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Author | Topic: Evolution of complexity/information | |||||||||||||||||||||||
mark24 Member (Idle past 5222 days) Posts: 3857 From: UK Joined: |
Saviourmachine,
It's a strawmen, 'average complexity' is an useless quantity. Let's say it like this: "In any case, depending on how you define it, earth is still, on average, not much more complex than it was 3 mld years ago. Almost all non-living, complex structures are simpler than bacteria. Almost all the mass of complex structures is in very simple complex (non-living) forms. And by "almost all" I mean darn near ALL." You see, the 'average complexity' depends heavily on the denominator: all vertibrates? all living things? all existing complex forms? all material forms?
It's very, very simple, mate. 3bn years ago ther were only unicellular prokaryotes. Today they still exist, but with the addition of MORE COMPLEX eukarotes, both unicellular & multicellular. Somewhere along the line complexity increased in order to achieve the eukarotic condition & multicellularity. Mark There are 10 kinds of people in this world; those that understand binary, & those that don't
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petersmall Inactive Member |
Jar writes:
yet after nearly 200 posts, we still have no idea of what either Complexity or Information are. We have no way to know if complexity is greater today than it was during the Cambrian era, or Cretaceous. Without both good definitions that we all agree upon, and some agreed method to measure and quantify, where the hell is this going?
Trying to understand complexity and give it a value has no meaning. It is the equivalent to asking, "How many infinities are there in infinity?". Complexity is a description of a system and the implication is that it is too complex to measure or understand. But, complexity theories aren't about measuring or understanding complexity, they are about making use of the fact that complex systems, however complex, settle into steady states. This is because they always tend towards states of minimum energy. This is somewhat analogous to the way water, under the influence of gravity, always runs down hill (towards a state of minimum potential energy). Just as water might get trapped into false minimums (dips in the ground), complex systems can become trapped in steady states known as "attractor basins". It is this phenomenon that makes complexity and chaos theories so valuable, because a system doesn't take up a state randomly from all possible states once it is disturbed - it takes up one of only a limited number of states dependent upon initial conditions. It is this phenomenon that is used by the brain to identify patterns of learned information that is contained in the billions of signals emanating continuously from our sense receptors. It is also the phenomenon that allows the brain to locate and combine a myriad of different neural networks in the brain for purposes of perception and cognition. As for a definition of information. Isn't it about "learned patterns of sensory inputs" that we talk about when we refer to information? Mary Catherine Bateson, talking about Greory Bateson's book "Steps to an ecology of mind" writes:
Having described mental systems, Gregory Bateson is able to lay out a number of other characteristics. He elaborates the notion that, in the world of mental process, difference is the analog of cause ("difference that makes a difference") and argues that embedded and interacting systems have a capacity to select pattern from random elements, as happens in evolution and in learning which Gregory calls the "two great stochastic processes." He explores the way analogy underlies all "patterns which connect,"
Peter Small Author of: LingoSorcery, Magical A-Life Avatars, The Entrepreneurial Web, The Ultimate Game of Strategy and Web Presence http://www.stigmergicsystems.com
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petersmall Inactive Member |
SIDELINED writes: Well astrology is nonsense and it too is a multi-billion dollar a year industry.So is homeopathy. no one ever became poor underestimating the gullibility of the public. I’ve heard similar views expressed about neuroscience and the Internet. All are opinions based upon a bounded rationailty. To each, in their own personal worlds, other worlds can seem nonsense - irrespective of whether or not any of the worlds are based upon absolute facts. Knowledge Management may seem nonsense if you take it to mean subjective knowledge. But, as Charles Knight pointed out, most knowledge management systems are really dealing with information. Thus, Knowledge Management to a marketing company using a database to create customer profiles and categories would hardly consider Knowledge Management to be nonsense. Peter Small Author of: LingoSorcery, Magical A-Life Avatars, The Entrepreneurial Web, The Ultimate Game of Strategy and Web Presence http://www.stigmergicsystems.com
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NosyNed Member Posts: 9003 From: Canada Joined: |
Trying to understand complexity and give it a value has no meaning. Then any sentences that say things like "Evolution can not increase complexity" are also meaningless. That is the point of the discussion. If we are unable to define and quantify "complexity" it is useless to continue the discussion on that topic.
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CK Member (Idle past 4154 days) Posts: 3221 Joined: |
You are playing semantic games with me Charles
No not at all, I meant entirely what I said. Perhaps you should read my paper before commenting further. You'll find it is actually a criticism of current beliefs in knowledge management (which is why I mentioned that it went down like a lead balloon). I did read your paper and I asked a collegue of mine (One of most cited figures in the information sciences academic community) to have a look. We both came to the same conclusions - overly complex and of very limited practical value to most organizations. I will say, however, that it had a few interesting ideas in it.
