Slashdot Mirror

All too true, from drones to these: http://en.wikipedia.org/wiki/S...
"In 2006, Samsung Techwin announced a $200,000, all weather, 5.56 mm robotic machine gun and optional grenade launcher to guard the Korean DMZ. It is capable of tracking multiple moving targets using IR and visible light cameras, and is under the control of a human operator. The Intelligent Surveillance and Guard Robot can "identify and shoot a target automatically from over two miles (3.2 km) away." The robot, which was developed by a South Korean university, uses "twin optical and infrared sensors to identify targets from 2.5 miles (4 km) in daylight and around half that distance at night." It is also equipped with communication equipment (a microphone and speakers), "so that passwords can be exchanged with human troops." If the person gives the wrong password, the robot can "sound an alarm or fire at the target using rubber bullets or a swivel-mounted K-3 machine gun." South Korea's soldiers in Iraq are "currently using robot sentries to guard home bases."[3]"

And the movie Elysium painted such a picture as well, with robot guards and robot police.
http://www.santafe.edu/news/it...
"he makers of this summer's Hollywood blockbuster Elysium got one thing right, according to a column in the Washington Examiner that cites a 2005 research by SFI Professor Sam Bowles: The abundance of 'guard labor' depicted in the movie -- in the movie's case case robot police and sleeper agents -- is an expected feature of a society with a high degree of economic inequality. The 2005 paper, co-authored by Bowles and Arjun Jayadev and published as an SFI working paper, connects inequality with a larger proportion of a population engaged in enforcing the property rights and protecting the assets of the elite. Roughly a quarter of the U.S. labor force was dedicated to guard labor in 2002, they wrote."

Even without robots, see also:
http://en.wikiquote.org/wiki/J...
"I can hire one half of the working class to kill the other half."

As Keynes wrote in his book about his own predecessors: "The completeness of the [classical] victory is something of a curiosity and a mystery. It must have been due to a complex of suitabilities in the doctrine to the environment into which it was projected. That it reached conclusions quite different from what the ordinary uninstructed person would expect, added, I suppose, to its intellectual prestige. That its teaching, translated into practice, was austere and often unpalatable, lent it virtue. That it was adapted to carry a vast and consistent logical superstructure, gave it beauty. That it could explain much social injustice and apparent cruelty as an inevitable incident in the scheme of progress, and the attempt to change such things as likely on the whole to do more harm than good, commended it to authority. That it afforded a measure of justification to the free activities of the individual capitalist, attracted to it the support of the dominant social force behind authority."

We have a choice as a society (at least in theory) like the choice presented in Marshall Brain's book Manna. For Plan A, we can create a world of wealth for all that takes us all (if we want) to the planets and asteroids and stars and beyond, by using fusion power and dirt cheap solar and 3D printing and nanotech and robotic helpers and cybernetic augmentation and so on. Or, for Plan B, we can let all but the super rich starve as the economy implodes from automation, and then, if society does not self-destruct in that starvation process, the children of the super rich can go to the stars eventually if they want. Either way, humanity, if it survives, ends up entirely super rich from technology. With exponential technological growth and declining human fertility in industrialized countries, and a solar system that can likely house quad

This isnt true. Check out this study:

http://tuvalu.santafe.edu/~bowles/PopulationSize.pdf

If the population shrinks enough, ie massive plague or apocalyptic type stuff, technology will regress, even to a stone age like state.

Good game theory books I keep on my shelf:

Nonlinear Dynamics, Mathematical Biology, and Social Science (Santa Fe Institute Studies in the Sciences of Complexity Lecture Notes)
by Joshua Epstein
Westview Press
ISBN: 9780201419887
(if you know enough math for partial differential equations, this book is a must-have, since it's directly applicable to mathematically modelling open source software projects)

The Evolution of Cooperation
by Robert Axelrod and William D. Hamilton
Paper: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.147.9644&rep=rep1&type=pdf
Book: ISBN 0-465-02122-2
Perspectives on Adaptation in Natural and Artificial Systems
Basic Books
ISBN: 9780195162929

The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration
by Robert Axelrod
Princeton University Press
ISBN 978-0691015675

Game Theory and the Social Contract, Vol. 1: Playing Fair
by Ken Binmore
MIT Press
ISBN 978-0262023634

Game Theory and the Social Contract, Vol. 2: Just Playing (Economic Learning and Social Evolution)
by Ken Binmore
MIT Press
ISBN 978-0262024440

Analyzing Policy: Choices, Conflicts, and Practice
by Michael C. Munger
W. W. Norton & Company
ISBN 978-0393973990

Growing Artificial Societies: Social Science from the Bottom Up (Complex Adaptive Systems
by Joshua M. Epstein, Robert L. Axtell
MIT Press
ISBN 978-0262550253

See also:

http://www.santafe.edu/
http://www.youtube.com/user/santafeinst

The Brookings Institute is also active in this area (it was their math that led most of the U.S. Cold War policy and kept everyone out of a nuclear exchange with the Soviets).

-- Terry

Velocity of Money

A savings account works a lot like a capacitor - or an inlet to the ocean (see how the rate of tidal flow varies with the different shapes of inlets, and the relative tidal force)

As a whole, economic systems are more easily viewed in information space, not physical space. But these two spaces have long ago been determined to be duals.

But the best way to look at economies is as complex adaptive systems. See the Santa Fe Institute for information on CAS. Of course, CAS are particular examples of dynamical systems.

If this were not true, the quants would have failed. Their singular advantage was recognizing (in a limited way) that economic systems do behave as complex systems. Just as one can not easily follow the motion of a single molecule in a gas cloud, but can model the behavior of the cloud via fluid dynamics, so also the behavior of a single financial instrument can not be fully predicted but the overall behavior of the system can be predicted to some extent - like the weather - and so the behavior of that instrument can be predicted within some range of probability. The predictability of the weather decreases as the physical scale is reduced, or the time scale is increased. But you can still say with 40% certainty that it will rain here on Thursday.

