You are currently browsing the tag archive for the ‘Invisible Hand’ tag.

Photo – The Aftermath Network research group: Manuel Castells, Terhi Rantanen, Michel Wieviorka, Sarah Banet-Weiser, Rosalind Williams, John Thompson, Gustavo Cardoso, Pekka Himanen, You-Tien Hsing, Ernesto Ottone, João Caraça and Craig Calhoun.

Oh!… nostalgia. But can you read between the lines? Could you perceive the cynical TV ads. The underlying media mantra that you are not being productive enough. That is you, ultimately the reason for the global crisis. That ‘something‘ went broken. Are you having a feeling that all this mess could give rise to National Socialism, again? That, reversed nostalgia plays a role too?! Well, … shortly after the beginning of the financial crisis of 2008 sociologist Manuel Castells gathered a small group of international top intellectuals to ponder the crisis. While the crisis expanded, Castells named his group ‘The Aftermath Network‘, a direct reference to the new world which according to him will emerge from the ashes of the crisis.

Under the venue and patronage of Calouste Gulbenkian Foundation, Lisbon-Portugal, Castell‘s multidisciplinary research group meet every year with the aim of discussing in real time and from different angles the societal and cultural consequences of the worldwide economic collapse. Now, thanks to the Dutch VPRO Backlight, a new documentary has been produced (uploaded last week over YouTube), reflecting part of those meetings. Entitled ‘Aftermath of a Crisis‘ (above) is a 48 minute documentary reporting the world incertitude, facing a global fallacy, as well as the emergence of new social movements and protests in Spain, Greece, Portugal and London. Unfortunately, as I said the other day (link), there are increasing signs that: Keynesianism is now Bankism. Know what? Next time someone or some institution comes to you covered by a veil of nostalgia, even a thin one, do yourself a favor: put your brain in maximum alert.

Advertisements

Book cover from Economics Nobel prize (2008), Paul Krugman (link): Paul R. Krugman, “The Self-Organizing Economy“, Cambridge, Massachusetts, and Oxford: Blackwell Publishers, 1996. What follows is the entire excerpt review on his book, by Cosma Shalizi, a friend and colleague, done in March 1996 with minor corrections in 1997 and 2006:

[…] Paul Krugman cannot be accused of lacking good opening lines:

    Is an economic slump like a hurricane, or is it more like an earthquake? Is a growing city like an embryo, or is it more like a meteorite?

Obviously some explaining needs to be done here.

The term “self-organization” seems to have entered the language in a 1947 paper in the Journal of General Psychology on cybernetic mechanisms of adaptation, though related ideas are considerably older. It has, of course, become a buzzword, indeed an indispensable element in modern techno-cant – I was once on a mailing list where some people proposed to write a “self-organizing” novel – but a lot of real science carries on under the label, in some remarkably different fields:

    [W]hat links the study of embryos and hurricanes, of magnetic materials and collections of neurons, is that they are all self-organizing systems: systems that, even when they start from an almost homogeneous or almost random state, spontaneously form large-scale patterns. One day the air over a particular patch of tropical ocean is no different in behavior from the air over any other patch; maybe the pressure is a bit lower, but the difference is nothing dramatic. Over the course of the next few days, however, that slight dip in pressure becomes magnified through a process of self-reinforcement: rising air pulls water up to an altitude at which it condenses, releasing heat that reduces the pressure further and makes more air rise, until that particular piece of the atmosphere has become a huge, spinning vortex. Early in the process of growth an embryo is a collection of nearly identical cells, but (or at least so many biologists believe) these cells communicate with each other through subtle chemical signals that reinforce and inhibit each other, leading to the “decision” of some cells to become parts of a wing, others parts of a leg. [pp. 3–4]

This is vague, for which I am grateful, since sharpening the notion of self-organization into something quantifiable is the subject of my thesis. But let us draw a veil over this and press on.

There’s a sense in which economists have been studying little but the “spontaneous formation of large-scale patterns” ever since Adam Smith and the creation of self-regulating markets, but Krugman is not interested in convincing his profession that it has been speaking prose all its life; it would, in his words, “be entitled to change the channel.” Rather he wants to look at the way economies organize themselves in space and over time, which they do in a most conspicuous way. (There is, however, a brief discussion of technological lock-in in chapter six.) Krugman picks out three examples in particular: the way cities differentiate themselves into specialized districts; the power-law distribution of city sizes; and business cycles.

That cities – even Los Angeles – are not homogenous lumps, with everything mixed together, seems to have been true from earliest times. Some of this is simply because different locations have different advantages – dockyards go by the water, fortresses on heights, and brothels and bars near fortresses. Some of it is due to zoning boards, planning commissions, real-estate magnates and red-lining, to say nothing of the police and cross-burning – whether such forces contribute to urban self-organization is a delicate question, and in any case Krugman is silent about them. Still, this leaves a lot of differentiation which seems to be due to nothing but self-reinforcement, which (unlike zoning boards and red-lining) has actually been studied in economic theory, especially by economic geographers, for some time. (Krugman is at pains to point out that self-organization was not unknown to economists before the arrival of missionaries from Santa Fe.) He begins his discussion of this with so-called “edge cities,” and then passes on to a marvelously elegant illustration from Thomas Schelling’s marvelously elegant book, Micromotives and Macrobehavior, which suggests how the former (requiring that at least 37% of your neighbors be like yourself) can lead to the latter (massive segregation). He then dives into a discussion of “urban morphogenesis” directly inspired by Turing’s classic work on embryological morphogenesis. He assumes his city is one-dimensional and either infinite or circular, but claims no more value for it than that of qualitative illustration; I can think of physicists who should be so modest. Self-organization happens here because the initial random noise contains components which correspond to many different patterns in nucleo, and the dynamics are such that some of these get magnified faster than others. The pattern which grows fastest ultimately dominates the system, which is called “pattern selection” in traditional reaction-diffusion systems. [Note containing the words “Fourier decomposition.”]

A power law distribution means that the number of objects whose size is at least S is proportional to S^a, for some (hopefully negative) constant a. It happens that the size of cities obeys a power law known as Zipf’s law, which is usually stated thus: the size of a city is inversely proportional to its rank order so that, for example, the 100th largest city is a tenth the size of the 10th largest city. This rule is almost exactly true of the sizes of American cities (it corresponds to a value of a of -2), and has been for at least a century. Physicists have liked power laws ever since Galileo, and recently we’ve developed a taste for power law distributions; Prof. Per Bak and his disciples sometimes seem to want to claim everything obeying a power law distribution for “self-organized criticality.” Krugman explains the power law distribution as an outcome of growth processes where the expected rate of growth is independent of the size already attained. Such processes do, in fact, generate power laws, and have been known to for some time – Herbert Simon proposed one, “in a completely impenetrable exposition,” in 1955. Alas, none of them are as regular as the empirical data!

