a good starter for implementing simplification. The task would be to transform a data base of DNA sequences into a set of associations.
Posted by: Enexseenge
Is orientation memory finite?
Can there be only so much orientation..
It seems that only so much could be "used" to form action at any given moment, and that some parts are ignored for certain actions, what do they do when they are being ignored?
If that same infant was in the crib and heard it's mother and father speaking, it could not have an orientation related to these words.
So if you walk up to a baby and say "sod off bugger" it cannot react in a normally oriented way from a structured faculty of language, yet 6 years later on the play ground if a fellow class mate comes up and says "sod off bugger" the child may react, for they have formulated orientated around the words.
My question is this... Does this orientation memory decay?
Not so as something that is inevitable, but more so as a process that must be worked against In order to form structure..
But does the orientation memory need constant "renewal" constant maintenance? Perhaps, if so, then within this "maintenance" process we can find emergent rules..
There are so many different facilities within the brain though..
Perhaps this could be extended to CA systems.
An idea that comes to mind is to have two CA running overlapped, one could represent the “environment” and the other could represent the “being”, just to put loose terms out there. The environmental CA would run first and developed a nested structure that repeats it self within a small degree of change, the “being” CA would then be deployed and it would have initial conditions that would adapt to the Environmental CA and develop for it self a nested structure which would be sourced from it’s initial conditions and the conditions of the “environmental” CA overlay… Later you could maybe go on to allow the “being” CA to effect the “environmental” CA, or increase the sophistication of the “environmental“ CA to include much more complex, yet useable structures..
Just an idea.
Posted by: Gershom Zajicek M.D.
The action memory of the newborn has the faculty to speak, known as language instinct. What, and when the baby will speak depends on how his orientation memory evolves. Memory is a process specified by the doublet {input, output} Input is provided by the senses and other processes. When input > output memory grows, and when output > input it decays. If the piano player of the previous example stops playing his memory will gradually vanish (he will forget). Memory requires resources.
Observe the proliferon http://www.what-is-cancer.com/papers/ca1/ca167.htm
Initially input = 1 , output = 0 and the CA is isolated. The 46 states through which it oscillates were viewed in the previous section as its music score. When you raise the output, the CA will change its structure, forget its pervious score and create a new one. On the hand when you lower the output it will regain its original score.
Alzheimer’s disease hits the orientation memory of the patient. Its output > input, and the patient loses his orientation. However his condition may be improved by raising input. Encourage the patient to move (sport), stimulate his senses with music, flowers or images (TV). The proliferon experiment illustrates how the lost memory (score) may be regained.
More on Alzheimer’s disease: http://www.what-is-cancer.com/paper...alzheimer1.html
In summary, here are the answers to your questions:
Orientation memory is finite but may be extended at will.
Unused memory decays. In other words: Use it or lose it.
In order to “enjoy” the phrase "sod off bugger" the baby has to evolve its orientation memory.
Please note that in the CA experiments, the CA themselves are “beings”, and the observer acts as environment.
Posted by: Gershom Zajicek M.D.
“She sat at a table and sipped slowly her coffee when she felt his eyes caressing her back. She turned around. Her eyes widened, her heart jumped into her throat and she blushed. ”
Emotions are inborn and stored in the action memory. Her sensation of his eyes was interpreted by the orientation memory. The interpretation triggered the initial state of the emotion process in the action memory. Emotions are stored all over the body. Take blushing, which is handled by blood vessels in the face. Or the heart which starts pumping faster. They have no representations in the brain and do not belong to it. Emotions are embodied.
“Motion” is the root of the word “emotion”. Motion stands for a change in behavior, or instinctive action originating in action memory. Emotions control the behavior of animals during courtship, which is practiced also by insects. The dance of a bee in front of the beehive is an act of emotion. Swarm intelligence is the collective intelligence of emotions.
She was an actress studying the role of Nora in Ibsen’s play. To prepare herself she studied emotions of lonely and desperate women, watched their behavior and tried to act it out. She had experienced a similar challenge before when studying piano playing. http://www.what-is-cancer.com/paper...ationmemory.htm Initially she had to memorize where the keys were, storing this information in her orientation memory. Finally when her action memory took over the playing she became a successful pianist. She new that in order to convince the audience, Nora has to be enacted by her action memory.
Years went by. One day, sitting with her family she suddenly remembered him, his eyes caressing her back and she blushed. What did she remember? She obviously remembered the cafeteria and him sitting behind her. Yet the image left out much of the detail. When she was urged to add more detail:” Tell us more granny!” She unconsciously supplemented it with information which she gathered in the neighborhood cafeteria. Memory of him triggered a process in her action memory which made her blush. Yet this process was not part of the recollection. It was there from the time of her birth and triggered whenever she remembered him.
These examples illustrate how we handle information. Memories are not images which are shipped as such between brain regions. What is shipped are representations handled in parallel. Abstract concepts like memory and emotions may now be simulated with cellular automata.
Posted by: Gershom Zajicek M.D.
In order to simplify the information which the organism handles it stores memories as representations and not as images http://www.what-is-cancer.com/paper...ctionmemory.htm Emotions are also stored as representations. These are states which when triggered generate a particular emotion. Yet the greatest challenge is how to handle information generated by sense organs and other receptors. Many (very many) receptors are scattered throughout the organism. They transduce touch, pressure, temperature, and more. Information is relayed to the central nervous system for additional processing.
Receptors respond only to change. Try it. Let somebody touch your hand. Initially you feel him touching you yet in a while you will not feel the touch anymore. We feel the temperature in or room only when it changes. Or, watch the fly enjoying your sandwich. As long as you stand still you do not exist. Only the movement of your hand is sensed by it and it acts while your hand lands on the sandwich obeying Newton’s laws of motion.
Then there is the Weber-Fechner law. When the intensity of a stimulus is raised it is tranduced into the logarithm of the change. The relationship between stimulus and perception is logarithmic. If the stimulus changes as a geometric progression it is transduced into an arithmetic progression. If the stimulus exceeds the transducing capacity of a receptor it is perceived as pain.
In order to be processed stimuli have to be expected or anticipated. Expectations are memory states that generate actions. Let me describe an important discovery of mirror neurons by Giacomo Rizzolatti et al. A mirror neuron in the brain fires both when an animal performs an action and when the animal observes the same action performed by another animal. When you raise your hand some neurons in your brain fire (generate action potentials), and the same happens when you watch your friend raising his hand.
You sit with your friend. As long he is still you are unaware of him. Suddenly he raises his hand (change) which is caught by your eye. The tranduced information triggers in your action memory a hand raising process by which you grasp (unconsciously) the meaning of the change that occurred in your friend. Mirror neurons indicate the state of your action memory.
His hand raising does not initiate in you an image processing of the observed change. It activates a certain state in your action memory, and if such a state does not exist you cannot interpret the change. When a change occurs your action memory anticipates its meaning.
You smile at a baby and it returns a smile which might be interpreted as follows. In order to understand that you smile, the baby has to store in its memory a face and interpret its change as a smile. Then it has to know which muscles to move in order to smile. Yet all this might be somewhat simpler. The baby observes the change in your lips which triggers in its action memory a mirror state which is followed by a smiling process.
Additional reading http://www.what-is-cancer.com/paper...ndfreewill.html
Posted by: janos
You write earlier about the two type of memory. You said that one is in the mind the other is in the body. I am wondering where these memories are actually stored. What is the mechanism to store memories. If I remember well, today's science says that memories are stored in the brain as action potencials between neurons. That would mean that a memory always die with the individual, because it MUST be with his decayed brain cells. In earlier post you discussed epigenetics, that is processes where something unique to the individual shows up in the descendends without any sign of it in the "genes". That sounds to me like memory. Then it means that memory cannot be "between cells" - braincells - but rather it must be at a lower level in the cell.
That brings me to my favorite subject of my childhood. The chicken and the goose problem. Newborn chicken hatched on a small island - 1 m diameter - surrounded by water surely dies on the island. The newly hatched goose does not have this problem. It jumps in the water and swimms around. How the chicken knows that it must not go into the water. That information obviously must be inherited. The chicken must have the concept of water as it hatched and if I just go a step back, I must say it must had the concept of water before it was hatched. Now if I go that line way back I must say that the chicken zigota just after the moment of conception must had the concept of water. So, it means that the concept of water for the chicken must have been there even before it was concived, that is it must have been in its parents too. If in the creation of the chicken there was nothing else there just the genetic materials from chickem mommy and chicken daddy, then the concept of water must have been in the genes. How did it go there. If it did go there - and the whole previous discussion shows that it must be that way, then there must be a mechanism that writes the life experience of a chicken back into its genes. Here under genes, I mean all the material that convey genetical information to the offspring, so it includes at this moment even epigenetical mechanisms. Now the question is what is that mechanism and how frequently this recording to the genes happens. If jus for the sake of argument now I jump from chicken to men, I would say that for the case of the female parent the writing was done by the parents, because as I know now - and correct me if I am wrong - for a female the eggs are forming during the embrionic stage and after birth the female eggs do not change much. It might be just a dogma, but that is what I know. If I take that dogma seriously than I can say that during the lifetime of the female the eggs do not get any additional - life experience related - info to be stored in the genes of the eggs. For the male it is different, because sper is generated all the time so there is opportunity there to encode life experience into the genes of the sperm and pass it to the offspring. There is the saying that the most important sex organ is the brain, so it is not a strech if I say that there must be a mechanism that behind the scenes writes the rememberings of a male directly to the genetical materials of the sperm and passing it that way.