It's a good idea. See:
"How to Do Agent-Based Simulations in the Future: From Modeling Social Mechanisms to Emergent Phenomena and Interactive Systems Design "
http://www.santafe.edu/media/workingpapers/11-06-024.pdf
"Since the advent of computers, the natural and engineering sciences have enormously progressed. Computer simulations allow one to understand interactions of physical particles and make sense of astronomical observations, to describe many chemical properties ab initio, and to design energy-efficient aircrafts and safer cars. Today, the use of computational devices is pervasive. Offices, administrations, financial trading, economic exchange, the control of infrastructure networks, and a large share of our communication would not be conceivable without the use of computers anymore. Hence, it would be very surprising, if computers could not make a contribution to a better understanding of social and economic systems. While relevant also for the statistical analysis of data and data-driven efforts to reveal patterns of human interaction, we will focus here on the prospects of computer simulation of social and economic systems. More specifically, we will discuss the techniques of agent-based modeling (ABM) and multi-agent simulation (MAS), including the challenges, perspectives and limitations of the approach. In doing so, we will discuss a number of issues, which have not been covered by the excellent books and review papers available so far. In particular, we will de- scribe the different steps belonging to a thorough agent-based simulation study, and try to explain, how to do them right from a scientific perspective. To some extent, computer simulation can be seen as experimental technique for hypothesis testing and scenario analysis, which can be used complementary and in combination with experiments in real-life, the lab or the Web."

And also:
http://www.brookings.edu/topics/agent-based-models.aspx

Or what I started almost a decade ago, but then had a kid and left on the back burner:
  http://savannah.nongnu.org/projects/simulchaord
"This project is mainly to develop simulations of chaordic organizations, processes, and systems under the GPL license, with "chaordic" used as defined by Dee Hock at http://www.chaordic.org/ and in his book "Birth of the Chaordic Age"."

Something on the idea of a campaign to get more free software written about manstream and alternative economics:
http://slashdot.org/comments.pl?sid=2356864&cid=36936914

You need to update your economics model. Monopolies are the natural product of an increasing demands industry like software. They aren't bad as long as there is room in the market for alternatives to provide a better fit product, which are clearly present with both Linux and Mac OS surviving. Ever since I read the following paper, I've gotten a bit leary on how much we should attack the natural formations of the market. http://www.santafe.edu/~wbarthur/Papers/Pdf_files/HBR.pdf

Here's one person's opinions along with the ergonomic adjustments he made to his Emacs setup:

http://www.santafe.edu/~nelson/ergo/

The above gives an introduction to phase change as it is considered in terms of Complexity Theory. Approaching phase change through complexity theory, even for an outsider like myself, gives insight into how far reaching are the results of insight into phase change.

> efforts to teach great apes more advanced languages have been remarkably successful.

Ummm...no.

In a small number of cases some primates have been trained to recognize (up to) a few hundred symbols. Grammatical structure? Never. It's a really far stretch to call that language.

Read about it:
http://www.garysturt.free-online.co.uk/gardner.htm

http://www.santafe.edu/~johnson/articles.chimp.htm l
" A chimp might learn to connect a hand sign with an item of food, skeptics like Dr. Terrace argued, but this could be a matter of simple conditioning, like Pavlov's dogs learning to salivate at the sound of a bell. Most importantly, there was no evidence that the chimps had acquired a generative grammar -- the ability to string words together into sentences of arbitrary length and complexity."

My favorite Emacs-specific ergo tip: avoid chording. It's not for nothing that Emacs is so massively configurable. I have:

(define-key global-map [f1] 'Control-X-prefix)
(define-key global-map [f2] 'find-file)
(define-key global-map [f3] 'save-buffer)
(define-key global-map [f4] 'kill-buffer)
(define-key global-map [f5] 'switch-to-buffer)
(define-key global-map [f6] 'other-window)
(define-key global-map [f9] 'compile)

in my .emacs (inspired by this.) I used to have a host of other things mapped all over the numeric keypad -- kill, yank, undo -- but I lost them at some point. I should re-create those.

Also don't neglect a good setup (good posture, good keyboard, good pointing device), and stretch breaks at least once an hour.

Usefulness is useful, but pure science is fascinating, and the research potential here astonishes me.

One of my all-time favorite reads was Complexity, couched as the story of the Sante Fe Institute and its brilliant, eccentric, tortured visionaries. Each an expert in their academic (in the sense of "strict observance of conventional rules" as well as "pertaining to academia") field, including economics, biology and computer science, they pursued the interdisciplinary "science of complexity".

The universe is full of complex systems, which are not comprehensible except as the aggregate of the interactions between autonomous agents: an economy consists of the transactions between buyers and sellers; the slime mold, depending on temperature and humidity, becomes a slowly-moving glob of brown goop, or simply vanishes as the individual cells go their own way; computers have not yet formed their own scientific community, but, we suppose, they're working on it.

Brains, it would seem, are complex systems; there is no "chief brain cell," they form spontaneously based on interactions between autonomous brain cells. I want to know more about the "api" of brain cells, and this article would seem to suggest the opening of a rather large door.

If India needs english speaking teckies, then it presents the old problem of worker mobility in a new light. Taking a page from Hot money it may be a new trend will arise where skills will move to where the relative cost of living will maintain or increase their net income. Living in a foreign land can be a bitch but if it means putting money in the bank then, perhaps, as a short term strategy it will win converts and create a global work force. This may be aided by the adoption of English as the lingua franca.