At this point Krugman tells us that what we have just seen are order from instability (“When a system is so constituted that a flat or disordered structure is unstable, order spontaneously emerges.” – p. 99) and order from random growth (“[O]bjects are formed by a growth process in which the expected rate of growth is approximately independent of scale, but the actual rate of growth is random.” – p. 100). He declines, thankfully, to call these universal laws of self-organization, but he does suggest they are “principles,” or rather common ways of self-organizing.

Temporal self-organization in the economy is more familiarly known as business cycles, or yet more familiarly as booms and crashes (err, depressions; err, recessions; err, slumps; err, slow-downs). Since Keynes (at least) the idea that these are in some way self-reinforcing has been common, and Krugman resurrects a body of Keynesian theory from the ’50s, “non-linear business cycle theory.” This is of the order-from-instability type, and so predicts a characteristic size to business cycles, which, on a comparison of 1933 with the recent unpleasantness, or even the early 1980s, is less than plausible. Krugman also presents an order-from-random-growth theory – really percolation theory in wolf’s clothing – which avoids that problem at the cost of “[making] less contact with what seems to happen during a boom or slump,” and predicting a power law distribution for business fluctuations, which is not observed. Charitably, Krugman chooses to “regard them both more as illustrations as how one might approach self-organization in time than as finished statements of how one actually ought to do it.” Some such theory will be necessary if we are not to continue treating shifts in aggregate demand as external shocks administered, perhaps, by the vengeful specter of Karl Marx.

If this were a formal and comprehensive treatise, I would be disappointed by the passing over of evolutionary and institutional economics; the cavalier starting of models from tabulæ rasæ rather than already-differentiated settings; the fact that most of the models are what in physics would be called “phenomenological,” i.e. they don’t try to connect to the underlying mechanisms, such as markets; the absence of even qualitative comparisons with empirical data; and the indifference to exogenous forces, natural , social or political, which in practice are very important in all of the topics Krugman discusses. But this is not a formal and comprehensive work; that will have to wait for a good many years. It is a self-described “discourse” of exactly a hundred pages, a very brief introduction and an appeal for further development, for the work which will make the treatise possible. As befits such a book, Krugman’s writing is clear, informal and concise (but then, it usually is). His attitude towards the mathematics is that it should be used and not seen; accordingly we get the hypotheses once as stories (“I do not want to dignify them by calling them models”); a second time with a bit of calculus; and a third time in an appendix for those who want the nitty-gritty. (Even there he draws the line at Fourier decomposition and linear stability analysis; phase space and attractors are explained verbally, and well, in the body of the text.) The economics should be accessible to anyone who’s taken Econ. 1, and probably many (such as your humble narrator) who haven’t. The book will be of particular interest to those crossing the bridge from economics to self-organization and dynamics in either direction, but most educated readers should find it informative and engaging. […] Cosma S. Shalizi, 1996.

(pic. – click to enlarge) Summer time in here, you know?! So, this will be my next T-shirt: “First, the Economy took over Politics. Now, Finance took over Economy. Bit by bit, planet Earth bounds to be a giant speculation machine“. @ViRAms April 28 2011 (link).

Animated Video – Lively RSA Animate [April 2010], adapted from Dan Pink‘s talk at the RSA (below), illustrates the hidden truths behind what really motivates us at home and in the workplace. [Inspired from the work of Economics professor Dan Ariely at MIT along with his colleagues].

What drives us? Some quotes: […] Once the task called for even rudimentary COGNITIVE skills a larger reward led to poorer performance […] Once you get above rudimentary cognitive skills, rewards do not work that way [linear], this defies the laws of behavioural physics ! […] But when a task gets more complicated, it requires some conceptual, creative thinking, these kind of motivators do not work any more […] Higher incentives led to worse performance. […] Fact: Money is a motivator. In a strange way. If you don’t pay enough, people won’t be motivated. But now there is another paradox. The best use of money, and that is: pay people enough to take the issue of money off the table. […] …Socialism…??

[…] Most upper-management and sales force personnel, as well as workers in many other jobs, are paid based on performance, which is widely perceived as motivating effort and enhancing productivity relative to non-contingent pay schemes. However, psychological research suggests that excessive rewards can in some cases produce supra-optimal motivation, resulting in a decline in performance. To test whether very high monetary rewards can decrease performance, we conducted a set of experiments at MIT, the University of Chicago, and rural India. Subjects in our experiment worked on different tasks and received performance-contingent payments that varied in amount from small to large relative to their typical levels of pay. With some important exceptions, we observed that high reward levels can have detrimental effects on performance. […] abstract, Dan Ariely, Uri Gneezy, George Loewenstein, and Nina Mazar, “Large Stakes and Big Mistakes“, Federal Reserve Bank of Boston Working paper no. 05-11, Research Center for Behavioral Economics and Decision-Making, US, July 2005. [PDF available here] (improved 2009 version below)

Video lecture – On the surprising science of motivation: analyst Daniel Pink examines the puzzle of motivation [Jul. 2009], starting with a fact that social scientists know but most managers don’t: Traditional rewards aren’t always as effective as we think. So maybe, there is a different way forward. [Inspired from the work of Economics professor Dan Ariely at MIT along with his colleagues].

[…] Payment-based performance is commonplace across many jobs in the marketplace. Many, if not most upper-management, sales force personnel, and workers in a wide variety of other jobs are rewarded for their effort based on observed measures of performance. The intuitive logic for performance-based compensation is to motivate individuals to increase their effort, and hence their output, and indeed there is some evidence that payment for performance can increase performance (Lazear, 2000). The expectation that increasing performance-contingent incentives will improve performance rests on two subsidiary assumptions: (1) that increasing performance-contingent incentives will lead to greater motivation and effort and (2) that this increase in motivation and effort will result in improved performance. The first assumption that transitory performance-based increases in pay will produce increased motivation and effort is generally accepted, although there are some notable exceptions. Gneezy and Rustichini (2000a), for example, have documented situations, both in laboratory and field experiments, in which people who were not paid at all exerted greater effort than those who were paid a small amount (see also Gneezy and Rustichini, 2000b; Frey and Jegen, 2001; Heyman and Ariely, 2004). These results show that in some situations paying a small amount in comparison to paying nothing seems to change the perceived nature of the task, which, if the amount of pay is not substantial, may result in a decline of motivation and effort.