So, whatever scientists say why sex was developed or evolved, from my point of wiew one aspects of sex is to pass the individual life experience of the male to the offsprings encoded in the sperm somehow.
Here comes the beauty. The life experience info must have been recorded into the DNA. After when the 4 letter DNA alphabet was settled it must have benn recorded with changes in the A, T C, G positions. That means that it is not only the outsider physical environment that can "mutate" the DNA, but it is also the given individual life experience that can change mutate its genetical material. Is it possible to separate these two type of mutations ? I do not know. One for sure both type of mutations had to be such that it could not rake havoc on the protein making mechanism because than the individual would have died - making his own sper cancerous - or its offspring line would have died, making the offspring embryo incapable to born.
Lets look another interesting phenoma. If we go back to our very early childhood, we all can remember that there were people who were apeared nice looking and there were others who apeared ugly looking at the first sight. We were able to do it even if we did not traveled around the village, that is even if we were not exposed to too many faces. How did we know at that time - 2-3 years old - who is good locking and who is ugly ? I must assume that it must have been important for survival that a young individual is capable to make a quick assesment if a creature around him looks nice or ugly. I even theorise that it must be so important that the young individual should not even think about it. Telling otherwise it must be in the genes to know at once if someone is nice or ugly. That also means that there must be a very quick process in the individual - whether it is in the brain or somewhere else - that in a subsecond amount of time we are able to come to the realization if a person is nice or ugly. If it is in the brain, then it must be there by birth. I do not think that at birth there is any significiant info stored in the brain because we would forget it. I rather believe that it must be in almost every cell of the individual and there is a mechanism that "bubbles" that info "UP" to the brain in less than a second. I am willing to risk to say that this info is also embedded in our genes. Just as sophesticated man-made alghorithms are capable to extract vital info for face recognition, I believe that during the "lifetime experience" of an individual such face recognition is done by the brain and the essence of it stored into the genetical material and passed it to the offspring. So, when the moment of "atavism" came - remembering for the info that the ancesters passed via the genes, the brain is notified immadiately on the "reverse channel" that a face in front of us is nice or ugly.
J‡nos
Posted by: Gershom Zajicek M.D.
In your “Back to memory” you cover a huge territory of interesting problems. In order not to get lost lets focus on the memory problem. The newborn has an action memory and lacks an orientation memory which will evolve and become its mind. Action memory is inherited. However it is not inherited as such. When the ovum is fertilized the parental and maternal genomes serve as initial conditions from which action memory will develop. The fertilized ovum, zygote, lives as an independent entity in the oviduct. In other words the zygote is a living entity with resources which will last for a week. It divides several times and becomes a blastocyst which enters the uterine cavity. By now it evolved an action memory which will direct it into the uterine wall where it will spend the next nine months. Without an action memory it will die since its resources last only for a week.
This action memory is stored in the entire blastocyst. If you find it difficult to understand play with my proliferon http://www.what-is-cancer.com/papers/ca1/ca167.htm You plant two CA-zygotes and the action memory emerges when the two CA interact. The proliferon action memory will always settle at an attractor. So where is it stored? The entire proliferon is an action memory. The same applies to the blastocyst.
In order to get resources from the uterine wall the blastocyst needs an orientation memory and grows an interface called placenta which for the coming months will serve as its orientation memory. Since during birth this valuable organ is lost the baby has to grow a new orientation memory.
While the baby inherits from its parents the initial states for growing an action memory, it does not inherit their orientation memories. A renown thinker by the name of Lamarck (1829) believed that acquired characteristics gained during an organism's life can be inherited by its offspring. Today he is in disfavor. Biologists despise him even more than intelligent design. Yet his comeback in the form of neo-lamarckism is imminent. As the genome becomes more and more complex Lamarck’s ideas gain in importance, http://www.what-is-cancer.com/paper...ofthegenome.htm
Posted by: Gershom Zajicek M.D.
In previous chapters I discussed some concepts which ought to be implemented in a CA model of robot intelligence. Some, like emotion or empathy seem difficult to handle, nevertheless their representations may be relatively simple. By representation I mean a mapping from a phenomenon to a CA system. Its adequacy will be judged whether system behavior meets our expectations.
An intelligent CA system has the following attributes:
1. It consists of at least two interacting processes (CA)
2. The system is dynamic, always seeking an attractor.
2a. The system’s configuration at an attractor is called the system’s solution.
2b. The system’s purpose (teleonomy) is to create an optimal solution. In other words of all the potential solutions the system faces it will create the most optimal.
3. The stem-process controls the system and when necessary adds to it transitional processes. It lives as long as the system does, and when it dies the system dies as well.
3a Transitional process is created by the stem-process and survives less than the stem-process does.
4. Each process state is an action memory which serves as initial condition for:
4a The next process state.
4b Transitional processes at the time of their creation by the stem-process.
5 The behavior of the system is driven by external (environmental) change.
5a Sensation: Is an external change that perturbs the system and modifies its action memory.
5b The system “understands” the external message (perturbation) only when creating a new solution.
5c The new solution is the memory of the event (message) which perturbed the system.
5d In other words if the system returns to its pre-perturbation solution, it did not understand the message and forgot it.
6 Orientation memory: Is an action memory modified by an external (environmental) change.
7. Emotion: Is a change in system’s behavior initiated by its present state.
Proliferon http://www.what-is-cancer.com/papers/ca1/ca167.htm
Action memory http://www.what-is-cancer.com/paper...ctionmemory.htm
Orientation memory http://www.what-is-cancer.com/paper...ationmemory.htm
Emotions http://www.what-is-cancer.com/paper...ty/emotions.htm
Sensations http://www.what-is-cancer.com/paper.../sensations.htm
Posted by: Enexseenge
How can we be sure that we know the whole scope of "changes" that take place..
You give the example of raising a hand, quite obvious yes...
But could there be even finer changes detected... by fine i mean REALLY fine... super fine...
the thing is, we never stand still..
How about death? when you see your friend dead do you have emotional reaction because you cannot create that state within you, there for you are in unknown area and have an emotional outburst? (Seems to me that whenever the brain enters into unknown territory it utilizes more "loose" abstractions, such as emotion, which can act as a base from which to structure things)
Posted by: Gershom Zajicek M.D.
When I raise my hand the organism responds at all levels.
1. In the extremity and in my brain blood flow is faster, in the intestine it is slower the heart pumps faster, breathing changes and so on. The tone of other muscle is adjusted to maintain the posture of my body.
2. Cells in organs adjust their metabolic activity. In the hand itself metabolism is accelerated, and in the intestine it is slower.
3. Even the smallest constituents (superfine as you say} participate in this hand raising
Indeed we never stand still and all our constituents continually stream (change). All these myriad changes are coordinated to maintain the organism in a multidimensional equilibrium called homeostasis. The organism is a multidimensional strange attractor.
We are not aware of these changes. The body signals to the mind only when something goes wrong.
When we face death, we suffer the loss of a dear person, however we are unable to even remotely grasp what it is to be dead.
http://www.what-is-cancer.com/paper...sstreaming.html
Posted by: Enexseenge
okay... I love that "multidimensional strange attractor"..
Now here is what i was asking,
You were giving the example of the mirror neurons, if my friend raises his hand then i become aware of it within the structure of my mirror neurons and their activation...
I was wondering, are these mirror neurons, or similar versions of neurons, receptive to subtleties that we our selves would be unaware of, for example, the metabolic changes within one who we observe?
I should have been more specific in my original question.
Thank you for your input, good day to you.
Posted by: Gershom Zajicek M.D.
There are two kinds of communication between individuals, verbal and non-verbal. The first is obvious. When I say to you “what about a juicy steak?” I activate in you myriad of metabolic processes which prepare themselves for the virtual steak. By non-verbal communication I can activate in you (myriad) healing processes without us being aware of it.
More on this in my chapter on Shamanism
http://www.what-is-cancer.com/paper...troduction.html
Posted by: Gershom Zajicek M.D.
