Posted on 09/04/2002 11:23:46 AM PDT by betty boop
Stephen Wolfram on Natural Selection
Excerpts from A New Kind of Science, ©2002, Stephen Wolfram, LLC
The basic notion that organisms tend to evolve to achieve a maximum fitness has certainly in the past been very useful in providing a general framework for understanding the historical progression of species, and in yielding specific explanations for various fairly simple properties of particular species.
But in present-day thinking about biology the notion has tended to be taken to an extreme, so that especially among those not in daily contact with detailed data on biological systems it has come to be assumed that essentially every feature of every organism can be explained on the basis of it somehow maximizing the fitness of the organism.
It is certainly recognized that some aspects of current organisms are in effect holdovers from earlier stages in biological evolution. And there is also increasing awareness that the actual process of growth and development within an individual organism can make it easier or more difficult for particular kinds of structures to occur.
But beyond this there is a surprisingly universal conviction that any significant property that one sees in any organism must be there because it in essence serves a purpose in maximizing the fitness of the organism.
Often it is at first quite unclear what this purpose might be, but at least in fairly simple cases, some kind of hypothesis can usually be constructed. And having settled on a supposed purpose it often seems quite marvelous how ingenious biology has been in finding a solution that achieves that purpose….
But it is my strong suspicion that such purposes in fact have very little to do with the real reasons that these particular features exist. For instead…what I believe is that these features actually arise in essence just because they are easy to produce with fairly simple programs. And indeed as one looks at more and more complex features of biological organisms ¯ notably texture and pigmentation patterns ¯ it becomes increasingly difficult to find any credible purpose at all that would be served by the details of what one sees.
In the past, the idea of optimization for some sophisticated purpose seemed to be the only conceivable explanation for the level of complexity that is seen in many biological systems. But with the discovery…that it takes only a simple program to produce behavior of great complexity [for example, Wolfram’s Rule 110 cellular automaton ¯ a very simple program with two-color, nearest neighbor rules], a quite different ¯ and ultimately much more predictive ¯ kind of explanation immediately becomes possible.
In the course of biological evolution random mutations will in effect cause a whole sequence of programs to be tried…. Some programs will presumably lead to organisms that are more successful than others, and natural selection will cause these programs eventually to dominate. But in most cases I strongly suspect that it is comparatively coarse features that tend to determine the success of an organism ¯ not all the details of any complex behavior that may occur….
On the basis of traditional biological thinking one would tend to assume that whatever complexity one saw must in the end be carefully crafted to satisfy some elaborate set of constraints. But what I believe instead is that the vast majority of the complexity we see in biological systems actually has its origin in the purely abstract fact that among randomly chosen programs many give rise to complex behavior….
So how can one tell if this is really the case?
One circumstantial piece of evidence is that one already sees considerable complexity even in very early fossil organisms. Over the course of the past billion or so years, more and more organs and other devices have appeared. But the most obvious outward signs of complexity, manifest for example in textures and other morphological features, seem to have already been present even from very early times.
And indeed there is every indication that the level of complexity of individual parts of organisms has not changed much in at least several hundred million years. So this suggests that somehow the complexity we see must arise from some straightforward and general mechanism ¯ and not, for example, from a mechanism that relies on elaborate refinement through a long process of biological evolution….
…[W]hile natural selection is often touted as a force of almost arbitrary power, I have increasingly come to believe that in fact its power is remarkably limited. And indeed, what I suspect is that in the end natural selection can only operate in a meaningful way on systems or parts of systems whose behavior is in some sense quite simple.
If a particular part of an organism always grows, say, in a simple straight line, then it is fairly easy to imagine that natural selection could succeed in picking out the optimal length for any given environment. But what if an organism can grow in a more complex way…? My strong suspicion is that in such a case natural selection will normally be able to achieve very little.
There are several reasons for this, all somewhat related.
First, with more complex behavior, there are typically a huge number of possible variations, and in a realistic population of organisms it becomes infeasible for any significant fraction of these variations to be explored.
Second, complex behavior inevitably involves many elaborate details, and since different ones of these details may happen to be the deciding factors in the fates of individual organisms, it becomes very difficult for natural selection to act in a consistent and definitive way.
Third, whenever the overall behavior of a system is more complex than its underlying program, almost any mutation in the program will lead to a whole collection of detailed changes in the behavior, so that natural selection has no opportunity to pick out changes which are beneficial from those which are not.
Fourth, if random mutations can only, say, increase or decrease a length, then even if one mutation goes in the wrong direction, it is easy for another mutation to recover by going in the opposite direction. But if there are in effect many possible directions, it becomes much more difficult to recover from missteps, and to exhibit any form of systematic convergence.
And finally…for anything beyond the very simplest forms of behavior, iterative random searches rapidly tend to get stuck, and make at best excruciatingly slow progress towards any kind of global optimum….
It has often been claimed that natural selection is what makes systems in biology able to exhibit so much more complexity than systems that we explicitly construct in engineering. But my strong suspicion is that in fact the main effect of natural selection is almost exactly the opposite: it tends to make biological systems avoid complexity, and to be more like systems in engineering.
When one does engineering, one normally operates under the constraint that the systems one builds must behave in a way that is readily predictable and understandable. And in order to achieve this one typically limits oneself to constructing systems out of fairly small numbers of components whose behavior and interactions are somehow simple.