Another situation in which effort may not respond in the expected fashion to a change in transitory wages is when workers have an earnings target that they apply narrowly. For example, Camerer, Babcock, Loewenstein and Thaler (1997) found that New York City cab drivers quit early on days when their hourly earnings were high and worked longer hours when their earnings were low. The authors speculated that the cab drivers may have had a daily earnings target beyond which their motivation to continue working dropped off. Although there appear to be exceptions to the generality of the positive relationship between pay and effort, our focus in this paper is on the second assumption – that an increase in motivation and effort will result in improved performance. The experiments we report address the question of whether increased effort necessarily leads to improved performance. Providing subjects with different levels of incentives, including incentives that were very high relative to their normal income, we examine whether, across a variety of different tasks, an increase in contingent pay leads to an improvement or decline in performance. We find that in some cases, and in fact most of the cases we examined, very high incentives result in a decrease in performance. These results provide a counterexample to the assumption that an increase in motivation and effort will always result in improved performance. […] in Dan Ariely, Uri Gneezy, George Loewenstein, and Nina Mazar, “Large Stakes and Big Mistakes“, Review of Economic Studies (2009) 75, 1-19 0034-6527/09. [PDF available here]

Now, these are not stories, these are facts. These are one of the most robust findings in social science,… yet, one of the most ignored [sic]. And they keep coming in. Such as the fallacy of the supply and demand model (March 2008). Anyway, enough good material (a simple paper with profound implications)… for one day. But hey, …Oh, if you are still wondering what other paper inspired the specific drawings at minute 7′:40” and on, in the first video over this post, well, here it is: Kristina Shampan’er and Dan Ariely (2007), “How Small is Zero Price? The True Value of Free Products“, in Marketing Science. Vol. 26, No. 6, 742 – 757. [PDF available here]… Got it ?!

Book – Karl Sigmund, The Calculus of Selfishness, Princeton Series on Theoretical and Computational Biology, Princeton University Press,  ISBN: 978-1-4008-3225-5, 192 pp., 2009.

[…] Cooperation means that a donor pays a cost, c, for a recipient to get a benefit, b. In evolutionary biology, cost and benefit are measured in terms of fitness. While mutation and selection represent the main forces of evolutionary dynamics, cooperation is a fundamental principle that is required for every level of biological organization. Individual cells rely on cooperation among their components. Multicellular organisms exist because of cooperation among their cells. Social insects are masters of cooperation. Most aspects of human society are based on mechanisms that promote cooperation. Whenever evolution constructs something entirely new (such as multicellularity or human language), cooperation is needed. Evolutionary construction is based on cooperation. The five rules for cooperation which we examine in this chapter are: kin selection, direct reciprocity, indirect reciprocity, graph selection, and group selection. Each of these can promote cooperation if specific conditions are fulfilled. […], Martin A. Nowak, Karl Sigmund, How populations cohere: five rules for cooperation, in R. M. May and A. McLean (eds.) Theoretical Ecology: Principles and Applications, Oxford UP, Oxford (2007), 7-16. [PDF]

How does cooperation emerge among selfish individuals? When do people share resources, punish those they consider unfair, and engage in joint enterprises? These questions fascinate philosophers, biologists, and economists alike, for the “invisible hand” that should turn selfish efforts into public benefit is not always at work. The Calculus of Selfishness looks at social dilemmas where cooperative motivations are subverted and self-interest becomes self-defeating. Karl Sigmund, a pioneer in evolutionary game theory, uses simple and well-known game theory models to examine the foundations of collective action and the effects of reciprocity and reputation. Focusing on some of the best-known social and economic experiments, including games such as the Prisoner’s Dilemma, Trust, Ultimatum, Snowdrift, and Public Good, Sigmund explores the conditions leading to cooperative strategies. His approach is based on evolutionary game dynamics, applied to deterministic and probabilistic models of economic interactions. Exploring basic strategic interactions among individuals guided by self-interest and caught in social traps, The Calculus of Selfishness analyses to what extent one key facet of human nature–selfishness–can lead to cooperation. (from Princeton Press). [Karl Sigmund, The Calculus of Selfishness, Princeton Series on Theoretical and Computational Biology, Princeton University Press,  ISBN: 978-1-4008-3225-5, 192 pp., 2009.]

What follows comes partly from chapter 1, available here:

THE SOCIAL ANIMAL: Aristotle classified humans as social animals, along with other species, such as ants and bees. Since then, countless authors have compared cities or states with bee hives and ant hills: for instance, Bernard de Mandeville, who published his The Fable of the Bees more than three hundred years ago. Today, we know that the parallels between human communities and insect states do not reach very far. The amazing degree of cooperation found among social insects is essentially due to the strong family ties within ant hills or bee hives. Humans, by contrast, often collaborate with non-related partners. Cooperation among close relatives is explained by kin selection. Genes for helping offspring are obviously favouring their own transmission. Genes for helping brothers and sisters can also favour their own transmission, not through direct descendants, but indirectly, through the siblings’ descendants: indeed, close relatives are highly likely to also carry these genes. In a bee hive, all workers are sisters and the queen is their mother. It may happen that the queen had several mates, and then the average relatedness is reduced; the theory of kin selection has its share of complex and controversial issues. But family ties go a long way to explain collaboration. The bee-hive can be viewed as a watered-down version of a multicellular organism. All the body cells of such an organism carry the same genes, but the body cells do not reproduce directly, any more than the sterile worker-bees do. The body cells collaborate to transmit copies of their genes through the germ cells – the eggs and sperm of their organism. Viewing human societies as multi-cellular organisms working to one purpose is misleading. Most humans tend to reproduce themselves. Plenty of collaboration takes place between non-relatives. And while we certainly have been selected for living in groups (our ancestors may have done so for thirty million years), our actions are not as coordinated as those of liver cells, nor as hard-wired as those of social insects. Human cooperation is frequently based on individual decisions guided by personal interests. Our communities are no super-organisms. Former Prime Minister Margaret Thatcher pithily claimed that “there is no such thing as society“. This can serve as the rallying cry of methodological individualism – a research program aiming to explain collective phenomena bottom-up, by the interactions of the individuals involved. The mathematical tool for this program is game theory. All “players” have their own aims. The resulting outcome can be vastly different from any of these aims, of course.