Introduction: http://www.what-is-cancer.com/paper...ntelligence.htm
Tolerance: http://www.what-is-cancer.com/papers/ca1/ca179.htm
CA mood: http://www.what-is-cancer.com/papers/ca1/ca180.htm
Robot behavior: http://www.what-is-cancer.com/papers/ca1/ca181.htm
Robot character: http://www.what-is-cancer.com/papers/ca1/ca182.htm
Robot memory: http://www.what-is-cancer.com/papers/ca1/ca183.htm
Swarm intelligence: http://www.what-is-cancer.com/papers/ca1/ca184.htm
Beehive: http://www.what-is-cancer.com/papers/ca1/ca185.htm
Posted by: Gershom Zajicek M.D.
http://forum.wolframscience.com/sho...d=3767#post3767
Complexity
Complexity of life
The complexity of a living cell cannot be generated with a simple program
http://www.what-is-cancer.com/paper...ityofliving.htm
No living entity known today generates its complexity from scratch.
http://www.what-is-cancer.com/paper...entityknown.htm
Law of conservation of minimal complexity
http://www.what-is-cancer.com/paper...lcomplexity.htm
The cell is the atom of life
http://www.what-is-cancer.com/paper...ecellisatom.htm
The complexity of the genome
http://www.what-is-cancer.com/paper...ofthegenome.htm
The complexity of a living cell is ordered
http://www.what-is-cancer.com/paper...xityordered.htm
The complexity of life is oriented
http://www.what-is-cancer.com/paper...dcomplexity.htm
Streaming complexity
http://www.what-is-cancer.com/paper...gcomplexity.htm
Wisdom of the Body (WOB)
http://www.what-is-cancer.com/paper...omofthebody.htm
Model of the Wisdom of the Body (WOB)
http://www.what-is-cancer.com/paper.../modelofwob.htm
Emergence of the Wisdom of the Body (WOB)
http://www.what-is-cancer.com/paper...rgenceofwob.htm
WOB and cell death
http://www.what-is-cancer.com/paper...ndcelldeath.htm
Autopoiesis
http://www.what-is-cancer.com/paper...autopoiesis.htm
Holon - A complexity unit
http://www.what-is-cancer.com/paper...plexityunit.htm
The hierarchical arrangement of our organism into attractors is entirely arbitrary
http://www.what-is-cancer.com/paper.../attractors.htm
Epigenesis in Cellular Automata
http://www.what-is-cancer.com/paper...genesisinca.htm
A simplified model of protein assembly
http://www.what-is-cancer.com/paper...elofprotein.htm
Action memory of a blastocyst
http://what-is-cancer.com/papers/ca...yblastocyst.htm
Chaos
Chaos does not exist as such in Nature
http://www.what-is-cancer.com/paper...oesnotexist.htm
Life is not chaotic
http://www.what-is-cancer.com/paper...snotchaotic.htm
Chaos and creativity
http://www.what-is-cancer.com/paper...dcreativity.htm
EEG and Chaos
http://www.what-is-cancer.com/paper...eegandchaos.htm
Heraclitus and boundary chaos
http://what-is-cancer.com/papers/ca...oundedchaos.htm
Complexity attributes
Complexity spectrum
http://www.what-is-cancer.com/paper...ityspectrum.htm
Properties of a complex system
http://www.what-is-cancer.com/paper...mplexsystem.htm
The Complexity Demon
http://www.what-is-cancer.com/paper...lexitydemon.htm
Transfinite complexity
http://www.what-is-cancer.com/paper...ecomplexity.htm
Optimality is a property of a process ensemble
http://www.what-is-cancer.com/paper...isaproperty.htm
Simplification
http://www.what-is-cancer.com/paper...plification.htm
Information theory and complexity
http://what-is-cancer.com/papers/ca...ationtheory.htm
Prerequisites for biological modeling
http://www.what-is-cancer.com/paper...rbiological.htm
Robot psychology
Robot intelligence
http://www.what-is-cancer.com/paper...ntelligence.htm
Soul and complexity
http://www.what-is-cancer.com/paper...dcomplexity.htm
Memory of a complex system
http://www.what-is-cancer.com/paper...ryofcomplex.htm
Action memory
http://www.what-is-cancer.com/paper...ctionmemory.htm
Orientation memory
http://www.what-is-cancer.com/paper...ationmemory.htm
Emotions
http://www.what-is-cancer.com/paper...ty/emotions.htm
Metaphysics
Bergson and Complexity
http://www.what-is-cancer.com/paper...dcomplexity.htm
Complexity and free will
http://www.what-is-cancer.com/paper...andfreewill.htm
Metaphysics and complexity
http://www.what-is-cancer.com/paper...dcomplexity.htm
Popper and complexity
http://www.what-is-cancer.com/paper...dcomplexity.htm
The first universal computer
http://www.what-is-cancer.com/paper...salcomputer.htm
The illusion of time
http://www.what-is-cancer.com/paper...usionoftime.htm
Relative time
http://www.what-is-cancer.com/paper...elativetime.htm
The issue here is the universality of NKS
http://www.what-is-cancer.com/paper...issuehereis.htm
Nature is neither complex nor simple
http://www.what-is-cancer.com/paper...thercomplex.htm
Popper and complexity
http://www.what-is-cancer.com/paper...dcomplexity.htm
CA and Aristotle’s Four Causes
http://www.what-is-cancer.com/paper...ndaristotle.htm
Intelligent design and complexity
http://www.what-is-cancer.com/paper...igentdesign.htm
Phenomenology of complexity
http://www.what-is-cancer.com/paper...fcomplexity.htm
Embodiment
http://www.what-is-cancer.com/paper.../embodyment.htm
Phenomenology of Artificial Intelligence
http://www.what-is-cancer.com/paper...fartificial.htm
Evolution of Intelligent Design
http://what-is-cancer.com/papers/ca...intelligent.htm
Randomness
http://www.what-is-cancer.com/papers/ca/randomness.htm
Posted by: Gershom Zajicek M.D.
You sit in Nature and observe how it changes. You forget all what they told you about it. Simply observe how nature changes. Some call this state mindfulness. You will notice the appearance of different structures, or species, and realize that despite an immense variability many attributes of life are conserved among the different species, e.g. number of limbs, or some basic metabolic pathways.
You exist in the Now, and yet wonder whether these structures have a history. You turn to the sages, and listen to their stories (theories) of evolution:
1. Genesis chapter 1 (Creationism)
2. Intelligent design (ID)
3. Neo-Darwinism
4. Lamarckism
5. Gaia
Once you turn to history you face some difficult questions. Evolution of what? Is it an evolution from the smallest to the biggest? Or do evolving entities become more complex? None of that. You lack a yardstick for measuring evolution. Not all species participated in evolution, like bacteria which never bothered to evolve. Or cockroaches and ants that stopped evolving eons ago. So what is the exact meaning of the current buzzword, “Survival of the fittest”? Are bacteria more fit than us, or the cockroaches? The only independent indicator that life evolved is fossil evidence. Geological layers may serve as crude time estimates into the past and they indicate that life in different epochs varied. Yet what drives this change is still unknown.
Our ancestor was a primordial microorganism which evolved into three phyla (kingdoms): archea, bacteria, and eukaria. We evolved from the latter. Actually we are fortunate that the other two phyla did not evolve further since they keep us alive. They initiate the complex food chain in which we participate. They are its initial state, and if eliminated the entire food chain including us would disappear.
Nobody observed evolution in action and the theories lack any predictive value. They are no more than just so stories with some convincing arguments. To me the most interesting is the evolving Gaia.
Further reading:
Evolution theory from a new perspective
http://www.what-is-cancer.com/paper...erspective.html
Decline of Darwinism
http://www.what-is-cancer.com/paper...ismDecline.html
Darwinism: A crude model of Life driven by Randomness
http://www.what-is-cancer.com/paper...s.htm#darwinism
The hypocrisy of Neo-darwinism
http://www.what-is-cancer.com/paper...hypocrysiof.htm
Intelligent design and complexity
http://www.what-is-cancer.com/paper...igentdesign.htm
Intelligent design and swarm intelligence
http://www.what-is-cancer.com/paper...ignandswarm.htm
The hierarchy of living complexity
http://www.what-is-cancer.com/paper...gcomplexity.htm
Facilitated variation
http://www.what-is-cancer.com/paper...edvariation.htm
Facilitated variation and intelligent design
http://www.what-is-cancer.com/paper...igentdesign.htm
The evolution of Gaia
http://www.what-is-cancer.com/paper...utionofgaia.htm
Posted by: janos
You write: " Not all species participated in evolution, like bacteria which never bothered to evolve. Or cockroaches and ants that stopped evolving eons ago."
I just saw a PBS documentary yesterday - Old Science :) - where they mentioned that the venemosity of small creatures is a recent phenomena - even for ants.
That means for me that all creatures are evolving, but for some the speed of evolution is very small. That speed might related to the number of genes or number of basepairs we have in our DNA. /For bacteria, that does not have DNA the length of their RNA might be a measurement/
If the length of the DNA is too short then the state space for the variations in the DNA might not be enough to support evolution. In that case there are just variations without evolution. I do not know if the RNA of a bacteria is too short in this regard or not. I guess for some bacteria it is true but our presence here shows that for other bacteria it was not true, so they evolved into more complex organisms.
J‡nos
Posted by: Gershom Zajicek M.D.
Evolution is generally defined as a gradual process in which something changes into a more complex or better form. It obviously does not apply to the history of life which does not become more complex or better. In other words evolution implies that change occurs in a certain direction, like a vector which is impossible to prove since we lack a measure of evolution. So why not call it an ongoing process manifested by change?