Somewhere, perhaps in a paper from the Santa Fe Institute, I read an exchange between a physicist and an economist. The economist derided the physicist saying that a career in physics did not last much beyond the physicist's 30th year. The economist went on to ask the physicist what he'll do after his 30th birthday. The physicist replied he'd likely become an economist

One of the key question underlying studies of life on earth is simply how did "life", RNA or DNA based, come to be encapsulated in the cell membrane? Studies of prebiotic life tend to skip over the issue. Dr.S. Kauffman, author of books on Complexity has offered a few alternative scenarios but the question of how life came to have a place to call 127.0.0.1 remains open to conjecture. Non-equilibrium open systems giving rise to complexity have held out alot of promise to answering basic questions arising from studies of prebiotic life but the question remains how do they get the caramilk inside a caramilk bar.

But the world changed while he was writing Out of Control largely due to the exaggerated importance placed on Mitchell, Hraber and Crutchfield's 1993 paper which cast aspersions on Langton's lambda and implicitly on the whole notion of "border of order--edge of chaos".

Wolfram's reunification of his own old Class 3 and Class 4 under his more recent Principle of Computational Equivalence goes even further in a direction I'd rather see us retreat from.

I actually read the book by Johnson reviewed here for contrast while I was wading through Wolfram's tome. Emergence now sits among a very small pile of books I keep on my desk in case I need to refer to them. A New Kind of Science also sits on my desk, but mainly to elevate my iBook, especially since Wolfram made the whole book I available online. I had to grab Out of Control off the living room bookshelf, but it still ranks as my favourite from the '90s.

If you're interested in network theory in general, and as it applies to scientific collaborations, you could do much worse than checking out Mark Newman's publications, in particular this, this, and this.

If you're interested in network theory in general, and as it applies to scientific collaborations, you could do much worse than checking out Mark Newman's publications, in particular this, this, and this.

If you're interested in network theory in general, and as it applies to scientific collaborations, you could do much worse than checking out Mark Newman's publications, in particular this, this, and this.

There are a lot of attempts at solutions, depending on exactly how the problem is phrased and what solution is considered acceptable (what constitutes "maximizing the satisfaction of all parties"). Some approaches have included evolutionary adaptation, inductive behavior, bounded rationality, and statistical mechanics. You can search the physics e-print server for "El Farol" or "Minority Game" in titles or abstracts for some physics-based approaches (mostly in the cond-mat archive); Google will get you other approaches. Look around at the Santa Fe Institute; that's where the actual El Farol bar is that spawned the problem.

I thought I'd add a few interesting ideas and resources to this discussion.

Check out the works of Amory Lovins / L. Hunter Lovins / Paul Hawken;
they have an interesting book which can be read free online or be purchased
in print depending on one's desire --
Read 'Natural Capitalism' free online or buy the book!
Read 'Natural Capitalism' free online
Read 'Natural Capitalism' free online

Amory Lovins has a lot to do with the Rocky Mountain Instutute
Rocky Mountain Instutute and there's a lot more information about efficient
technologies and industrial / social evolutions there.

"Natural Capitalism: Creating the next industrial revolution" is all about
paradigm shifts that evaluates efficiency and resource conservation as
being key factors both for environmental reasons as well as economic reasons --
economics is about the market prosperity of the most efficient products and
services, and surely there are disadvantages in inefficient use of one's
inputs.

"Achieve multiple benefits with single expendutures" -- and the book/ebook
is full of really thought provoking and compelling practical paradigms to
illustrate the power of that thinking!

Ok so my next salient point and resource on the subject of power supply efficiency is to look beyond the power supply to the load and realize that
computing itself can be as close to a "zero power needed" technology as one
cares to implement. Current digital circuits waste the vast majority of their
power by irreversably converting 1's to 0's and 0's to ones, basically charging
up capacitors to make a high voltage "1" where there was no voltage before
and then wasting all that energy a bit later shunting it to ground / zero volts
to make a "0" again. This isn't necessary to achieve the computing function!
And here are some interesting readings on that area:

"Reversible Logic" is one such practical approach to it --
Article At MIT

http://www.google.com/search?ie=UTF-8&q=%22rever si ble+logic%22+%2BMIT

And otherwise: Book Info: "Complexity, Entropy and the Physics of Information"
"Complexity, Entropy and the Physics of Information"
a great read on the relationship between information theory, computing,
and thermodynamic entropy's relationship to data entropy, even touching
on how many "bits" of information a black hole must accumulate based upon
the entropy of the infalling matter/energy!

Besides classical circuit theory implementations like "Reversible Logic"
to save power there are very exciting opportunities in other quantum-computing
technologies like "Spintronics" (e.g. using the spin-quantum of currents flowing between magnetized metals / semiconductors to represent "1", "0" or
multi-level logic which is basically related to the way a NMR device gets
its signals):
Spintronics
Google It ...and various other quantum-effect computing technologies.

As for efficient power supplies, how about one that's 99% efficient,
generally non-toxic, cheap to manufacture (actually it's self manufacturing!)
and generates perfectly 'clean energy'?
Wired: Algae based fuel cells!
How about using the same kinds of photosynthesis that every green plant
on earth uses to split Hydrogen apart from Oxygen and create a microscopic
electrochemical fuel cell complete with the option of integrated
efficient 'storage batteries' for holding power when the sun's no

Contact: Nancy Ross-Flanigan rossflan umich edu
734-647-1853
University of Michigan

From football conferences to food webs: U-M researcher uncovers patterns in complicated networks

SEATTLE---The world is full of complicated networks that scientists would like to better understand---human social systems, for example, or food webs in nature. But discerning patterns of organization in such vast, complex systems is no easy task.

"The structure of those networks can tell you quite a lot about how the systems work, but they're far too big to analyze by just putting dots on a piece of paper and drawing lines to connect them," said Mark Newman, an assistant professor of physics and complex systems at the University of Michigan.