THE INVISIBLE HAND: If the end result depends on the decisions of several, possibly many individuals having distinct, possibly opposite interests, then all seems set to produce a cacophony of conflicts. In his Leviathan from 1651, Hobbes claimed that selfish urgings lead to “such a war as is every man against every man“. In the absence of a central authority suppressing these conflicts, human life is “solitary, poor, nasty, brutish, and short“. His French contemporary Pascal held an equally pessimistic view: : “We are born unfair; for everyone inclines towards himself…. The tendency towards oneself is the origin of every disorder in war, polity, economy etc“. Selfishness was depicted as the root of all evil. But one century later, Adam Smith offered another view.An invisible hand harmonizes the selfish efforts of individuals: by striving to maximize their own revenue, they maximize the total good. The selfish person works inadvertently for the public benefit. “By pursuing his own interest he frequently promotes that of the society more effectually than when he really intends to promote it“. Greed promotes behaviour beneficial to others. “It is not from the benevolence of the butcher, the brewer, or the baker, that we expect our dinner, but from their regard to their own self-interest. We address ourselves, not to their humanity but to their self-love, and never talk to them of our own necessities but of their advantages“. A similar view had been expressed, well before Adam Smith, by Voltaire in his Lettres philosophiques: “Assuredly, God could have created beings uniquely interested in the welfare of others. In that case, traders would have been to India by charity, and the mason would saw stones to please his neighbour. But God designed things otherwise….It is through our mutual needs that we are useful to the human species; this is the grounding of every trade; it is the eternal link between men“. Adam Smith (who knew Voltaire well) was not blind to the fact that the invisible hand is not always at work. He merely claimed that it frequently promotes the interest of the society, not that it always does. Today, we know that there are many situations – so-called social dilemmas – where the invisible hand fails to turn self-interest to everyone’s advantage.

Two “The Economist” covers. The first one was manually created and posted by Richard Dawkins himself, … – yes – the evolutionary Biologist. The second one is real as well recent (as of April 4th) – UNDER ATTACK, a 14-page special report on the rise and fall of the wealthy. Do note the Blackberry on top of the dead guy in the front and the skyline of London’s Canary Warf financial district in the background (via HS Dent blog). The Laissez-faire Economy lead to all this (more).

The Economist cover OH FUCK Sept 2008

The Economist April 4 2009 UNDER ATTACK

 

It’s not everyday we see a 40 year ideology collapsing through a dramatic act of contrition. It has happened just a few hours ago (check video above), yesterday in the “financial crisis” congressional hearing in Washington (23. Oct. 2008). Moreover, what seems remarkable, is that the recognition comes from one of his most universally respected founding fathers and defenders.

Alan Greenspan was the longest serving chairman in the Federal Reserve board history (1987-2006), and during this 18-year period of time he were perhaps the leading proponent of de-regulation along with libertarian capitalism, vividly expressed on his “The Age of Turbulence – Adventures in a New World” 2007 book, advocating above all issues, Adam Smith’s “Invisible Hand” that markets can regulate themselves. As it’s known, for his whole adult life, the former Fed chairman has been a devotee of the philosophy of Ayn Rand, who celebrated free-market capitalism as the world’s most moral economic order and advocated a strict laissez-faire approach to government regulation of the marketplace. Ironically, he was a regulator that did not believed in any regulation at all.

It is now quite a remarkable historic moment seeing former Federal Reserve chairman, a lifelong champion of free markets, publicly questioning the philosophy that guided him throughout his years as the world’s most powerful economic policymaker. A philosophy followed and strongly defended by him (along with many others like Margaret Thatcher and Ronald Reagan), at least in the last 40 years, as he himself acknowledged yesterday. Asked by the congressional committee chairman, whether his free-market convictions pushed him to make wrong decisions, especially his failure to rein in unsafe mortgage lending practices, Greenspan replied that indeed he had found a flaw in his ideology, one that left him very distressed. “In other words, you found that your view of the world, your ideology was not right?” he was asked:

Absolutely, precisely“, replied Greenspan. “That’s precisely the reason I was shocked, because I have been going for 40 years or more with very considerable evidence it was working exceptionally well“. Albeit he was surely one of the most influential voices for de-regulation: “There is nothing in Federal regulation that makes it superior to Market regulation”, said Greenspan back in 1994, in one among many of his past radical free-market statements.

I presume we now all wonder, where was Greenspan, when back in 2003 one of the most prestigiously recognized and legendary financial investors such as Warren Buffet, called credit default obligations and derivatives “weapons of financial mass destruction“? Or where was he when Princeton Professor of Economics, Paul Krugman – the recent Nobel laureate – said back in 2006 that “If anyone is to blame on the current situation (sub prime) is Mr Greenspan who poopooed warnings about an emerging bubble and did nothing to crack down on irresponsible lending“. Or what did he, Greenspan itself, said just a few days after ENRON collapsed?

People working in complex systems – and surely financial markets are one of them (yes, for the past 4-5 years including these present turbulent times I am working hard in this area as well) – for long know that any systemic structure could collapse if only positive-feedbacks are injected into them, creating an auto-catalytic snow-ball effect, leading among other things to a power-law like Black Swan. Indeed power-laws are a striking powerful signature. This is specially true when we address self-organization (read it in the present context as self-regulation). In order to be a truly self-regulated system, financial markets should also be embedded with negative-feedbacks as well, as I have addressed in a post about finance and complex systems one month ago. In fact, in order to emerge as a truly self-organized system, self-interest, should constitute just one among many of the ingredients over the entire financial system, and not the isolated unique ingredient. Self-interest promotes amplification and positive feedback, which is – as I recognize – necessary. However, left alone, promotes instead dramatic snowballing drifts over chaotic regimes, due to it’s intrinsic amplification. What’s amazing (at least for me), is that Alan Greenspan just recognized that in a tiny few seconds along his current discourse (check video above), pointing it to the precise key-word:

[…] I made a mistake in presuming that the self-interest of organizations, specifically banks and others, was such that they were best capable of protecting their own shareholders. […] So the problem, here is something which looked to be as a very solid edifice, and indeed a critical pillar to market competition and free-markets, did breakdown and I think that, as I said, shock me. I still do not fully understand why it happened, and obviously to the extend, that I figure out where it happened and why, … aaaaaa, … I will change my views. If the facts change I will change. […]

As a result, “the whole intellectual edifice” of risk management collapsed, Greenspan said. In what regards his unexpected words yesterday at the congressional hearing, at least, I frankly praise him for his huge intellectual courage and present honesty. In the end, it seems that during the past 18 years, former FED chair was nothing else then a simple-man driven by his own blind faith on markets, from which he apparently comes out now. Unfortunately, only now at a very high price. Meanwhile as we know, severe consequences are here to stay, as was already evident when Greenspan addressed the House Financial Services Committee on 2003 (video below). Let’s hope that all these will not be forgotten in 3 decades from now (though, I doubt it – after all, nothing really serious came out from the entitled 3-man dream-team Bush-Sarkozy-Barroso “new global finance order” summit at Camp David last weekend, as expected):

“You have told the American people that you support a trade policy which is selling them out.” – Rep. Bernard Sanders to Federal Reserve Chairman Alan Greenspan on 7/16/03. Rep. Bernard Sanders (Independent-Vermont), now a US Senator, dresses down Federal Reserve Chairman Alan Greenspan in front of the House Financial Services Committee on 7/16/03.