Even DNA length cannot serve as a measure of evolution . For instance amebas have a genome 200 times as large as ours, and onion has more than 12 times as much DNA as we. http://www.hno.harvard.edu/gazette/...2.10/onion.html
Let’s return to our home base, Wolfram’s book. Look at page 282 where the histories of class-4 CA are displayed. Some structures disappear, other remain permanent. You might conclude that the fittest survive! However Wolfram’s environment does not select anything. It may seem as if they evolve, yet you lack a yardstick to measure evolution . So why insist that it is an evolution while in reality it is an ongoing change? The same applies to Neo-Darwinism
http://www.what-is-cancer.com/paper...ntroduction.htm
Posted by: green_meklar
Evolution is generally defined as a gradual process in which something changes into a more complex or better form.
As far as I know, evolution has nothing to do with 'more complex' or 'better' but only 'better suited to its environment', which is quite a different thing. Evolution does not run towards any particular 'goal' unless the environment it is occuring in stays the same.
Posted by: Gershom Zajicek M.D.
I agree with you that how evolution ought to be defined. Please consider two dictionaries:
Hyperdicitonary
[n] a process in which something passes by degrees to a different stage (especially a more advanced or mature stage); "the development of his ideas took many years"; "the evolution of Greek civilization"; "the slow development of her skill as a writer"
[n] (biology) the sequence of events involved in the evolutionary development of a species or taxonomic group of organisms
http://www.hyperdictionary.com/sear...efine=evolution
Answers.com
• A gradual process in which something changes into a different and usually more complex or better form. See synonyms at development.
a. The process of developing.
b. Gradual development
http://www.answers.com/Evolution?gw....0.453&method=3
Posted by: Gershom Zajicek M.D.
Cellular Automata http://cellularautomat.blogspot.com/
Streaming Organism http://streamingorganism.blogspot.com/
Cancer Statistics http://cancer-statistics.blogspot.com/
Cancer and Wisdom of the Body
http://what-is-cancer.blogspot.com/
Here are the Blog feeds. Place them in your feed reader for additional news
Cancer and Wisdom of the Body
http://feeds.feedburner.com/CancerAndWisdomOfTheBody
Cellular automata in Bio-medicine
http://feeds.feedburner.com/Cellula...aInBio-medicine
Streaming Organism
http://feeds.feedburner.com/StreamingOrganism
Feedreader download
http://www.feedreader.com/download
Posted by: Gershom Zajicek M.D.
Watch the following experiments:
Chapter 4
Two interacting mortal CA fuse into an immortal chaotic CA. The chaotic CA then generates chaotic and non chaotic immortal progeny (attractors).
Chapter 5
CA interacts with a barrier
http://cellularautomat.blogspot.com/
http://www.what-is-cancer.com/papers/ca/ca2.htm
Posted by: Gershom Zajicek M.D.
A collection of articles on robot psychology illustrates some elementary functions which might be essential for controlling robot behavior. http://www.what-is-cancer.com/papers/ca/complexity.htm
Recently I discovered Hans Jonas’ “The phenomenon of Life” which provides a deep insight into this subject. His definition of emotion is important and highly relevant to the design of a robot mind.
According to Jonas: Plants, animals and the human animal display an ascending development of organic functions and capabilities. The emergence of the human mind does not mark a great divide within nature but elaborates what is prefigured throughout the life-world. The organic even in its lowest forms prefigures mind, and the mind even on its highest reaches remains part of the organic.
In other words, the basics of the human mind are inherent in simple organisms like an ameba or a paramecium. If you capture the essence of their mind you might construct on it artificial mind functions.
Jonas: Three characteristics distinguish animal from plant life: motility, perception , and emotion (p. 99). All three manifest a common principle. First we ought to realize that environment and the organism are contiguous. In plants, chemicals are directly exchanged between environment and organism. Since immediacy of satisfaction is concurrent with the permanent organic need, in this condition of continuous feeding there is no room for desire. Plants lack emotions.
Plants continually synthesize inorganic matter directly into organic compounds, while animals depend on organic matter.
Jonas: The animal feeds on existing life, continuously destroys its mortal supply and has to seek elsewhere for more. The appearance of directed long-range motility thus signifies the emergence of emotional life. Greed is at the bottom of chase, fear at the bottom of flight. If appetition is the basic condition of motility, pursuit is the primary motion. Fulfillment not yet at hand is the essential condition of desire. Emotion implies distance between need and satisfaction.
Emotions are embodied http://www.what-is-cancer.com/paper.../embodyment.htm
These excerpts illustrate the novelty of Jonas’ approach. His philosophy of biology is based on Phenomenology:
http://www.what-is-cancer.com/paper...fcomplexity.htm
http://www.what-is-cancer.com/paper...fartificial.htm
References
Hans Jonas The Phenomenon of Life - Toward a Philosophical Biology
Northwestern University Press Evanston Ill 2001
http://books.google.com/books?hl=en...ogy%22+#PPP1,M1
Posted by: Gershom Zajicek M.D.
Scientific discoveries indicate that life evolved on earth starting from a single cell and emerged into the life (nature) in which we exist. Yet what was it evolving to? Is it more complex than before? Or is there more life today than before? What is the measure of this evolution? At one time it seemed as if life evolves from the smaller to the bigger until the dinosaurs disappeared. The human is obviously more complex than a bacterium, nevertheless unicellular organisms contribute significantly to the earth biomass. Since they have obviously “evolved less” than us why are they still with us? Shouldn’t they be replaced by the “more evolved”?
More disturbing thoughts were published here previously:
http://www.what-is-cancer.com/paper...ntroduction.htm
Let’s turn to a remarkable book , “The phenomenon of Life” by Hans Jonas (1), for some new ideas on this issue. Throughout evolution the higher depends on the lower. The “fittest” may still survive as Neo-Darwinists claim, but depends more and more on the lower. According to Jonas:” {There is a] dependence of each higher on the lower, [and a] retention of the lower in the higher.
Life evolves within food chains. A food chain is defined as: A succession of organisms in an ecological community that constitutes a continuation of food energy from one organism to another as each consumes a lower member and in turn is preyed upon by a higher member. (Answers.com). At the origin of the food chain are algae, cyanobacteria and plants, which polymerize organic matter from inorganic molecules. Initially food chains consisted of cyanobacteria. Then came algae and finally the plants. They paved the way for other organisms which depend solely on organic matter. This is why evolution retains a “Dependence of each higher on the lower”. Life (us) cannot exist without the lower.
The food chain may be regarded as an elementary process in a super organism called Gaia, which is the set of all food chains on earth. Gaia is a web of food chains. It is Gaia which is evolving and we evolve in it.
http://www.what-is-cancer.com/paper...utionofgaia.htm
Yet where does Gaia evolve to? Jonas suggests that evolution is a progressive freedom of action. This certainly applies to individual organisms. The animal feeds on existing life, continuously destroys its mortal supply and has to seek elsewhere for more. The appearance of directed long-range motility thus signifies the emergence of freedom of action.
Freedom of action in the broader sense is a manifestation of Gaia’s optimality. It may serve as an indicator where Gaia is heading to.
http://www.what-is-cancer.com/paper...y/robotmind.htm
References
1. Hans Jonas The Phenomenon of Life- Toward a Philosophical Biology
Northwestern University Press Evanston Ill 2001
Posted by: Gershom Zajicek M.D.
Can machines think? Not yet, however soon they will. Place a powerful computer (network) with the Google knowledge base behind a screen, interrogate it and you won’t be able to distinguish its response from that of a human. By the way, you interrogate the computer using text formatted linguistic input. This is the essence of the Turing test. With Google at hand, soon it will be even smarter than you.
Turing believed that appropriately programmed computer can think. Or better the computer simulates thinking which cannot be distinguished from your thinking. The digital computer does not posses intelligence, it simulates it. Some believe that soon it will simulate a mind or even consciousness. All you need is a powerful computer, and since computer hardware develops exponentially (Moore’s law), soon conscious computers (agents, robots) will hop around.
This wishful thinking illustrates yet another shortcoming of AI (Artificial Intelligence) reasoning, Anthropomorphism. The other, “Cartesian Slumber”, was discussed in a previous chapter.
http://www.what-is-cancer.com/paper...puterscando.htm
Following the Creator who created us in His image, AI seeks to create machines in the human image. The only meaningful intelligence is human. Which is the root of Turing’s test, which tests a dis-embodied intelligence. What about a Turing test which allows us to talk to the computer? Since voice reveals emotions, we might easily spot the culprit (simulator). Will the future computer simulate emotions? Since emotions require embodiment, the question has to be rephrased, how to create an embodied zombie which will fake (simulate) emotions? Yet another anthropomorphism.
Is swarm intelligence a real intelligence or a misnomer? Does an ameba possess an intelligence despite not being able to convey it to us? AI would dismiss such speculations as nonsense. Let’s turn therefore to Hans Jonas’ “The phenomenon of Life” (1): Plants, animals and the human animal display an ascending development of organic functions and capabilities. The emergence of the human mind does not mark a great divide within nature but elaborates what is prefigured throughout the life-world. The organic even in its lowest forms prefigures mind, and the mind even on its highest reaches remains part of the organic.