One challenge in making sense of a large network is finding clumps---or communities---of members that have something in common, such as Web pages that are all about the same topic, people that socialize together or animals that eat the same kind of food. Newman and collaborator Michelle Girvan, a postdoctoral fellow at the Santa Fe Institute in Santa Fe, New Mexico, have developed a new method for finding communities that reveals a lot about the structure of large, complex networks. Newman will discuss the method and its applications Feb. 15 at the annual meeting of the American Association for the Advancement of Science in Seattle.

"The way most people have approached the problem is to look for the clumps themselves---to look for things that are joined together strongly," said Newman. "We decided to approach it from the other end," by searching out and then eliminating the links that join clumps together. "When we remove those from the network, what we're left with is the clumps."

The researchers tested their method on several networks for which the structure was already known---college football conferences, for example. In college football, teams in the same conference face off more frequently than teams in different conferences. When inter-conference games do occur, they're more likely to be between teams that are geographically close together than between teams that are far apart. Plugging in information on frequency of games between pairs of teams in the 2000 regular season, Newman and Girvan tested their method to see if it could correctly sort the colleges into conferences. "There were a few cases where it made mistakes, but it got well over 90 percent of them right," said Newman. "It gave us the structure we were expecting, so that was encouraging."

Newman and Girvan---and other researchers who've learned about their work---have gone on to apply the technique to systems where the structure is not as well understood, looking at everything from networks of Spanish language web logs to communities of early jazz musicians to a food web of marine organisms living in Chesapeake Bay.

"Networks and other systems that we study are becoming increasingly large and complicated these days," said Newman. "New methods like this help us to make sense of what we see and to understand better how things work."

For more information:
Mark Newman
American Association for the Advancement of Science
Santa Fe Institute

known as

The Santa Fe Institute

This is not news.

Zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz.

Regards,
Kilgore

I've been hearing "emergent phenomena" used to describe behavior of systems that appears to be systematic but arises from the simple rules that govern the system in a non-obvious way.

So the emergent aspect has nothing to do with "violate"-ing the rules that start things in motion and more to do with the fact that the behavior comes about because of those rules, but is not something that an observer would easily anticipate or derive from considering the rules at a low level. (See, for instance this page in which "emergent phenomena" are defined as those best predicted through simulation. )

But, its always possible that the phrase has taken on a different meaning in the last few weeks, so I'll have to go find out.

Pity you couldn't get that article; it was really a fun read with a truly massive bibliography. If you were taught that the Miller-Urey experiment was proof of evolution, then your organic chemistry teacher was either wrong or you misunderstood. At any rate, this is the only example I have ever heard of. Still, the challenge remains: find me a textbook which claims that Miller-Urey is proof of evolution.

"Indeed physics and chemistry are deterministic - they go where the Gibb's free energy dictate they go. Which is why polypeptides don't spontaneously form."

So if you know this, then why make a comment you know to be false, ie chemistry being non-deterministic? Besides, polypeptides do spontaneously form under certain conditions. There is nothing special about an organism or the enzymes and ribozymes it uses to make this happen. It's all still the same chemistry. On a closely related note, I just found this really neat article by Stuart Kauffman (okay, it's just an editorial blurb in Nature on the actual article, Nature vol 382 pg 525-528 (1996) sadly not available online or I'd link it) on a 32-amino acid polypeptide that can autocatalyse its own synthesis by accelerating the condensation of 15- and 17-amino acid fragments in solution. I wonder what's been found in the six years since that was published?

"Aside from chlorophyll, where does adding sunlight produce anything but decay?"

There is nothing special or unique about chlorophyll. You add light or energy of some kind to a system, you (may) get some change. For light, you may get degradation of a compound if it has a photolabile group, you may get isomerization about a chemical bond, or fluorescence, or a change of phase, or drive some anabolic reaction. Photochemistry's a hopping field of study: just google "light polymerization" for one example that's especially topical. I myself had no idea that there was so much out there, commercial light polymerizers and all!

"I have read far more on the topic than the abstract you mention, it's just typical of the work in the field (probably why you selected that one)."

Yet you've also been trying to use a number of old creationist chestnuts which suggests either the abiogenesis material you've read is badly out of date or is written solely by creationists. Spend an afternoon on the talkorigins abiogenesis pages--what have you got to lose?

"You seem to understand fundamentals of chemistry - work out the equilibrium constant of a moderate sized protein in an aqueous solution, given the energy of peptide bonds for a selection of amino acids. Figure it out to 150 or 200 proteins in the peptide. I could give you the answer but working it out yourself you may learn something significant. "

Well, I would like to think that I haven't wasted the last decade I've spent studying biochemistry and chemistry. But far from informative and speaking of creationist chestnuts, I suspect what you're asking me to do is one of the classics. You want me to sit down and calculate the odds of a peptide forming--a specific length, a specific sequence, from a pool of amino acids, at random. In the abiogenesis link that I provided in my first post in this thread is ample description of why this argument is fallacious, right up at the top under the heading "Problems with the creationists' "it's so improbable" calculations."" You can't miss it--they even talk about the same 32-mer autocatalytic protein that I found just by googling around, and the page links to more examples of similar autocatalytic proteins! Wow. SunY looks really interesting.

Hopefully QWERTY will indeed be the next cursive, in this regard.
As an exmaple, Dvorak's key layout is, indeed, more efficient for typists than the QWERTY. Early research on that topic might have been biased by Dvorak himself, but a more robust examination provided solid evidence five years ago.
With decades of further ergonomics and language learning under our belts since Dvorak made his design, one would think we could improve upon QWERTY even more drastically today.

...I was also messed with later when I contemplated what is being said: "You're not here to make a choice, you've already made it, you're here to find out why you made that choice." Wow. So life isn't making choices, but discovering who we are and why we do what we do.