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petersmall Inactive Member |
NosyNed writes: Then any sentences that say things like "Evolution can not increase complexity" are also meaningless. That is the point of the discussion. If we are unable to define and quantify "complexity" it is useless to continue the discussion on that topic. It depends very much how you define complexity as it can mean different things to different people. The WORD IQ encyclopedia describes it as follows
Complexity There are different senses of complexity: * In information processing, complexity is a measure of the total number of properties transmitted by an object and detected by an observer. Such a collection of properties is often referred to as a state.* In computer science, the study of how much time and memory a computer algorithm may take is the field of computational complexity theory. * Complexity is often used as a shorthand for the field that developed in the late 1980s around the use of mathematical and computational modeling of biological, economic and technological systems known as "complex systems" (sometimes complex adaptive systems). * In the sense of how complicated a problem is from the perspective of the person trying to solve it, limits of complexity are measured using a term from cognitive psychology, namely the hrair limit. * In mathematics, Krohn-Rhodes complexity is an important topic in the study of finite semigroups. Some of these meanings can be quantified, but as is pointed out in the article: "Complexity is just a word" by Peter A. Corning, Ph.D. Institute for the Study of Complex Systemshttp://www.complexsystems.org/commentaries/jan98.html quantifying complexity can have very little value if it refers to the complexity in non linear systems (i.e., biological systems). The issues relating to definition and quantifying complexity are brought out in an ISSS discussion at:We've got some trouble | 404 - Resource not found Perhaps the best attitude to have towards complexity is that described by Peter Coming, who wrote:
Rather than trying to define what complexity is, perhaps it would be more useful to identify the properties that are commonly associated with the term. I would suggest that complexity often (not always) implies the following attributes: (1) a complex phenomenon consists of many parts (or items, or units, or individuals); (2) there are many relationships/interactions among the parts; and (3) the parts produce combined effects (synergies) that are not easily predicted and may often be novel, unexpected, even surprising. At the risk of inviting the wrath of the researchers in this field, I would argue that complexity per se is one of the less interesting properties of complex phenomena. The differences, and the unique combined properties (synergies) that arise in each case, are vastly more important than the commonalities. If someone does develop a grand, unifying definition-description of complexity, I predict that it will add very little to the tree of knowledge (pardon the pun). But that shouldn't deter us from trying; the very effort to do so will surely enrich our understanding.
Peter Small Author of: LingoSorcery, Magical A-Life Avatars, The Entrepreneurial Web, The Ultimate Game of Strategy and Web Presence http://www.stigmergicsystems.com
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Hangdawg13 Member (Idle past 778 days) Posts: 1189 From: Texas Joined: |
Thanks for the info, Loudmouth, I haven't overlooked it. So much to do, so little time...
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Loudmouth Inactive Member |
Not a prob, bro. I will admit that it is a little strange to have such a polite creationist around. Take your time.
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contracycle Inactive Member |
quote: It sounds to me like you guys are having a semantic difference. As I understand it, the Humanities distinguish between KNOWLEDGE and INFORMATION, in which information is the raw input, and knowledge the result of interpretation and processing. Information science makes exactly the same distinction except between DATA and INFORMATION. The commonality of the term information in two different senses trips people up a lot, it seems to me.
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CK Member (Idle past 4154 days) Posts: 3221 Joined: |
I'm am information sciences academic, I have no problem with the concept of
knowledge . I have a problem with knowledge management - because it's not possible. Like I said before it's just information management under a snakeoil front. This message has been edited by Charles Knight, 07-22-2004 08:16 AM
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petersmall Inactive Member |
contracycle writes:
It sounds to me like you guys are having a semantic difference
Yes. This is very common in all forums. It is particularly interesting for me as an author because I have to write stuff that might be read by people with all kinds of technical (and non technical) backgrounds. When I'm preparing to write a new book, I visit a number of different forums to see how they react to different ways of explaining concepts. Semantic differences are a big problem, but an even greater problem is that people seem to use a heuristic method of reading information, whereby they reinterpret not only words but whole concepts into their own cognitive models. This can lead to total misunderstandings and can even promote extreme antagonism. Antagonisms usually come from people who have a particular cognitive model to defend. Any trespass - into their area of special interest that doesn't conform with their views - is attacked with vigor. This is particularly noticeable when a subject area has many different branches. The evolutionary psychology forum [evol psych] is a good example here. This subject area includes hundreds of different disciplines, where words and concepts can have all kinds of different meanings to the different groups. The extent of the diversity was described recently by one of the [evol psych] moderators, who wrote:
It occurs to me that Evolutionary Psychology is at the crossroads of numerous specialist disciplines. There is not just evolutionary biology and psychology, but numerous branches of biology and psychology from memetics to genetics to psychopathy to social psychology to ethnology and so on. I hesitate to even attempt to list all the underlying disciplines as I am bound to exclude more than I include. As consciousness is also an important issue, and consciousness is made up of at least 100 disciplines, possibly as many as 200, then the list for Evol Psych must be long indeed. Robert Karl Stonjek
Since the beginning of this year, I've been trying to understand semantic problems from the point of view of how the brain processes information. This has opened up a pandora's box because I had no idea how extensive this subject area is. But, what I have discovered is that brain imaging techniques is shedding a whole new light on this problem. Peter Small Author of: LingoSorcery, Magical A-Life Avatars, The Entrepreneurial Web, The Ultimate Game of Strategy and Web Presence http://www.stigmergicsystems.com
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CK Member (Idle past 4154 days) Posts: 3221 Joined: |
removed by author.