In other words, the organic even in its lowest forms prefigures intelligence, which shapes also the human intelligence. AI ought to study first the intelligence of an ameba. Simulate it and model it. This basic model may then serve as an initial state from which intelligence, and even consciousness might emerge. Such an endeavor requires a new kind of programming tool different from what is known today. It might look like the one which I apply in my CA studies. You plant two zygotes which evolve into a stable system with emerging and unpredictable properties.
http://www.what-is-cancer.com/papers/ca1/ca163.htm
Robot mind: http://www.what-is-cancer.com/paper...y/robotmind.htm
References
1. Hans Jonas The Phenomenon of Life- Toward a Philosophical Biology
Northwestern University Press Evanston Ill 2001
Posted by: Gershom Zajicek M.D.
“When man first began to interpret the nature of things – and this he did when he began to be man – life was to him everywhere, and being the same as being alive. Animism was the widespread expression of this stage, hylozoism (2) one of its later, conceptual forms.” Thus begins Hans Jonas’ first essay in his book entitled “The Phenomenon of life” (1). Most of what we encounter on the surface of earth is intimately intertwined with the dynamics of life. “modern thought which began with the Renaissance is placed in exactly the opposite theoretic situation. Death is the natural thing, life is the problem” (p.9)
Explanation of life has to be in terms of the lifeless, this is what modern biology is about. “Life’s place in this world has shrunk to that of the organism” (p. 11). In order to understand life it has to be reduced to non life. “Our thinking today is under the dominance of death” (p.12) “Panvitalism” of the past was replaced by “panmechanism.”
The science of the (dead) matter is reaching an impasse, since it lacks concepts and tools to understand our non-linear surroundings which are intimately affected by life. Some call this deviation from traditional science as chaotic, which reflects their clouded vision. Chaos was first applied to the weather since modern science fails to account how life shapes it. Any process which involves life, e.g., economy, stock market or the web cannot be tackled anymore by the traditional scientific concepts. We need a new approach whose philosophy is outlined in Jonas’ book. Back to panvitalism. First we ought to explore our backyard called Gaia, our super organism in which we exist. Then we ought to broaden our view and “revive” the dead universe which harbors vast amounts of life, known as panspermia, some of which is entering our atmosphere every second.
This is the main theme of the present thread. It started with the inadequacy of the concept of randomness which is the brainchild of the “science of the dead|”
http://www.what-is-cancer.com/papers/ca/randomness.htm
Then came short discussions of various concepts of complexity:
Life does not generate complexity from scratch
http://www.what-is-cancer.com/paper...entityknown.htm
The cell is the atom of life.
http://www.what-is-cancer.com/paper...llistheatom.htm
Gaia
http://www.what-is-cancer.com/paper...ismDecline.html
Evolution has a meaning only in terms of Gaia
http://www.what-is-cancer.com/paper...utionofgaia.htm
Phenomenology of complexity
http://www.what-is-cancer.com/paper...fcomplexity.htm
And more:
http://www.what-is-cancer.com/papers/ca/complexity.htm
References
1. Hans Jonas The Phenomenon of Life- Toward a Philosophical Biology
Northwestern University Press Evanston Ill 2001
hylozoism: The philosophical doctrine holding that all matter has life, which is a property or derivative of matter. (Answers.com)
Posted by: Gershom Zajicek M.D.
Three kinds of complex systems were introduced in the previous section:
1. The whole is the sum of its parts. (Reductionism)
2. The whole is more than the sum of its parts (Aristotle)
3. The whole controls its parts. (Life) These systems obey the allometric law , or power law, which describes the relationship between the whole (W) and its parts (p). Like in the following equation: p = a * W ^ b or Log[p] = Log[a] + b * Log[W].
The three types may be regarded as stages in the evolution of scientific discourse, aimed at understanding reality.
1. Atom and force are the basic concepts of Cartesian reductionism according to which the whole is the sum of its atoms whose properties are the same as that of the whole. The same applies to force of the whole which is the sum of the forces of its parts. Essentially, chemistry is reducible to physics, and biology is reducible to chemistry and physics,
However in the real world this simple relationship does not hold.
Galileo discovered the law of Free Fall, according to which acceleration of gravity g equals 9.8 m/s2 and is the same for all bodies. Yet daily experience teaches that the free fall of bodies varies. Galileo’s laws ignore the context in which they are applied. The context “distorts” (perturbs) the observed law randomly, and the deviation of the observed from the postulated is regarded as an error. The error may be reduced by repeating the experiment many times, whereupon measurements will approach the “true” limit postulated by the Law. This is the essence of the reasoning of physics. Its metaphysics was laid down by Plato. Laws inhabit the realm of ideas and represent the reality while the observed phenomena are distorted.
2. Aristotle realized the whole is more than the sum of its parts. The behavior of objects can be attributed to four kinds of explanation, which Aristotle called causes.
http://www.what-is-cancer.com/papers/ca/ca47.htm
During the 19th century physical laws where applied to bio-medical reasoning introducing the error concept (or randomness) to medicine. Disease is defined as an error while the normal is health. This notion is highlighted by the Genetic fatalism. Genes are the blueprint of our healthy organism and when they mutate (change) we are sick. The task of the physician is to repair bad genes or even replace them.
Soon it became evident that many people with mutated genes are actually healthy. In order to save the reductionist view of disease geneticists conjured new genetic terms, and theories which explain why some people with mutated genes are healthy. They are discussed elsewhere
http://www.what-is-cancer.com/paper...tsgenetics.html
Geneticists fail to realize that the context in which they observe disease cannot be ignored anymore. The context is our organism in its entire complexity, and it cannot be reduced, or simplified like it is done in physics. The organism may make us sick with “good” genes and keeps us healthy with mutated genes.
3. Since the organism as a whole controls its parts new mathematical tools are needed in order to untangle its sophistication. All the nice mathematical tools applied in physics are of little help since they were designed to handle isolated and ideal situations devoid of any context, while processes in the organism are neither isolated, nor ideal and above all their context cannot be ignored anymore.
Cellular automata are the first step in the new direction. The main NKS message is that the iteration of simple CA may create any desired complexity. Which is still a reductionist approach. Yet this it not enough . Above all we need tools to simplify complexity without losing its essence which ought to be Wolfram’s concern. Twenty years ago he created the Mathematica package in order to explore the NKS ideas. Time has come for a new kind of Mathematica software, which will enable the end user to simplify complexity without losing its essence.
His name of the game is symbolic computing, which served for creating Mathematica. Why not start the computing from complex blobs obeying the allometric law, and simplify them more and more . . . ?
The allometric law points to a new era in science and philosophy. Cartesian reduction is dead, long live phenomenology.
Posted by: Philip Ronald Dutton
"Time has come for a new kind of Mathematica software, which will enable the end user to simplify complexity without losing its essence." -- previous post
If some form of complexity yields itself to some form of simplicity then where is the complexity? This is symptomatic of the classic "meta-language" problem.
Consider the question of detecting when information is transferred: if you have an answer then you are talking in the meta-realm. The observer is making the decision about what is simple and what is complex. The objects or systems themselves do not ever know if they are simple or complex.
Consider the output of all any of the first 256 Cellular Automaton: they are "mechanical" and mundane. The output is then interpreted by an observer to be class 1 or 2 or 3 or 4.
Perhaps you can simplify and/or repeat your definition of the essence of complexity?
Thank you.
Posted by: Gershom Zajicek M.D.
You ask for the nearly impossible. Nevertheless you might benefit from going through some arguments in this thread which are summarized here:
http://www.what-is-cancer.com/papers/ca/complexity.htm
Then turn to the NKS book only to find out that even Master Wolfram did not define it. So let’s try.
What a newborn baby perceives is a change amidst a huge mess. Fortunately it is equipped with instincts and prior (or a priori) knowledge called here wisdom of the body (WOB) with which it simplifies this mess to meet its needs. For the baby this mess is extremely complex, it is the hallmark of complexity. Yet since the baby lacks a mind which it will develop later on, “complexity” (the concept) is meaningless to it or better not relevant. After all it has the necessary tools to make this mess meaningful.
Some babies grow to become physicists whose main concern is how to harness this change in order to build machines. In order to proceed they adopt the following concepts: The whole is the sum of its parts, every change has a unique cause. The context in which change occurs, is random and negligible. Or better one may always define a context in which the cause and effect relationship will hold. They are assisted by a special language, mathematics, with which these concepts may be studied rationally.
When physics confronted life (Descartes) it regarded it as a special kind of machine, which has a soul. The latter you need for religious purposes and since soul is not a scientific entity (not even a context) it can be ignored. Yet already Aristotle claimed that this soul controls the machine (organism) and therefore ought to be regarded as its context.