Subprime Banking Mess (via YouTube) – John Bird and John Fortune (the Long Johns) brilliantly, and accurately, describing the mindset of the investment banking community in this satirical interview.

Now, above in the video, do you remember the words: Structured Investment Vehicle (S.I.V. or Conduits)? No? Okay, let’s now pass to a very brief and relatively more technical approach to it (as you will see it, reality transcends fiction) – CNBC via Youtube:

Care for more?

[…] From the ice-age to the dole-age
There is but one concern
I have just discovered: Some girls are bigger than others
Some girls are bigger than others
Some girls mothers are bigger than
Other girls mothers
[…]

The Smiths – “Some Girls Are Bigger Than Others“, (Queen is dead) 1986. Song written by Morrissey and Johnny Marr.

 ________________  §  ________________

NOUN:dole

Key: “S:” = Show Synset (semantic) relations, “W:” = Show Word (lexical) relations / S: (n) dole (a share of money or food or clothing that has been charitably given) / S: (n) dole, pogy, pogey (money received from the state

 ________________  §  ________________

(via William Gibson‘s blog)

SUBJECT: REQUEST FOR URGENT BUSINESS RELATIONSHIP
posted 12:29 PM

DEAR AMERICAN:

I NEED TO ASK YOU TO SUPPORT AN URGENT SECRET BUSINESS RELATIONSHIP WITH A TRANSFER OF FUNDS OF GREAT MAGNITUDE.

I AM MINISTRY OF THE TREASURY OF THE REPUBLIC OF AMERICA. MY COUNTRY HAS HAD CRISIS THAT HAS CAUSED THE NEED FOR LARGE TRANSFER OF FUNDS OF 800 BILLION DOLLARS US. IF YOU WOULD ASSIST ME IN THIS TRANSFER, IT WOULD BE MOST PROFITABLE TO YOU.

I AM WORKING WITH MR. PHIL GRAM, LOBBYIST FOR UBS, WHO WILL BE MY REPLACEMENT AS MINISTRY OF THE TREASURY IN JANUARY. AS A SENATOR, YOU MAY KNOW HIM AS THE LEADER OF THE AMERICAN BANKING DEREGULATION MOVEMENT IN THE 1990S. THIS TRANSACTIN IS 100% SAFE.

THIS IS A MATTER OF GREAT URGENCY. WE NEED A BLANK CHECK. WE NEED THE FUNDS AS QUICKLY AS POSSIBLE. WE CANNOT DIRECTLY TRANSFER THESE FUNDS IN THE NAMES OF OUR CLOSE FRIENDS BECAUSE WE ARE CONSTANTLY UNDER SURVEILLANCE. MY FAMILY LAWYER ADVISED ME THAT I SHOULD LOOK FOR A RELIABLE AND TRUSTWORTHY PERSON WHO WILL ACT AS A NEXT OF KIN SO THE FUNDS CAN BE TRANSFERRED.

PLEASE REPLY WITH ALL OF YOUR BANK ACCOUNT, IRA AND COLLEGE FUND ACCOUNT NUMBERS AND THOSE OF YOUR CHILDREN AND GRANDCHILDREN TO WALLSTREETBAILOUT@TREASURY.GOV SO THAT WE MAY TRANSFER YOUR COMMISSION FOR THIS TRANSACTION. AFTER I RECEIVE THAT INFORMATION, I WILL RESPOND WITH DETAILED INFORMATION ABOUT SAFEGUARDS THAT WILL BE USED TO PROTECT THE FUNDS.

YOURS FAITHFULLY MINISTER OF TREASURY PAULSON

Many man made and naturally occurring phenomena (being inherently complex systems), including city sizes, incomes, word frequencies, internet links, social networks and earthquake magnitudes, are distributed according to a power-law distribution. One under f Zipf’s law follows the same characteristic, or pink noise. Here is a possible long list, collected year after year, since the 1910’s up to now – 2008 (which I vividly recommend). From vacuum tubes to trading activities in world financial markets. Even, we could easily found them on Pollock’s paintings (recently here). Back in 2002, I have addressed some of his painting features (mostly fractal) regarding the theme “Emergent Aesthetics in Autonomous Collective Systems“. Astonishingly, without having a clue what fractal dimension’s would be, Jackson increased his fractal signatures year over year, while getting old. Indeed, “Action painting”, has he call it, mainly using his body motion and a bucket, were largely enough. 

Financial markets are indeed complex systems, even if they are far from being self-regulated. Much after this recent black Monday, I have made here some notes regarding Self-Organization and finance, over two weeks or so. Their basic features – as I see it. However- essentially what brings me here today is-, what happens to their frequency? Are phenomena like the current financial crisis, frequent? Well, much of that depends on our knowledge on power-laws. Good news is that we know how many of them will occur in a very large time window, bad news is that, we don’t know when will they precisely occur. As in Earthquakes (check this out). Does this impel us to do nothing? Not at all. We can’t do anything about earthquakes (at least for now – except prevent them), however we can establish some ground smart rules in order to avoid financial systems to collapse in turmoil (that is, tune them in the precise physical regime). Power-laws are not only our wake-up call, as they are a signature. For good or for worse. It seems that we are all playing across the planet, a reversed El Farol Bar problem. If that’s somehow true we all should ask new questions like: In what frequency should we go to a bar ?! In other words, should we all run to the banks now, asking for our deposits?

Any polynomial relationship that exhibits the property of scale invariance is a Power-Law. Power-law implies that small occurrences are extremely common, whereas large instances are extremely rare (similarly over maps and cities – if you have time, found out the foundation of Berlin city over time). As the large quantity of small dots + low frequency of large dots we may found on Jackson Pollock paintings. The same goes for Black-Swans.

Jackson Pollock in action - As reported somehow recently by Nature magazine (Sept., 13, 2000), research suggests that the abstract works of artists such as Jackson Pollock are esthetically pleasing because they obey fractal rules similar to those found on the natural world. Pollock was known to have swung his paint back and forth like a pendulum, using a can on the end of a string with a hole punched in it. Researchers (Jensen) have found that if a swinging pendulum is hit with a hammer at just the right frequency (slightly less than the natural rhythm of the pendulum), its motion becomes chaotic and the paint traces out very convincing fake Pollocks. However, the artist had no idea of fractals or chaotic motion, while dot distribution over Pollocks paintings follow a power-law.