This message has been edited by Charles Knight, 07-22-2004 01:46 PM
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RAZD Member (Idle past 1432 days) Posts: 20714 From: the other end of the sidewalk Joined: |
Sorry to take so long to get back to this (I've been away)
my point was more that increased complexity does not necessarily result in a better design, in many cases something can be simplified to gain an advantage -- less weight, more efficient use of energy.
SaviorMachine writes: A very weak definition of complexity, such as the size of genome, would be sufficient to explain an increase in the maximum complexity of all species under evolution. size of genome is not enough if one has many repeated sequences and another has more varied sequences, and this gets into information theory to define the complexity based on "compressed information" similar to making a ZIP file of the code and the larger 'zipped genome' would be more complex. would telepathic amoebas be more complex than non-telepathic ones? depends on whether the result would be more of a 'hive mind' being than an assembly of individuals continuing to do same old tasks without specialization, for in one sense all multicell organisms are an assembly of single cell 'individuals' working together telepathically: the complexity comes from specialization. we are limited in our ability to understand by our ability to understand RebelAAmerican.Zen[Deist
{{{Buddha walks off laughing with joy}}}
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NosyNed Member Posts: 9003 From: Canada Joined: |
This seems as good a place as any to carry on discussing complexity.
From: Message 140 Here is a copy:he one you get is actually a reminder of the one I've already cited someplace here in this thread. It is the human brain. I know other creatures have also complex brains, but I'm somewhat familiar with some stuff about our brains. 1. What we observe in our daily lives is that complex things like computers, televisions, airplanes, etc is that in order to become complex to do what we want them to do, masterfully precisioned and designed by thousands of individuals go into making them the complex machines which function to serve us as they do. 2. By the same token, scientists observe the brain, it is discovered that some 100 billion neurons, served by around a trillion service agents function with great precision to operate the nervous systems of each of billions of people. Each neuron interacts with at least 10 other neurons in the process. I believe the human mind is far more complex than anything man-made. No amount of co-operative human intelligence can make one from scratch. 3. The thread title is "Ignorant Creationists vs. Knowledgeable Evolutionists. It is the notion of some of us more ignorant Biblical fundamental creationists that no amount of time nor natural selection nor random mutation with out a smidget of intelligence would be able to produce such a precisely designed and super-highly complex wonder as the human brain, no matter how you cook up your math and rig up your theories. Do you mean to say that complexity can only come about with God's intervention? PRECISELY! If all the kings wise men, with all their combined trillions of neuronic brains working together can't make a brain, imo, mindless Mr. Natual Selection and his cohort, dead headed Ms Radom Mutation never did it. And don't forget also that the kings wise men have models to observe and work from/copy, where NS and RM, had nothing atol to begin to put it all together, not even anything whatsoever to motivate them to do it. We have an example of something that we can probably all agree is complex: the human brain. What we don't have is any definition of what complex is. It appears that it is something with lots of parts. They also have to be organized in some "special" way. But instead of taking an extreme case could we ask about something simpler? How much less complex than a human brain is the brain of a cat? Is it too much to build with processes that have been demonstrated to be able to form complex results? If that is how about the brain of a flat worm? Is there a lower line where Buz would agree something can evolve?
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Peter Member (Idle past 1506 days) Posts: 2161 From: Cambridgeshire, UK. Joined: |
The biggest problem one faces (beyond defining terms )
when considering information and complexity to biological systems is to decide what we are applying them to. Many start with the DNA .... unfortunately it is not theDNA that makes the organism so this is inapproriate. It is the collection of proteins made from the DNA that makes the organisms so information and complexity have to be considered at least at this level. Not the proteins, but the INTERACTION of a collection ofproteins. I'm still not convinced that information and complexity areuseful concepts in biology let alone evolutionary theory. Evolution is about change. That's all. Change. It focusses on the relationship between a set of phenotypictraits with an environment. That we appear to see an increase in complexity (if viewed asnumber of interacting components of some kind) is suggestive of an environmental need for such complexity to overcome the shortcomings of organism. Like 'human intelligence', much valued and praised, is onlyrequired because we are so puny as an organism. The more resilient and adaptable an organism is, the less'intelligence' it requires to survive .... that's why there are more bacteria and insects than mammals. More complex (however one considers it) doesn't mean betterif it did (even in terms of match to environment) there wouldn't be any 'simple' organisms left after 3.5 billion years.
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