For the next centuries complexity was hardly an issue. Since the whole equals the sum of its parts, you may always reverse engineer it and discover its structure. Then came two sobering discoveries:
1. Godel’s incompleteness theorems revealed that even mathematics is incapable of encompassing any complexity. “any theory capable of expressing elementary arithmetic cannot be both consistent and complete”.
http://www.answers.com/topic/g-del-...teness-theorems
In order to make a system “complete” you need additional statements from outside the system which I regard as the context of this particular system.
2. A three body system whose parts obey Newton’s laws yet the system as a whole may become chaotic.
I regard a system as complex when the whole is more than the sum of its parts and it cannot be understood by dissecting it into its elements. The parts interact and it appears as if the whole controls them. Yet it lacks any central control.
A complex system may be quite small, like my two CA system called proliferon.
http://www.what-is-cancer.com/papers/ca1/ca167.htm
Posted by: Gershom Zajicek M.D.
Most attributes of complex systems studied by the exact sciences may be approximated by the Gaussian (normal) distribution. Asymmetric or skewed distributions are transformed so as to make them normal, e.g., the log-normal distribution. On the other hand life generates only skewed distributions. Hitherto those distributions were also transformed so as to make them Gaussian. The asymmetric tails were regarded as noise which ought to be reduced by an appropriate transformation.
The Gaussian distribution (model) is generated from random phenomena, and since nothing in life is random the Gaussian model fails to capture some essential attributes of life. http://www.what-is-cancer.com/papers/ca/randomness.htm
Life is manifested by the allometric law with asymmetric tails.
http://www.what-is-cancer.com/paper...icomplexity.htm
After a century of ignoring these tails as random noise, developers encounter this phenomenon in the Internet, and since it is bad for business, it is unpleasant. Particularly since the area under the long tail is larger than the body that wags it. Hitherto you believed that the distribution-body harbors most of your customers only to discover that they hide in the long tail. The phrase “Long Tail” was coined by Chris Anderson, and highlighted by an influential essay by Clay Shirky, "Power Laws, Weblogs and Inequality" (February 2003) http://en.wikipedia.org/wiki/The_Long_Tail.
The long tail is a manifestation of the allometric law (a power law) which is an expression of life, and since the Internet is a living system it behaves allometrically. Thus, in order to improve your business, you ought to abandon the outdated Gaussian distribution, and turn your attention to life. You cannot generate a long tail from random elements, since phenomena generating long tails are creative. My CA models are such creative constructs which generate long tails.
The long tail carries with it a sad message which led some to conclude that Web 2.0 is dead. On one hand the web is flooded with information, yet most of it is redundant, irrelevant, and misleading. Suppose that you fell ill with cancer. You turn to the experts and get treated. Nevertheless you worry. They talk about probabilities of cure, while you want a definite answer. What about alternative cancer treatments? Google spits out 10,700,000 links within 0.09 seconds. You start reading and reading only to encounter the non-relevant. The distribution of these links forms a body with a long tail. The first n pages consist of the body, while the creative links are distributed somewhere in the long tail.
More on cancer: http://www.what-is-cancer.com/
The optimists hope to remedy this with new search engines of Web 3.0 .Yet the future lies in Web-Bionics, whose basic ideas were introduced in this thread.
Posted by: Gershom Zajicek M.D.
Reading how Wolfram muses http://blog.wolfram.com/2007/09/my_...unive.html#more
is always exciting since musing is controlled (manipulated) by Muses. My hobby is hunting for ideas, and Wolfram’s blog is a fruitful and promising field for exciting inspirations. I am particularly intrigued how he handles concepts so dear to physicists, e.g., space and time.
“There's not just our own physical universe to think about, but the whole universe of possible universes.” Says Wolfram. Suppose that the rules underlying these universes are simple one might be able to search the universe of all possible rules, and find our own physical universe.
Wolfram: “Physicists often like to think that they're dealing with the most fundamental kinds of questions in science. But actually, what I realized back in 1981 or so is that there's a whole layer underneath.” So what is this layer underneath? A network of interacting programs in which space and time do not apply. Such a network does not exist in a space. “There is not a ‘space’ there but a bunch of points.” Which are actually connections. The programs exchange pieces of the network. “And in general each possible sequence of rule applications might correspond to a "different branch of time".”
“. . these networks with almost nothing "built in" somehow generate behavior that corresponds to gravitation in physics.” In other words, space and time do not exist as such, they emerge and so do the laws of physics.
“Another thing that seems alien is the idea that our whole universe and its complete history could be generated just by starting with some particular small network, then applying definite rules.”
What a pleasant heresy! Indeed Wolfram implies that many physicists dislike his combinatorial approach of a “causal network.” Dislike? They probably hate it and Wolfram consoles himself by : “They haven't quite reached the level of abstractness that I'm at.” For me Wolfram is on a “colliding course” with biology. He approaches us biologists! I call his causal network Wisdom of the Body (WOB). A set of interacting processes each with its own time, which I call biological, as opposed to the chronological time of physics. Its properties where discussed in this thread. http://www.what-is-cancer.com/paper...lexityFrame.htm
Why hunt for universes when you have me. A finite and bounded universe, infinitely complex. Why not search for the “causal network” underlying me? which might be the secret of life.
Posted by: Gershom Zajicek M.D.
Gaia is a super-organism embracing all life on earth. Gaia is the joint manifestation of life on earth and behaves like any other living creature. It is controlled by its wisdom (WOB). Gaia involves the Earth's biosphere, atmosphere, oceans, and soil.
http://www.what-is-cancer.com/paper...utionofgaia.htm
Like any other living creature, Gaia has an input and output, and maintains an equilibrium (homeostasis).
The input is solar energy and cosmic dust which falls through the atmosphere. Gaia’s output, or graveyard, is the earth crust. Solar energy is converted to organic matter which is transferred through multiple food chains. Dying organisms and organic matter find their way to the oceans where they sink and join the earth crust as dead rocks (graveyard). In other words only life is capable to bind the organic matter which was initiated by the solar energy and later on becomes a dead rock. Life is the sole grave digger on earth and controls Gaia’s output.
Ever since it was formed Gaia maintained a steady state in which input = output. Actually Gaia evolved maintaining a steady state. Yet it’s peaceful existence was disrupted by the industrial revolution (18th century), which gained access to a new energy source (fossils). The total energy input rose and input > output. The rapid rise in the production of fossil energy caught Gaia unprepared. In order to establish a new steady state Gaia ought to raise its output, and mobilize more grave diggers.
First Gaia raises its temperature. Ice melts and ocean surfaces increase. Since life generally occupies the surfaces, new live forms find their place in the sun. Species with better grave-digging capabilities, are promoted, and the less efficient eliminated. Species variety declines. The rising temperature raises the metabolic rate of each individual, and it binds more organic matter. The overall turnover of food chains rises so that more live forms die. Gaia’s grave-digging properties improve (and output rises).
The neo-liberal capitalism thrives on growth and ever rising energy production, which raises Gaia’s input. Yet our super-organism is determined to survive the folly of the human race. It is capable to raise its temperature (fever) until we all end in Gaia’s grave yard. Leaving behind insects and microorganisms which are less sensitive to heat and lack any intention to burn fossil energy. Then output will match input and Gaia’s steady state finally restored.
There is a simple moral to this story. Gaia is extremely complex. Nevertheless you don’t have to untangle (simplify) its complexity. It suffices if you monitor (control) it’s inputs and outputs. Which applies to any living organism maintaining steady state.
http://www.what-is-cancer.com/paper...ewmedicine0.htm
Posted by: Gershom Zajicek M.D.
According to Moore's Law the number of transistors that can be inexpensively placed on an integrated circuit is raising exponentially, doubling approximately every two years.
http://en.wikipedia.org/wiki/Moore's_law
Apparently Moore’s exponential function approaches its limit. Soon it will be impossible to pack more transistors into an integrated circuit.
It is striking that software did not evolve so fast. According to Wirth’s law software is decelerating faster than hardware is accelerating and computer performance evolves much slower. http://en.wikipedia.org/wiki/Wirth's_law
What will happen next? Massively parallel computers perform better, yet are also impeded by Wirth’s law. In addition the allocation of processors to program segments is extremely complicated and inefficient, lowering computer performance. Why not consider what Nature has to offer?
Signals in the “brain computer” travel much slower than transistor electrons. Action potentials travel from 10 – 100 m/s. Nevertheless the organism controls myriad processes “computing” in parallel. What is its secret? First it is a massively parallel non-linear computer which has been called Wisdom of the Body (WOB).
http://www.what-is-cancer.com/paper...wobcomputer.htm
In the traditional computer processors hardly interact and interaction is linear. In the WOB computer all processes interact non-linearly. In other words, interaction changes the process structure, which obviously does not apply to processor interactions. Such an interaction is called also embodiment.
http://www.what-is-cancer.com/paper.../embodyment.htm
In traditional computers control is generally from the top down, while the control of WOB processes is from bottom up.