Jackson Pollock in action - As reported somehow recently by Nature magazine (Sept., 13, 2000), research suggests that the abstract works of artists such as Jackson Pollock are esthetically pleasing because they obey fractal rules similar to those found on the natural world. Pollock was known to have swung his paint back and forth like a pendulum, using a can on the end of a string with a hole punched in it. Researchers (Jensen) have found that if a swinging pendulum is hit with a hammer at just the right frequency (slightly less than the natural rhythm of the pendulum), its motion becomes chaotic and the paint traces out very convincing "fake Pollocks". However, the artist had no idea of fractals or chaotic motion, while dot distribution over Pollock's paintings indeed follow a power-law.

A Black Swan is a highly improbable event that has three characteristics: It is unpredictable, it has incredible impact, and after it happens we invent a reason for it that makes it seem less probable. For those of you that did not have read 2007 Taleb’s book (picture above), wondering what a Black Swan is, or question yourself from where the name arises, just jump for a quick look over here. Nassim started to wrote his book in 2003. Finished it in 2006. So, in what way this “funny” distribution regards financial markets? Well, for many of us now, it his surprising that he have wrote this, back then:

[…] Globalization creates interlocking fragility, while reducing volatility and giving the appearance of stability. In other words it creates devastating Black Swans. We have never lived before under the threat of a global collapse. Financial Institutions have been merging into a smaller number of very large banks. Almost all banks are interrelated. So the financial ecology is swelling into gigantic, incestuous, bureaucratic banks – when one fails, they all fall. The increased concentration among banks seems to have the effect of making financial crises less likely, but when they happen they are more global in scale and hit us very hard. We have moved from a diversified ecology of small banks, with varied lending policies, to a more homogeneous framework of firms that all resemble one another. True, we now have fewer failures, but when they occur ….I shiver at the thought. […]

Were these words a Black Swan within the Black Swan book itself? Rather not. He continues directly to something we now know and face it in precise context. Please note that this was written in the period 2003-2006:

[…] Banks hire dull people and train them to be even more dull. If they look conservative, it’s only because their loans go bust on rare, very rare occasions. But (…) bankers are not conservative at all. They are just phenomenally skilled at self-deception by burying the possibility of a large, devastating loss under the rug. […] The government-sponsored institution Fannie Mae, when I look at its risks, seems to be sitting on a barrel of dynamite, vulnerable to the slightest hiccup. But not to worry: their large staff of scientists deemed these events “unlikely”. […] 

What about the costs, and the memory of them? Yes, indeed memory is important while playing game-theory-like games, as his mainly in our daily reality, but in one-two generations it will be probably lost (I hope not), and once again all will start:

[…]  the real-estate collapse of the early 1990s in which the now defunct savings and loan industry required a taxpayer-funded bailout of more than half a trillion dollars. The Federal Reserve bank protected them at our expense: when “conservative” bankers make profits, they get the benefits; when they are hurt, we pay the costs.

Should we be surprised? In fact, this is not new. Somehow, fallacy goes on (as George Monbiot tackle it with extreme precision over Guardian Journal very recently – Sep. 30). Not only we were not reacting to these power-law consequences, as many of those economic agents playing within the systems core itself, were thinking of something else:

[…] Once again, recall the story of banks hiding explosive risks in their portfolios. It is not a good idea to trust corporations with matters such as rare events because the performance of these executives is not observable on a short-term basis, and they will game the system by showing good performance so they can get their yearly bonus. The Achilles’ heel of capitalism is that if you make corporations compete, it is sometimes the one that is most exposed to the negative Black Swan that will appear to be the most for survival.[…] As if we did not have enough problems, banks are now more vulnerable to the Black Swan and the ludic fallacy than ever before with “scientists” among their staff taking care of exposures. The giant J. P. Morgan put the entire world at risk by introducing in the nineties RiskMetrics, a phony method aiming at managing people’s risks, causing the generalized use of the ludic fallacy, and bringing Dr. Johns into power in place of the skeptical Fat Tonys. (a related method called “Value-at-Risk,” which relies on the quantitative measurement of risk, has been spreading.) […]

Starting with the distribution and frequency of these kind of events (among many others), all of these words were written in the period 2003-2006. Since then, you could follow Taleb’s war on “Value at Risk” over here.  Or here, at Edge.org which I highly recommend.

Meanwhile, apart from what markets are suffering and complex science may enlightened us, life goes on. Not necessarily as we supposed. As we know, reality, many times excels fiction; one single video frame could value one thousand words. Right at your neighborhood. As you may see below, consequences could be much worse than a tornado:

Vodpod videos no longer available.

more about “Foreclosure Alley – SoCal Connected“, posted with vodpod

 

 

Image source: ITGO.COM (large size)

In what concerns Social Psychology, just check this out: Milgram et al.(1) found that if one person stood in a Manhattan street gazing at a sixth floor window, 20% of pedestrians looked up; if five people stood gazing, then 80% of people looked up.

As latest fraud facts told us last week in cascade manner (Freddie Mac, Fannie Mae, Lehman Brothers, AIG), essentially, the current financial crisis results from the fact that in order to be a truly self-organized, self-regulated adaptive evolving system as Adam Smith envisioned (back in 1776 – The Wealth of Nations), financial markets need not only to adopt Positive Feedback as they do (e.g., the one Milgram founded, above), but mainly – though in some proportion – Negative Feedback features as well, that is, some form of a priori outside Regulation – in other words, the context and environment of the entire “game” (check here for some basic features of Self-Organization -(2).  Ill or badly defined environments among complex systems, lead to chaotic or unprecedented biased evolutionary pressures (e.g., many of the entities – read it as some companies -, cheaters playing economic games such as the Iterated Prisonners Dilemma IPD over Bounded Rationality – that should naturally “die”, in fact proliferate), turning to be counterproductive for the whole system. Self-Organization occurs in precise very-subtle-narrow regimes (“at the edge of chaos”Christopher Langton, Santa Fe Institute), not over entire entropic regimes as the one we were facing, neither over the entire spectrum (Order, Semi-Order, Edge of Chaos, Chaos – check Stuart Kaufmann’s I, II, III, IV phases). They occur near them, not in them. In order to do so, among several other things (2), also Negative Feedback is necessary. As we know from complex systems, nature, as well as artificial intelligence, the system becomes too greedy and instable.