But systems in nature need not in general operate under the constraint that their behavior should be predictable and understandable. And what this means is that in a sense they can use any number of components of any kind ¯ with the result…that the behavior they produce can often be highly complex.
However, if natural selection is to be successful at systematically molding the properties of a system then once again there are limitations on the kinds of components that the system can have. And indeed, it seems that what is needed are components that behave in simple and somewhat independent ways ¯ much as in traditional engineering.
At some level it is not surprising that there should be an analogy between engineering and natural selection. For both cases can be viewed as trying to create systems that will achieve or optimize some goal….
…[I]n the end, therefore, what I conclude is that many of the most obvious features of complexity in biological organisms arise in a sense not because of natural selection, but rather in spite of it.
Stephen Wolfram is a well-known scientist and the creator of Mathematica. He is widely regarded as one of the world's most original scientists, as well as an important innovator in computing and software technology.
Born in London in 1959, Wolfram was educated at Eton, Oxford, and Caltech. He published his first scientific paper at the age of 15, and had received his Ph.D. in theoretical physics from Caltech by the age of 20. Wolfram's early scientific work was mainly in high-energy physics, quantum field theory, and cosmology, and included several now-classic results. Having started to use computers in 1973, Wolfram rapidly became a leader in the emerging field of scientific computing, and in 1979 he began the construction of SMP--the first modern computer algebra system--which he released commercially in 1981.
Exactly! This could be the key. Or maybe not. Checking it out, though.
The best I have found thus far is a consortium that I have been following for years. The group continues to grow and develop their theory in various disciplines.
So here is my first candidate(s) for you: Space-Time-Matter Consortium
I may also end up dismissing the book as trivial. But not yet.
It sure does shake up one’s paradigms, Lysander. But that’s essentially what Wolfram is trying to do with this book. As he puts it, he wants traditional mathematicians and scientists to “retrain their intuition.” He apparently believes that certain basic assumptions of the sciences are incorrect. A particularly famous one is the assumption that complex behavior must have complex causes. He repeatedly shows that this is untrue by modeling all kinds of systems, natural, physical, mathematical. And what he has discovered is that apparently random, extraordinarily complex behavior can be generated by the evolution of very simple rules. His piece de resistence is the Principle of Computational Equivalence, which holds that a fundamental unity exists across a vast range of systems and processes in nature and elsewhere; and that despite all their differences in detail, every system that is not obviously simple can be viewed as corresponding to a computation that is ultimately equivalent in its sophistication. Two important corollaries are universality and computational irreducibility. The presence of the latter ultimately means that there are limits to human knowledge and to human thinking itself that are quite likely impossible to overcome. Which sounds like something a philosopher might say, but it’s certainly not what we expect to hear from a scientist….
But then again, maybe he’s just been looking at computer screens too long: The systems he models are executed as computer graphics, whose behavior can be analyzed just by looking. He’s looked at millions of them over the past 20 years. It’s simply uncanny how often particular sorts of patterns can be seen in the evolution of widely disparate systems.
Anyhoot, there’s a lot of “food for thought” in this book. I'll be working through its implications for some time to come, I'm sure.
The universe as a whole seems to have done that since the time we can see in the cosmic microwave background. At the time it contained a thin gas of hydrogen, helium, and a little lithium. And the laws of physics.
His piece de resistence is the Principle of Computational Equivalence, which holds that a fundamental unity exists across a vast range of systems and processes in nature and elsewhere; and that despite all their differences in detail, every system that is not obviously simple can be viewed as corresponding to a computation that is ultimately equivalent in its sophistication.
There are already known limited examples of that, too. Lots of relationships in physics involve inverse-square laws. The equations of electrostatics turn out to apply to a lot of seemingly unrelated problems. I'm told there are here are other examples. But I'm not sure if it goes as far as Wolfram suggests, or if that's exactly what he's talking about.
I agree. Complexity right now is too complicated.
I do. I largely agree. I don't agree with Wolfram's pretense that these ideas are new. They are culled from the biology literature.
The Evolutionists, and here Wolfram, are fond of speaking as though "natural selection" were some sort of motive intelligence driving perceived evolution toward some unknown end, even while admitting that nature, inclusive of the creatures populating it, can compose little more than a passive context and therefore must be largely undirective. I guess I would say that there is an imputation of activeness and directedness to "natural selection" by "scientific" thinkers and writers to which I object. It has not been shown. Wolfram seems to some extent to agree.
Wolfram also easily adopts the notion that mutation is or can be an effective mechanism of positive change or growth in complexity. Mutation operates like a rifle shot through intricate electronic machinery and I think it highly doubtful that positive change can occur in this fashion, even given an almost unlimited timeframe. Multiple rifle shots, to me, add up to massive damage and little else.
But he clearly is thinking "outside the box" and that's a good beginning in my opinion. Truly "outside the box" thinking would assume that consciousness came first.
Hmmmm .... sounds a bit like a twist on Penrose's The Emperor's New Mind (a good review) - Roger Penrose argues against the viability of artificial intelligence. In Chapter 10, "The non-algorithmic nature of mathematical insight" he argues that by consciousness, people have insight into mathematical truth.
I have yet to read the book. Judging by the above prose, it looks like it might be rough sledding, although I'm always happy to see somebody get a dig in on "random" natural selection.
What I really want to know, and what I haven't heard any of his peers yet weigh in on, is: Does he offer anything new?
Did you enjoy the book, BB?
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