These two requirements can be modeled with CA. Please inspect an elementary unit of such a WOB computer, the Proliferon, which may be regarded as its byte.
http://www.what-is-cancer.com/papers/ca1/ca167.htm
Posted by: tomjones
I am not sure why you use CA as your example I cannot imagine a more linear form of computation then CA. Please explain how the linear applications of rules in a CA in any way duplicates the non-linear behavior in the brain considering your idea WOB computing.
Thanks
Posted by: Gershom Zajicek M.D.
Please inspect the Interaction applet
http://www.what-is-cancer.com/papers/ca1/ca150.htm
You start with two isolated CA. The Rule=600 by itself does not induce non-linearity. Only when interacting their response is non-linear and unpredictable.
In later experiments each CA is endowed with a certain amount of resources. When isolated it loses resources, and when interacting it gains resources. Again interaction generates non linear response, e.g. in the Proliferon
Posted by: tomjones
I am sorry you are still mistaken, what you have is a linear system interacting with a linear system, in a linear way.
My guess is that you have two CA's the same rules control their evolution. Then you write an interaction rule that controls when the two intersect the appearance. This is not non-linear or unpredictable.
You have two 3 color CAs which means there are 15 possible combinations of colors that can occur, then you have some interaction rule which only appears to make a rule change for the composite CA essentially increasing the amount of grey in the CA and pushes the other colors out to the edges, but its still not a non-linear system.
I don't see how this meets any standard of non-linearity, the only one I could see some argument for is it being indeterminate, but that doesn't work due to the simple nature of the interaction and the lack of real unpredictability. In fact the fact that your two CA's use the same rules only further proves my point of linearity being operative here.
Essentially the point is that CA's will never be good models of the brain or biology since they are far to linear and too rigid.
Thanks
Posted by: Gershom Zajicek M.D.
The question is what in a system is non-linear? Linear chemical interactions of atoms and molecules, drive life which is essentially non-linear. Peptide polymerization is linear. Yet only when peptides interact they create proteins (enzymes), exhibiting non-linear structure and behavior. The same applies CA systems. Indeed the CA are linear, as you wrote, however their interaction initiates non-linear structure and behavior. You have to distinguish between a linear engine consisting of CA, whose manifestation is a non-linear change of structure and behavior.
You might liken the CA to isolated peptides. Once interacting they generate the complexity which we observe in life. There are two pre-requisites for this kind of non-linearity: Interaction and death (turnover).
http://www.what-is-cancer.com/paper.../comp2Frame.htm
Posted by: tomjones
Define for me if you will non-linear. Or how you are using it.
Please answer the question of what about the interaction is non-linear?
Does it fail the superposition test?
Does it meet any of the standard criteria in mathematics for a non-linear system? For example is it non-deterministic?
Thanks
Posted by: Gershom Zajicek M.D.
Nonlinearity
Situation where the relationship between variables is not directly proportional.
http://www.answers.com/topic/linearity?cat=biz-fin
non•lin•e•ar [ non línnee ər ]
1. not in line: not lying on the same straight line
2. not predictable from past: varying markedly as a result of individual factors or circumstances and so difficult to anticipate or likely to depart from previous patterns
3. mathematics not in direct proportion: describes a relationship or function that is not strictly proportional
http://encarta.msn.com/encnet/featu...efid=1861683677
Posted by: tomjones
Yes, thank-you for the dictionary definitions, but what I am getting at here is that saying some interaction is non-linear takes more then assigning it a label in science there is actually a formal definition of it.
You have two linear systems that follow some pattern, then you define some rule that based on that pattern and proximity changes the rules this is not non-linear this is still only linear. I don't see that your result from the interaction is anything more then the combination of the two CA's.
"f[state[j, i], rule[#], max age] = f[state[j, i - 1], rule[#], state[j - 1, i - 1]]
f[state[j-1, i], rule[#], max age] = f[state[j-1, i - 1], rule[#], state[j , i - 1]]"
In fact if this is your interaction rule it is in-fact a linear reaction being all additions and subtractions.
Essentially to be technical the definition of linearity in a mathematical system is:
If you have two functions F(x1) and F(x2) then one can write a function F(x1+x2)=F(x1) + F(x2). It follows both the additive rule and the homogenous rule.
Please tell me how is your interaction is not linear.
I eagerly await you answer.
Thanks
Posted by: Gershom Zajicek M.D.
There is a broader definition of non-linearity than mathematics has to offer. When you encounter a system what you perceive is change. Then you ask yourself where is this change going to? In order to find out you decide that this change is a process and your task is to capture the essence of this change in order to predict where it is going to. You know its past and would like to predict its future. You obviously start with mathematical tools:
1. Assume that the change is linear and find out that you can’t predict its future.
2. You turn to non-linear mathematical tools, and still the future of this process is unpredictable.
3. Then you transform the observed change to make it linearly or non-linearly predictable. And the process is still unpredictable.
4. In short none of the mathematical tools known today may foretell the future of this process.
5. Then your teachers turn to Plato and say that this change which you observe is a corruption of how really this process ought to behave . They beam with self-confidence and are ready to face a corrupted future which current mathematical tools foretell.
The non-linearity of life cannot be captured by current mathematical tools.
In order to see what I mean do the following:
Look for an ant’s nest and study it for some time. What you perceive is change. You already know that this nest is a process with a past and a future, yet you don’t have the tools to study its past. You can’t even define its today’s initial conditions on which you might construct a conceptual model for predicting the future. This is the non-linearity I am talking about. Yet the nest is an organism which experienced its past and has inborn expectations of what its future might be. Its “swarm –intelligence” outsmarts any scientific intuition.
It is my humble belief that CA may capture a tiny bit of this non-linearity.
http://www.what-is-cancer.com/paper.../comp2Frame.htm
Posted by: tomjones
"Look for an ant’s nest and study it for some time. What you perceive is change. You already know that this nest is a process with a past and a future, yet you don’t have the tools to study its past. You can’t even define its today’s initial conditions on which you might construct a conceptual model for predicting the future. This is the non-linearity I am talking about. Yet the nest is an organism which experienced its past and has inborn expectations of what its future might be. Its “swarm –intelligence” outsmarts any scientific intuition. "
Here are my final comments, this is actually not the case mathematics is actually quite capable in this area of swarm intelligence and is getting better at modeling it and creating it. It is of course the case with any model the accuracy is never 100% this is well known and does not deter anyone from making models.
"It is my humble belief that CA may capture a tiny bit of this non-linearity. "
CA is a mathematical tool its a development of one corner of mathematics.
"1. Assume that the change is linear and find out that you can’t predict its future.
2. You turn to non-linear mathematical tools, and still the future of this process is unpredictable.
3. Then you transform the observed change to make it linearly or non-linearly predictable. And the process is still unpredictable.
4. In short none of the mathematical tools known today may foretell the future of this process.
5. Then your teachers turn to Plato and say that this change which you observe is a corruption of how really this process ought to behave . They beam with self-confidence and are ready to face a corrupted future which current mathematical tools foretell.
The non-linearity of life cannot be captured by current mathematical tools. "
If your above statement is true then:
"It is my humble belief that CA may capture a tiny bit of this non-linearity. "
Is false, since all is contained in the broader scope of mathematics.
While it is true that there is a need for a new mathematics it is also equally true that NKS is not it.
Thanks
Posted by: Gershom Zajicek M.D.
Computer science searches in biological systems for ideas which might by modeled in silico, e.g. artificial intelligence (AI), genetic algorithms (GA), or neural nets. Hitherto the progress was somewhat disappointing. Like the rule based classical AI which fades away. Or GA which approach solutions only asymptotically. The reason for such inadequacies, is an adherence to anthropomorphism. Robots are supposed to mimic humans, even think and feel like humans. To me this avenue is barren, and time has come to search for simpler alternatives which are more promising.
Let’s start with an important insight by the great philosopher Hans Jonas. “The emergence of the human mind does not mark a great divide within nature but elaborates what is prefigured throughout the life-world.” (The Phenomenon of Life ISBN 0-8101-1749-5).This is the most important conclusion of evolution theory. Since evolution is a continuous process, the mind has also evolved in a continuous fashion. Not only the mind but anything which makes us human, e.g., memory, intelligence and creativity.
Computer scientists ought to turn their attention to simple organisms like an ameba called Physarum polycephalum . When this ameba is subjected to a series of shocks at regular intervals, it learns the pattern and changes its behavior in anticipation of the next one to come, according a team of Japanese scientists (Nature 451, 385 (2008)). Toshiyuki Nakagaki of Hokkaido University in Sapporo and his colleagues say that their findings “hint at the cellular origins of primitive intelligence”.( Saigusa, T., Tero, A., Nakagaki, T. & Kuramoto, Y. Phys. Rev. Lett. 100, 018101 (2008)).
Since lacking a nervous system amebas memory is embodied. And so is their intelligence, manifested by their creative response to injury. These experiments suggest that amebas may be trained in a Pavlovian fashion, although this was not the research objective. Why not create simple objects (robots) with ameba intelligence? Which may be achieved with CA.
v. CA memory
http://www.what-is-cancer.com/papers/ca/ca47.htm
v. CA embodiment
http://www.what-is-cancer.com/papers/ca1/ca143.htm
Posted by: Gershom Zajicek M.D.