This quote has an interesting parallel to Daniel Dennett's Theory of Consciousness. Dennett argues that the way we experience our lives is essentially false. He says we have a very limited form of free will - the thing that is "us" is in fact a virtual machine that runs on the brain's wetware and is not a mechanism for making choices (though I simplify greatly). The brain is a set of (very many) simplistic parallel processes that perform basic mental tasks including decision making. Consciousness is a virtual, learnt serial process that constructs an ongoing narrative to make sense of the conflicting reports and decisions that these hidden ("subconscious") processes are making.

Thus the subconscious brain is what makes decisions and the conscious "self" rationalizes the decisions by pretending that it makes the choice itself. Essentially the subconscious has already made the choice and the mind is attempting to find out why you made that choice.

If you believe in free will and a more traditional concept of consciousness, there are some very disturbing experiments that show people acting on decisions and only afterwards making the conscious "decision" that "causes" the action. In other words you (sometimes?) do things before you have decided to do them.

I hope, but doubt, that the Wachowski brothers are going to use this model in Matrix Revolutions. How cool would it be if the Matrix and the "real" world of Zion were ultimately the inside of a human mind, say Neo's?

You can find out more about Dennett in his book "Consciousness Explained". A good review gives an overview of his philosophy. Highly provocative reading.

Especially: Evolution, Ecology and Optimization of Digital Organisms and Zen and the Art of Creating Life

2)The Santa Fe Institute

3)Kevin Kelly's Out of Control: The New Biology of Machines, Social Systems and the Economic World

I tried Dvorak for a while. It was novel, and I go through phases with things like that. Didn't change my life or anything.

My work wouldn't pick up a for-real Dovrak keyboard for me, so I'd just switch the OS's keyboard layout on the fly -- it was an OS 8 Mac office -- and learned to use the new layout blind, on keys that showed the QWERTY letters. (Kind of a fun little security measure, too, when someone sitting down to your machine gets all the wrong letters...)

Despite the convincing-sounding rationale behind it, there's real debate over whether Dvorak's an improvement over QWERTY. It makes intuitive sense when you hear the arguments, but there's research -- like this article comparing speed on both versions either way.

Her name is Laurie Garrett she works for Newsday, she's a well known journalist/writer.

The Swarm Development Group

SFI

Complex Systems

and the full text of the interview. I'm starting to think he's onto something, given such newer areas of research as chaos theory and complexity . For the uninformed, these are the folks who bring you such things as fractal generation and the "butterfly effect". (I have purchased hardcopy/books a few years ago). I hope he will correct me if I'm wrong, but I think that what Jaron's question really is, is "At which point can we not use complex computations/computers to model the "real" world (FSVO $REAL)? If our computational mechanisims and models approach the complexity of the "real", how can we validate our results against a third-party?" Just an idea.

Firstly:

of the emerging science of complexity
Damn funny, that...

Secondly, it was in New Scientist, years ago ( paper edition ) where it was noted that each dimension of complexity is equivalent to about an order-of-magnitude increase in detail: Having neurons ( synthetic neural-net ) that stimulate other neurons, only, in one system, and having neurons-that-stimulate and neurons-that-suppress in a second system, the first system would require 10x~100x ( IIRC, it actually may have been a factor of 10 000 ) as many neurons to get the job done, as the second.

Interestingly, our neurons communicate by stimulative synapses, by suppressive synapses, by pattern-of-signal, and by nitrous-oxide diffusion ( as well as possibly electrical conduction ), so the mere 100 000 000 000 neurons we're born with
( with ~100 synapses, and ~1000 dendrites on each one, +/- an order-of-magnitude, in short a stunning quantity of connections )
can accomplish as much as many-more of a less-dimensionally-deep neural-net...

And that is boggling, but the principle, that each extra ( necessary ) dimension removes the need for a quantum-order-of-magnitude of detail-level-things, holds reasonably well...
... is elegant, and very useful ( try simplifying your business/processes/anything this way... 'The 7 Habits..' does this, unconsciously... )

PS, here's the link from above, clickable, for your incconvenience:
http://www.santafe.edu/

"The Santa Fe Institute is a private, non-profit, multidisciplinary research and education center, founded in 1984. Since its founding SFI has devoted itself to creating a new kind of scientific research community, pursuing emerging science."

"Operating as a small, visiting institution, SFI seeks to catalyze new collaborative, multidisciplinary projects that break down the barriers between the traditional disciplines, to spread its ideas and methodologies to other individuals and encourage the practical applications of its results."

Worthy intention, 't seems...

Consider this thought experiment: scan a brain on a low level (neurons and their interconnections), and then put the whole thing into a computer (that will be available in say 40 years, according to some estimates; there are also currently quite good models of neuronal behavior, and I don't mean the simplified ANNs we often hear of), and then just run it. It doesn't matter that you don't understand how it works, it works anyways -- proof of concept -- not to say that's the most practical way to do AI, but just to show it's possible.

About Godel -- Godel's theoremis very specific, and says absolutely NOTHING about human intelligence

Like the article linked above says, it has been much abused (Penrose comes to mind). As far as your statement that intelligence is ultimately axiomatic, I don't know what you mean. You say the social sciences would become mathematical scienes: this is in fact not the case simply because social systems are too large, intricate, and complicated in order to consider them on the fundamental level (i.e. physics). It is a practical issue. It is perfecly clear, however, that theoretically social behavior is based on biology which reduces to chemistry which reduces to physics.

> Perhaps we could eventually develop AI to the point where it can simulate lower animal behavior [popsci.com], but the search for machines capable of human levels of thought is ultimately futile.

This comment is no better than the claims of the message I originally replied to.

Usually the subject is the rottenness of both of them :) I can't imagine that when a diversity of opinions is represented in a two party system, that the parties represent much of an ideology, but there are some differences of style.

This interview with George Lakoff is about the difference between the perceptions of conservatives and liberals. I think it's insightful. Consider a crude mapping of conservative to republican and liberal to democrat.