For instance, on social insect societies know to be self-organized, Positive Feedback (PF) could be illustrated by pheromone reinforcement on trails, allowing the entire colony to exploit some past and present solutions. Generally, as in the above cases, positive feedback is imposed implicitly on the system and locally by each one of the constituent units, whereas Negative Feedback is imposed explicitly mainly by environmental “pressure” conditions, promoting counter-balanced innovative solutions. Fireflies flashing in synchrony follow the PF rule, “I signal when you signal”, fish traveling in schools abide by the rule, “I go where you go”, and so forth. In Humans, the “infectious” quality of a yawn of laughter is a familiar example of positive feedback of the form, “I do what you do”. Seeing a person yawning, or even just thinking of yawning, can trigger a yawn. There is however one associated risk, generally if Positive Feedback acts alone without the presence of Negative Feedbacks, which per si can play a critical role keeping under control this snowballing effect, providing inhibition to offset the amplification and helping to shape it into a particular pattern (2). Indeed, the amplifying nature of Positive Feedback means that it has the potential to produce destructive explosions or implosions in any process where it plays a role. Thus – several biological studies express it – the behavioral rule may be more complicated than initially suggested, possessing both an autocatalytic as well as an antagonistic aspect (2).

The fundamentalist ultra-liberal strategy of “no regulation at all”, followed in recent years, believing ideologically – like a fatwa – that markets are a truly Darwinian CAS (Complex Adaptive System) where invisible hands operate every day in a perfect situation, lead us to a chaotic situation, where shimmering waves of panic proliferate through the world (check video below), constraining states to intervene in a a posteriori manner (the ongoing Paulson Plan). Though, the ultimate best option was to do it a priori, ceasing nations to sleep much of their time earlier in face of many disastrous – out of control – innovative as well as cannibalistic financial products invented in the last decade (many of them being nothing else than financial pyramid schemes, though sophisticated), without reasoning of possible and profound dramatic social costs. Alternatively, a priori smart intervention seems to be the only resource to avoid the current ongoing privatization of profits, and immoral massive losses nationalization, being payed by tax contributors across USA and Europe. Keeping in reasonable shape the wealthy resource that finance markets really are and could be for all of us: promoting robust and innovative companies.

{ [VIDEO] Shimmering Giant Honeybees from Science News on Vimeo.
For some, Financial Markets in crisis could be seen as shimmering waves across the globe, however they are far from being self-organized as honeybee colonies. The invisible hand metaphor originates with Adam Smith in The Wealth of Nations (1776). Bernard Mandeville made a similar point with his Fable of the Bees (1705), which fancifully describes human society as a wondrously productive bee hive, even though each bee is as selfish as can be (3). – Video and article (see 8). }

Washington is right now asking for help and money to China, as well as indulging many other countries in the world to step in. At the same moment, in UK, in the aftermath of the Northern Rock takeover, some big and many medium companies are now selling themselves for short, in Belgium, FORTIS is on the verge, and in Ireland – once the first example of economic bloom in Europe -, the first technical ressence in many years is now fully recognized. France seems to go next. Partial-nationalizations are now occuring from Iceland to the sunny mediterranean Gibraltar. While, back in the US, a very recent LA Times-Bloomberg poll revealed that 60% of Americans claim for some sort of state intervention. In face of this facts, ultra liberals appeal to two typical arguments: (first) that the current phenomena is inevitable (no comments on my side on that, since 1929 till now nothing of this dimension happened before), and (second) markets evolve, some die and some prosper, forgetting however that markets are far from being perfect, and truly self-organized. The question is not if some die (which they should), the question is why the current system is not being able to self-control the proliferation of cheaters and pyramidal schemes on the entire pool of economic agents, in contrast to what happens in truly evolvable economic agents playing IPD or other economic-like games, showing profound traces of self-organized features. Sadly, among many of these if not all, ultra market liberalism evangelists, self-organization is wrongly recognized as self-interest (check 3). Self-interest taken to this limits, is not only their repeated mantra, used to quote “there ain’t those things as a free lunch” (NFL) over and over again as their blindness. NFL after all, is instead broadly recognized as being connected to robustness in computational search and optimization areas. Unfornately, they will never recognize that even under some complex co-evolutionary domains (nature is full of them; where explicit targets or interests were not embedded on the evolutionary algorithm), indeed free-lunches were found (5).

In fact, in order to emerge as a truly self-organized system, self-interest, should constitute just one among many of the ingredients over the entire financial system, and not the isolated unique ingredient. Self-interest promotes amplification and positive feedback, which is – as I recognize – necessary. However, left alone, promotes instead dramatic snowballing drifts over chaotic regimes, due to it’s intrinsic amplification. It’s necessary to promote negative feedbacks as well. This is recognized for some time in neurosciences, neurocomputation and learning (check LTD – long term synaptic depression) (6,7):

  • Learning by reinforcement good responses (Positive Feedback) is a process that by definition never stops. There is not an explicit rule that ends the reinforcement whenever the goal has been reached. On the other hand, if learning proceeds only by correcting mistakes it implies a process that stops as soon as the goal is achieved. This prevents formation of “deep holes“, i.e. highly stable states from which adaptation to new rules is difficult and slow, requiring, perhaps, a significant amount of random noise.
  • If an adaptive system is placed on a new environment, or otherwise subjected to learning something new, the likelihood of making mistakes is generally larger than the chance to be initially right. Therefore, the opportunity to shape synapses is larger for the adaptive mechanism that only relies on mistakes, leading to faster convergence.

Of course, being arrived here at this turmoil chaotic stage, we are nowadays assisting – ironically – to a dramatization of Bush’s Administration speeches. Bush words “Markets are not working properly” are indeed surprising from what we are used to expect from him, his office, as his known to be quite unusual words within his neo-liberal Haliburton centered – pro oil pro preemptive war – social networks (at VisualComplexity), however, subliminally he’s nothing else then reinforcing McCain’s election over Obama, as if great part of the actual crisis did not derived from the Republican past “I see nothing, I hear nothing and I say nothing” political strategy. Lying saying the truth, again ironically, this is the quickest formula to maintain things as they were before, the entire status quo going on, while markets in despair applaud –awkwardly – state interventions for the first time (or second to be precise – 1929; also check October 1907’s actions under J.P. Morgan). Being a liberal I have always believed that some ground-smart rules are always necessary. Let’s face it: even when we drive our car over a highway.