Hitherto I published my CA experiments in applets. From now on experiments may be examined with the Mathematica player.
http://www.what-is-cancer.com/paper.../comp3Frame.htm
Posted by: Gershom Zajicek M.D.
The first step to model life phenomena is to endow a CA with movement. Please inspect a one dimensional CA with the following features:
1. Movement
2. Input and output
3. Foraging
It is interactive and may be examined with a Mathematica player
http://www.what-is-cancer.com/paper.../comp3Frame.htm
Posted by: Gershom Zajicek M.D.
Conditioning is a vital mechanism by which organisms interpret the environment. Psychology regards it as a process of behavior modification by which a subject comes to associate a desired behavior with a previously unrelated stimulus.
http://www.answers.com/Conditioning...3&ver=2.3.0.609
Conditioning was discovered by Ivan Petrovich Pavlov, who studied salivation physiology in dogs. Salivation is induced whenever the dog smells or sniffs food. In an experiment Pavlov rang a bell when feeding the dogs with meat and measured the amount of saliva. After two weeks of training he rang the bell without feeding the dogs, and the animals salivated as if they were sniffing meat.
CA behavior
http://www.what-is-cancer.com/paper.../comp3Frame.htm
The previous experiment showed a CA moving around in a search for resources. Finally it hit upon an obstacle which provided them. In order to interact the observer had to raise the input a bit whereupon the CA stopped moving and remained there. The CA aim was to maximize resources.
CA mood or satisfaction was manifested by its behavior. When hungry it lost weight (shrunk) and moved faster. When interacting with the obstacle it gained weight and stopped moving. Observing the experiment we might have concluded that the obstacle triggered CA behavior.
CA Conditioning
http://www.what-is-cancer.com/paper.../comp3Frame.htm
The present experiment demonstrates how a CA is conditioned by the obstacle. Like in the previous experiment, the CA moves around (input > 0), searches for resources, and encounters the obstacle. It then accumulates resources, yet when overweight it dies, and is replaced by a zygote. The same fate awaits the newly born, and the CA soon dies. However when a zygote is formed, CA output is raised a bit, and when output > input the CA leaves its prison. It is small and hungry but free and will not interact with the obstacle.
With time the CA forgets its traumatic experience, (output declines) and when input > output it is ready to interact with the obstacle and be conditioned.
Please consider the following:
- When conditioned, the CA remembered its trauma. It learned not to grow above a certain size. This memory was embodied in the entire CA.
- The obstacle served as a trigger. It shaped the CA memory.
Further reading:
Memory of a complex system
http://www.what-is-cancer.com/paper...ryofcomplex.htm
Will and Imagination
http://what-is-cancer.com/papers/ne...magination.html
Posted by: Gershom Zajicek M.D.
CA flatland
http://www.what-is-cancer.com/paper.../comp3Frame.htm
In 1884 Edwin Abbot wrote a fascinating book, Flatland: A Romance of Many Dimensions, in which he describes the life of two dimensional objects (creatures) and their perception of the third dimension. Reading the book, one could grasp how we experience the fourth dimension.
The experiments describe CA flatlanders who exist in a two dimensional space. Despite their simple behavior, they raise important philosophical issues which in CA-flatland seem to be uncomplicated and straight forward. We are concerned here with concepts, e.g. mind, self, and consciousness, and wonder whether the behavior of CA-flatlanders suggests that they might have a self, or are conscious.
Let’s remember that attributes e.g., mind or self do not exist as such. There is not a mind organ or an organ controlling emotion. We deduce these concepts from the behavior which we observe in an individual. Observing CA behavior may help us to grasp the essence of these issues, and this insight may then ease the analysis of these concepts when applied to us.
Hans Jonas
These experiments illustrate also concisely some profound philosophical issues raised by Hans Jonas in his important book “The phenomenon of Life”(1). According to Jonas: Plants, animals and the human animal display an ascending development of organic functions and capabilities. The emergence of the human mind does not mark a great divide within nature but elaborates what is prefigured throughout the life-world. The organic even in its lowest forms prefigures mind, and the mind even on its highest reaches remains part of the organic.
In other words, the rudiments of the human mind are inherent in simple organisms like an ameba or a paramecium. Or, concepts, like mind, self, and consciousness are applicable to all forms of life. An ameba has a self, a mind and is conscious. Obviously its mind only prefigures ours, and so are its other attributes. However understanding ameba’s mind may assist us in the understanding of our mind.
Imagine that some brainless creatures like an ameba are conscious and may have a mind. How does it relate to our understanding of our mind that requires a brain to exist.
Emergence
The CA has two genes. {initial condition , rule}, represented by two numbers {1 , 600}. You plant a zygote or a number one, represented by a square and it emerges into a CA. Emergence depends on the space in which CA exist. The two genes inherited from CA to CA are the blueprint of CA life, yet lack any information how the CA phenotype will emerge. The first experiment displays CA with different genes (rules). The system presented here consists of two interacting CA called proliferon http://www.what-is-cancer.com/papers/ca1/ca167.htm
Emergence is an unpredictable process. The zygote with its two genes does not reveal to us (observers) how it will evolve. Despite its simple structure CA behavior is unpredictable. Its trajectory is computationally irreducible and may be outlined only by observation. Nevertheless as a whole the proliferon is predictable. It always approaches and settles at an end-point. It always attempts to maximize its resources, yet the manner how it maximizes is unpredictable. Observing its behavior we conclude, that the proliferon “knows” something which we are unable to express mathematically. In order to find out how the proliferon reaches its end-point we have to observe its behavior all the way. This proliferon wisdom is called here Wisdom of the Body (WOB) http://www.what-is-cancer.com/papers/ca/ca93.htm
The image displays one state of an adult CA which oscillates between 46 states. The two exterior bits of a CA are its one dimensional membranes (M) which seal off the CA-self from the environment. Changes within the membrane are manifestation of CA metabolism or turnover. Each membrane bit has two sensors, one for touch and one senses remote objects.
http://www.what-is-cancer.com/paper.../comp3Frame.htm
CA-self
How do we know that a CA has a self? We don’t know. After all we don’t know whether our neighbor has a self. All we know that he is covered by a membrane, his skin, which seals off its inside, or self. The same reasoning applies to any living organism an even to a CA, which is also covered by a membrane.
Three characteristics of animal life
According to Jonas three characteristics distinguish animal from plant life: motility, perception , and emotion (p. 99). All three manifest a common principle. First we ought to realize that environment and the organism are contiguous. In plants, chemicals are directly exchanged between environment and organism. Since immediacy of satisfaction is concurrent with the permanent organic need, in this condition of continuous feeding there is no room for desire. Plants lack emotions.
The animal feeds on existing life, continuously destroys its mortal supply and has to seek elsewhere for more. There is a “linkage between motility and emotion” (p.100). The appearance of directed long-range motility thus signifies the emergence of emotional life. Greed is at the bottom of chase, fear at the bottom of flight. If appetition is the basic condition of motility, pursuit is the primary motion. Fulfillment not yet at hand is the essential condition of desire. Emotion implies distance between need and satisfaction.
“Emotion has no external organ by which to be identified and to force its way into a physical account” (p.100). It is embodied and cannot be localized or measured.
The CA senses remote objects toward which it moves. This “directed long-range motility” indicates that the CA has emotions. It’s “greed is at the bottom of chase.” The less resources it carries the faster its chase.
v. Embodied emotions http://www.what-is-cancer.com/paper.../embodyment.htm
CA conditioning and memory
Every live form is equipped with an instinct of association. External stimuli trigger processes in the organism, some are concurrent or associated. Association may be advantageous or threatening. In either case it will be manifested by movement, either toward, or from the stimuli. Conditioning is based on the association instinct and requires an embodied memory. We cannot observe the conditioning process itself. We deduce it from the behavior of the organism (v. CA conditioning).
Proliferon
http://www.what-is-cancer.com/papers/ca1/ca167.htm
The proliferon is the minimal construct which displays some essential characteristics of life, motility, perception and emotion. You may regard it as a byte of a complex model simulating life. It pre-figures attributes which will emerge in multi-proliferon systems, e.g., robots.
Modern robotics is dominated by anthropomorphism. It is led astray by false notions that consciousness and mind are manifestations of our brain and require a brain organ. However if you follow Jonas’ reasoning you soon realize that even an ameba has a mind, a prefigured one which is easier to model than our brain.
Robot domestication
Robots cannot be designed as such, they have to be grown, like animals. You plant two zygotes and create a proliferon. Let it interact with another one. Add more and more proliferons, and select the set which meets your expectations. Exactly as it is done during domestication of animals.
Additional reading:
Robot psychology http://www.what-is-cancer.com/paper...lexityFrame.htm
Slime mold intelligence http://www.what-is-cancer.com/paper...ligence.htmWill
Will and imagination http://www.what-is-cancer.com/paper...magination.html
References
1. Hans Jonas The Phenomenon of Life- Toward a Philosophical Biology
Northwestern University Press Evanston Ill 2001
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