Generation X was a book about the growth of youth culture in England in the 60s. It's an insult aimed at those of us born roughly between the end of the 60s and the middle of the 70s who were told we weren't going to amount to anything because we whined too much. Ironically, the people telling us that were told they weren't going to amount to anything, either. And as much as I hate to say "me too", check this out for some further reading.

In America the earthquake of 1755 was widely ascribed, especially in Massachusetts, to Franklin's rod.

The Rev. Thomas Prince, pastor of the Old South Church, published a sermon on the subject, and in the appendix expressed the opinion that the frequency of earthquakes may be due to the erection of ``iron points invented by the sagacious Mr. Franklin.'' He goes on to argue that ``in Boston are more erected than anywhere else in New England, and Boston seems to be more dreadfully shaken. Oh! there is no getting out of the mighty hand of God.''

Three years later, John Adams, speaking of a conversation with Arbuthnot, a Boston physician, says: ``He began to prate upon the presumption of philosophy in erecting iron rods to draw the lightning from the clouds. He railed and foamed against the points and the presumption that erected them. He talked of presuming upon God, as Peter attempted to walk upon the water, and of attempting to control the artillery of heaven.''

As late as 1770 religious scruples regarding lightning-rods were still felt, the theory being that, as thunder and lightning were tokens of the Divine displeasure, it was impiety to prevent their doing their full work. Fortunately, Prof. John Winthrop, of Harvard, showed himself wise in this, as in so many other things: in a lecture on earthquakes he opposed the dominant theology; and as to arguments against Franklin's rods, he declared, ``It is as much our duty to secure ourselves against the effects of lightning as against those of rain, snow, and wind by the means God has put into our hands.''

In Switzerland, France and Italy, popular prejudice against the lightning rod was ignited and fueled by the churches and resulted in the tearing down of lightning rods from many homes and buildings, including one from the Institute of Bologna, the leading scientific institution in Italy. The Swiss chemist, M. de Saussure, removed a rod he had erected on his house in Geneva in 1771 when it caused his neighbors so much anxiety that he feared a riot.

In 1780-1784, a lawsuit about lightning rods gave M. de St. Omer the right to have a lightning rod on top of his house despite the religious objections of his neighbors. This victory established the fame of the lawyer in the case, young Robespierre.

In America, Rev. Thomas Prince, pastor of Old South Church, blamed Franklin's invention of the lightning rod for causing the Massachusetts earthquake of 1755.

In Prince's sermon on the topic, he expressed the opinion that the frequency of earthquakes may be due to the erection of "points invented by the sagacious Mr. Franklin." He goes on to argue that "in Boston more are erected than anywhere else in New England, and Boston seems to be more dreadfully shaken. Oh! There is no getting out of the mighty hand of God."

It took many years for scientists to convince the priests to attach a lightning rod to the spire of St. Bride's Church in London, even though it had been destroyed by lightning several times.

Check out John Horgan's feature on SFI in Scientific American, "From Complexity to Perplexity" (Scientifc American, June 1995; the Web archive only seems to go back to 1996 now) and Melanie Mitchell's retort, ("Complexity and the Future of Science")

Both make for interesting reads on the Sante Fe Institute.

He is one of those rare individuals that consistantly produce.

Uhh, I hate to disagree with you but how is going into hiding to write a book "producing"? When a person is risen to the level of celebrity scientist, they are going to get press when they want it, no matter what they say. He is neither the first person to marvel at CA's and while cool, we have yet to see whether his ideas are truely significant or not.

-Sean

OK, our friend Leibowitits presents a reasonably convincing argument about file sharing.... file sharing is huge, and we don't see any appreciable change in sales, so something else must be going on. I buy that.

I have to question his credibility just a little bit. No network effect? The term "path dependence" is fairly well distributed through the economic literature, and I can't recall the name, but I once tried to work through a paper on it from someone at the Santa Fe Institute... not exactly a bunch of intellectual lightweights (at the very least as credible as anyone from the Cato Institute). The paper supported the network effect.

The Salon article almost presents Leibowitz as having debunked the concept rather than challenged it. Lots of handwaving if you ask me.

But then again, that's been my experience with econ in general. : )

When you think about the Athlon on your desk running GNU/Linux, you could consider it not so much as a "computer" itself but as an tiny interface to a deep computational reality that is the universe. That is, your Athlon only computes because it is a certain special pattern of bits in a larger system which supports computation. So, your Athlon provides a special kind of interface between your mind and that larger computationally reality -- say, like a Series 1 minicomputer was often used to provide full screen editing interfaces to much larger IBM mainframes. An Athlon may be a tiny little keyhole to peak through compared to the size of the universe, but it is perhaps better than nothing. Think of your Athlon as being more like a telescope or microscope than a thing of study itself (not to say an Athlon can't be studied of course). Someday, perhaps we will store information in the very fabric of reality itself, and computations will be perfomed on that information without physical silicon needing to be present. Probably we'll still just mainly use it to embed smiley faces everywhere though. :-) Or edit them if one is so inclined. :)

By the way, I first saw this idea of "the universe is a computer" referenced in the 1988 book by Robert Wright called "Three Scientists and their Gods:Looking for Meaning in an Age of Information" in the part about Edward Fredkin, see for example: http://www.santafe.edu/~johnson/reviews.wright.htm l and: http://digitalphysics.org/Publications/Fredkin/New -Cosmogony/

This means he's almost certainly a crank. If actual scientists were arguing heavily about it, there might be a bit more uncertainty. But if the debate is happening amongst people whose knowledge of physics comes mainly from Star Trek, then that pretty much settles the matter in advance.

Wolfram will probably end up having a place on the intellectual fringes, worshipped by people who are often smart but who haven't bothered/aren't trained well enough to see why specialists don't really pay attention to them. In nerd idea-space Ayn Rand is the other main example of this type.