Take the following example. For some moments image yourself to puzzle out how to create a mathematical-algorithmic model on how a flock of birds fly in collective formation. You could on one hand try to model the dynamics of each part, using differential equations, in order to achieve somehow the global behaviour – however, the phenomena is so complex and intricate that differential equations could not handle it. On the other hand, you could try to observe the phenomena innumerable times while envisioning a set of rules, based on the behaviour of the whole system, however as is typical in Self-Organized complex phenomena’s there is no pre-commitment to any particular representational scheme: the desired behaviour is distributed and roughly specified simultaneously among many parts, and there is minimal specification of the mechanism required to generate that behaviour, i.e. the global behaviour mainly evolves from the many relations of multiple simple behaviours. Parts and wholes behave differently. Relations are the key. Surprisingly, and having self-organization theory in mind, you could envision 3, and just 3 simple generative rules following positive and negative feedback features that are able to precisely model this complex phenomena (check Boids): (one) Separation: steer to avoid crowding local flockmates, (two) Alignment: steer towards the average heading of local flockmates, and (three) Cohesion: steer to move toward the average position of local flockmates. Rather, non-linear phenomena are most appropriately treated by a synthetic approach, where synthesis means “the combining of separate elements or substances to form a coherent whole’. In non-linear systems, the parts must be treated in each other’s presence, rather than independently from one another, because they behave very differently in each other’s presence than we would expect from a study of the parts in isolation (4). In order to form the complex coherent whole, antagonistic measures are needed. Realistic counter-powers on the entire global economic TIC-TAC.

That’s why also, being a liberal, I defend a priori over a posteriori interventions. States, after all, were not created or envisioned to be omnipresent firefighters, specially to those few that under the 80-20 Pareto rule umbrella, profited before, month after month, with the current aftermath ([…] And so, my fellow Americans: ask not what your country can do for you – ask what you can do for your country […], John F. Kennedy). Not only Size is important (1) (critical mass) as well as Time, that is, over when should we lay down initial conditions in order to emerge the complex whole to flourish on the precise and desirable Self-Organized domain. Even better than nothing, as I believe, the current and late a posteriori state intervention will only endure the collective illusion for a while.

Not only have we recognized that markets are not perfect as Smith’s Invisible Hand metaphor seems to be dead wrong (3).  As David Sloan Wilson tackles it:

[..] I hope that our economy recovers, but the time has come to declare its guiding metaphor dead. This is the metaphor of the invisible hand, which makes it seem as if the narrow pursuit of self-interest miraculously results in a well-functioning society. […] The collapse of our economy for lack of regulation was preceded by the collapse of rational choice theory. It became clear that the single minimalistic principle of self-interest could not explain the length and breadth of human behavior. […] Mandeville could not have been more wrong about actual nature of bees. There is a difference between self-organization and self-interest. Beehives and other social insect colonies are indeed self-organized. There is no single bee commanding the troops, certainly not the queen. Each bee plays a limited role in the economy of the hive, just as a single neuron plays a limited role in the economy of the brain. The intelligence of both can be found in the interactions among the parts, which have been shaped by natural selection operating over countless generations. But bee behavior cannot be reduced to a single principle of self-interest, any more than human behavior. There are solid citizens and cheaters even among the bees, and the cheaters are held at bay only by a regulatory system called “policing” by the biologists who study them. […] We can argue at length about smart vs. dumb regulation but the concept of no regulation should be forever laid to rest. […]

Somehow, within the middle of countless wrecks, affecting innumerable millions of people thorough out the planet (even those not playing at the stock-exchange), via energy, tax, food and life cost raisings, we are still assisting at truly interesting phase-transition times. The question is: will we learn from it, or will we maintain the recent blind faith that markets, by themselves, will drive us all – similarly to communism – to the land of milk and honey?

  1. in Milgram, Bickerman and Berkowitz, “Note on the Drawing Power of Crowds of Different Size“, Journal of Personality and Social Psychology, Vol 13(2), Oct 1969, pp. 79-82. Abstract: Reports on the relationship between the size of a stimulus crowd, standing on a busy city street looking up at a building, and the response of passersby. As the size of the stimulus crowd was increased a greater proportion of passersby adopted the behavior of the crowd. Data included 1424 pedestrians. The results suggest a modification of the J. S. Coleman and J. James model of the size of free-forming groups to include a contagion assumption.
  2. in V. Ramos et al., “Social Cognitive Maps, Swarm Collective Perception and Distributed Search on Dynamic Landscapes“, 2007. Abstract: Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) entities interacting locally with their environment cause coherent functional global patterns to emerge. SI provides a basis with wich it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a globalmodel. To tackle the formation of a coherent socialcollective intelligence from individual behaviors, we discuss several concepts related to Self-Organization, Stigmergy and Social Foraging in animals. Then, in a more abstract level we suggest and stress the role played not only by the environmentalmedia as a driving force for societal learning, as well as by positive and negative feedbacks produced by the many interactions among agents. Finally, presenting a simple model based on the above features, we will adressthe collective adaptation of a socialcommunity to a cultural (environmental, contextual) or media informational dynamical landscape, represented here – for the purpose of different experiments – by several three-dimensional mathematical functions that suddenly change over time. Results indicate that the collective intelligence is able to cope and quickly adapt to unforseensituations even when over the same cooperative foraging period, the community is requested to deal with two different and contradictory purposes.
  3. in David Sloan Wilson, “The Invisible Hand is Dead. Long Live (Smart) Regulation“, in Axis of Logic, Sep. 2008.
  4. in V. Ramos, “On the Implicit and on the Artificial – Morphogenesis and Emergent Aesthetics in Autonomous Collective Systems“, in ARCHITOPIA Book, Art, Architecture and Science, INSTITUT D’ART CONTEMPORAIN, J.L. Maubant et al. (Eds.), pp. 25-57, Chapter 2, ISBN 2905985631 – EAN 9782905985637, France, Feb. 2002.
  5. in Wolpert, D.H., and Macready, W.G. (2005) “Coevolutionary free lunches,” IEEE Transactions on Evolutionary Computation, 9(6): 721-735.
  6. in Chialvo, D.R., Bak, P., “Learning from Mistakes“. Neuroscience, Vol. 90 (4), pp. 1137-1148, 1999.
  7. in  Bak, P., Chialvo, D.R., “Adaptive Learning by Extremal Dynamics and Negative Feedback“, Phys. Rev. E., Vol. 63, p. 031912, 2001.
  8. in Susan Gaidos, “Honeybees do the Wave“, in Science News, Web edition, Sep. 2008.

[...] People should learn how to play Lego with their minds. Concepts are building bricks [...] V. Ramos, 2002.

@ViRAms on Twitter

Archives

Blog Stats

  • 246,258 hits