The best comment I've read about Wolfram's book comes from Cosma Shalizi, a physicist working at the Santa Fe institute, who specializes in cellular automata. He comments [scroll down on link]:

Dis-recommended: Stephen Wolfram, A New Kind of Science [This is almost, but not quite, a case for the immortal ``What is true is not new, and what is new is not true''. The one new, true thing is a proof that the elementary CA rule 110 can support universal, Turing-complete computation. (One of Wolfram's earlier books states that such a thing is obviously impossible.) This however was shown not by Wolfram but by Matthew Cook (this is the ``technical content and proofs'' for which Wolfram acknowledges Cook, in six point type, in his frontmatter). In any case it cannot bear the weight Wolfram places on it. Watch This Space for a detailed critique of this book, a rare blend of monster raving egomania and utter batshit insanity.]

I await solid arguments to the contrary --- ie, arguments that don't start from any of the following premises:
1. But he was a boy genius at CalTech and Feynman said so!
2. But he wrote Mathematica, which is obviously really hard!
3. But if he's right this will change the world!
4. But other Scientists are ignoring/laughing at/refuting him only because they are jealous of his enormous brain!
5. But he only ignored peer review because he's so brilliant!
6. But every work of genius always seems crazy when it first appears!

I leave it was an exercise to the reader to show why Wolfram's supporters shouldn't rely on these points (although Wolfram himself apparently does).

As a letter writer to Salon points out, it seems that Wolfram thinks that he's discovered Complexity Theory all by himself. The Salon article certainly gives that impression -- not having read the book, I can't make my own judgment.

The Salon writer writes as if cellular automata were some silly mathematical curiosity (or worse, the writer thinks that CA is recent to computing) that Wolfram "rediscovered" and took seriously for the first time. Of course that's absurd.

The Santa Fe Institute was founded jointly around 1984 by the eminent Nobel Laureate, physicist Murray Gell-Mann, and several others. Stuart Kauffman has researched and written on complexity for many years.

I myself have been following, as a layperson, complexity theory for about fifteen years. In 1991 I had the opportunity to be an undergraduate intern -- an opportunity I didn't follow up on because of my severe academic workload, but an opportunity I will always regret not taking advantage of. Undergraduate intern positions are much more competitive now. This eleven years has made the difference between "bleeding edge" and "cutting edge". Or perhaps complexity theory is even mainstream. I've noticed a burgeoning graduate school interest in complexity studies programs.

Complexity theory intersects many disciplines, and it involves several related ideas such as chaos theory, modeling, self-reference, artificial life, and others. It's evolved into a fairly rigorous discipline, and the more formalized idea of "complex adaptive systems" forms the core. For those who have read Douglas Hofstadter's book, Godel, Escher, Bach, (a very influential book for many of us) published around '82, many of these ideas will be familiar.

Wolfram's quip that seems so risible is really only an overstatement of the central idea of complexity theory: that a limited number of "rules" can give rise to extremely complex behavior. This was the surprise of cellular automata, exemplified by Conway's "Life", invented in 1970. But the underlying idea goes as far back as John von Neumann. Wolfram has done some interesting work in CA. But it sure as hell isn't his idea. For many in the Slashdot community, this is all as familiar as the back of their hands. But apparently there's still a lot of people that should be aware of this stuff that are not.

Finally, many people here would probably be interested to know that SimCity's designer, and Maxis, have had some association with SFI. This makes sense because the emergent behaviors of complex systems are not (as a practical matter) deductively predictable -- their behavior must be studied. The techniques of systems modeling are requisite. SimCity was the general public's first accessible insight into just how fascinating and educational systems modeling can be.

As a letter writer to Salon points out, it seems that Wolfram thinks that he's discovered Complexity Theory all by himself. The Salon article certainly gives that impression -- not having read the book, I can't make my own judgment.

The Salon writer writes as if cellular automata were some silly mathematical curiosity (or worse, the writer thinks that CA is recent to computing) that Wolfram "rediscovered" and took seriously for the first time. Of course that's absurd.

The Santa Fe Institute was founded jointly around 1984 by the eminent Nobel Laureate, physicist Murray Gell-Mann, and several others. Stuart Kauffman has researched and written on complexity for many years.

I myself have been following, as a layperson, complexity theory for about fifteen years. In 1991 I had the opportunity to be an undergraduate intern -- an opportunity I didn't follow up on because of my severe academic workload, but an opportunity I will always regret not taking advantage of. Undergraduate intern positions are much more competitive now. This eleven years has made the difference between "bleeding edge" and "cutting edge". Or perhaps complexity theory is even mainstream. I've noticed a burgeoning graduate school interest in complexity studies programs.

Complexity theory intersects many disciplines, and it involves several related ideas such as chaos theory, modeling, self-reference, artificial life, and others. It's evolved into a fairly rigorous discipline, and the more formalized idea of "complex adaptive systems" forms the core. For those who have read Douglas Hofstadter's book, Godel, Escher, Bach, (a very influential book for many of us) published around '82, many of these ideas will be familiar.

Wolfram's quip that seems so risible is really only an overstatement of the central idea of complexity theory: that a limited number of "rules" can give rise to extremely complex behavior. This was the surprise of cellular automata, exemplified by Conway's "Life", invented in 1970. But the underlying idea goes as far back as John von Neumann. Wolfram has done some interesting work in CA. But it sure as hell isn't his idea. For many in the Slashdot community, this is all as familiar as the back of their hands. But apparently there's still a lot of people that should be aware of this stuff that are not.

Finally, many people here would probably be interested to know that SimCity's designer, and Maxis, have had some association with SFI. This makes sense because the emergent behaviors of complex systems are not (as a practical matter) deductively predictable -- their behavior must be studied. The techniques of systems modeling are requisite. SimCity was the general public's first accessible insight into just how fascinating and educational systems modeling can be.

The theory supposes that life did not start on Earth so your criticism is invalid. However, the question is relevant: "How did life begin?" Another possibility of determining the likelihood of finding life in other regions of the cosmos is by employing Complexity Theory and the study of Emergent Systems. One of the implications of these sciences is that it predicts that: in a sufficiently complex system, (i.e. the Universe, Earth etc...) and over a sufficiently lengthy period of time, (i.e. billions of years) the probability of a system exhibiting "life-like" characteristics approaches certainty. See: The Santa Fe Institute, and the badly written but informative, Out of Control

In the abstract he states:

"In the Demographic Prisoner's Dilemma, neither assumption is made: agents with finite vision move to random sites on a lattice and play a fixed culturally-inherited zero-memory strategy of cooperate (C) or defect (D) against neighbors."

After his citation of Michael Oliphant's paper (1994) Evolving Cooperation in the Non-Iterated Prisoner's Dilemma: The Importance of Spatial Organization published in Brooks, R. and Maes, P. (eds.) Proceedings of the 4th Artificial Life Workshop, pp 349-352, The MIT Press. Epstein proceeds to attempt to justify his paper in comparison to Oliphant's genetic-algorithm paper by emphasizing his definition "culturally-inherited" as follows:

"Perhaps it is worth emphasizing that, in adopting this assumption of a fixed agent strategy, we are not claiming that human strategies are literally hard-wired genetically. Rather, for modelling purposes, we are assuming that they are culturally transmitted from parents to children--vertically transmitted--with high fidelity, like certain religious or ethnic affiliations, tastes, and native tongues. 19 Below we consider the effect of degradation (mutation) in this vertical transmission fidelity."

This definition, as well as from his other descriptions of his algorithms differ in no way from Oliphant's 'genetic' tendencies to defect or cooperate, except to make the environment 2 dimensional instead of one dimensional and to make spatial structure evolve out of variation in "sight" rather than a simple gaussian distribution of mating -- neither of which can be used to distinguish "culturally-inherited" from "genetically-inherited" traits.

While it is interesting to extend Oliphant's work on genetic algorithms to 2 dimensions, it sheds little new light on the subject.

What would have been far more interesting, especially from the Brookings Institute's charter, and from Epstein's position of responsibility for defense policy analysis there, would have been to do a genuine investigation of cultural transmission in the presence of genetic selection as well as cultural selection:

1. Use Oliphant's model for the evolution of communications given in Oliphant, M. (1996) The Dilemma of Saussurean Communication. BioSystems 37 (1-2), pp 31-38 as the basis for the genetic evolution of cultural transmission.
2. Include Oliphant's genetic evolution of tendencies toward defection vs cooperation.
3. Allow certain internal states to override the genetic predisposition toward defection or cooperation.

Then study under what conditions genotypes arise that tend to transmit 'cooperator culture' while they, themselves, transmit 'defector genes'.

The above extensions to Oliphant's one dimensional gaussian model should be sufficient to illuminate the nature of such 'meta-defection', although I'm sure variations and elaborations on his minimalist environmental model would become obviously interesting in short order.

``The French Disease'' is what the Italians of the 16th century called syphilis; the French, naturally, called it the Italian Disease, or the Disease of Naples

Really. Because there's times I'm very, very, happy not to be using Windows, such as when the latest Outlook or Word infection is going around.

Sig: What Happened To The Censorware Project (censorware.org)

Hitler was in no way a christian, in fact his aryan beliefs were in almost complete contradiction to any christian belief. And the holocaust was based on race, not religion.

Hitler was indeed a christian. He did very evil things, but he was still a christian. Your second point however, is correct, the holocaust was about race, however the eugenicists saw it..

The Christian religion, is one of the primary reasons for the development of Europe to where it is today. Considering the immense influence it has had over the last 1500 years, it it not supprising that bad things came along with the good. The problem is with human nature, compared to any powerful instituion before it, it was a model of civility.

In fact, Christianity was one of the prime factors holding BACK Western European civilization for the 6-800 years following the fall of the roman empire. What need is there to innovate and to improve your lot in life if the messiah's second coming is right around the corner? It was only after Greco-Roman thought was re-introduced via Islam that Western European civilization started its upswing. Even later, the church had to be pulled kicking and screaming through the centuries by science. From Gailileo to Creationism, the church has had a great damping effect on scientific progress. See A History of the Warfare of Science with Theology in Christendom for many, many more examples.

I'm not trying to take a dump on your beliefs. If they work for you, great. Have a cookie. But don't try to paint Christianity, or any other religion too rosy. Like most institutions, it has its darker side, and Christianity has a very dark one indeed.

If a bunch of people get together and decide something is important, then through that community effort it becomes important. Google is our Global Brain. The best solution is for all of use to speak our voice on on a blog. That way google's results better match with what is important to us as a community.
-----
Virtual Personalities, inc. Verbots.com - start the dialog(sm).

The site I was referring to is: Cosma's Homepage. BUT: he's dropped the "pessimized for IE" schtick, possibly because MS fixed their defaults, or maybe he just got bored with it. There's a reference to it in his "What's New" changelog from 1995, but that's all now. Hope that's not too much of a let down.

Anyway, I like this guy's site much. He's got a physics background, but also has a wide range of intellectual interests, and when the web was new he started putting his notebooks on-line, for anyone to browse. Kind of like a wikipedia written by one guy. You might want to give his stuff a glance some time before you go back to working on your Transformers fan-fic site.

There has been some serious academic work done by many researchers into this field. I was lucky enough to be able to see Duncan Watts present his research in the Small-World phenomena a few years ago. While his talk starts out with a mention of the Kevin Bacon game, it continues into more serious areas, including the way the neural network of the worm C. elegans conforms to the small-world predictions and the connectivity of power grids. The implications into computer networks should be worth at least a few moments of thought to all of us.