David and Goliath

During several years, Octavio Aburto thought of one photo. Now, he finally got it. The recently published photograph by Aburto, titled “David and Goliath” (it his in fact David Castro, one of his research science colleagues at the center of this stunning image) has been widely shared over the last few weeks. It was taken at Cabo Pulmo National Park (Mexico) and submitted to the National Geographic photo contest 2012. Here, he captures the sheer size of fish aggregations in perspective with a single human surrounded by abundant marine life. On a recent interview, he explains:

[…] … this “David and Goliath” image is speaking to the courtship behavior of one particular species of Jack fish. […] Many people say that a single image is worth a thousand words, but a single image can also represent thousands of data points and countless statistical analyses. One image, or a small series of images can tell a complicated story in a very simple way. […] The picture you see was taken November 1^st, 2012. But this picture has been in my mind for three years — I have been trying to capture this image ever since I saw the behavior of these fish and witnessed the incredible tornado that they form during courtship. So, I guess you could say this image took almost three years. […], in mission-blue.org , Dec. 2012.

Video – Behind the scenes of David and Goliath image. This photo was taken at Cabo Pulmo National Park and submitted to the National Geographic photo contest 2012. You can see more of his images from this place and about Mexican seas on Octavio‘s web link.

Signals and Boundaries

Complex adaptive systems (CAS), including ecosystems, governments, biological cells, and markets, are characterized by intricate hierarchical arrangements of boundaries and signals. In ecosystems, for example, niches act as semi-permeable boundaries, and smells and visual patterns serve as signals; governments have departmental hierarchies with memoranda acting as signals; and so it is with other CAS. Despite a wealth of data and descriptions concerning different CAS, there remain many unanswered questions about “steering” these systems. In Signals and Boundaries, John Holland (Wikipedia entry) argues that understanding the origin of the intricate signal/border hierarchies of these systems is the key to answering such questions. He develops an overarching framework for comparing and steering CAS through the mechanisms that generate their signal/boundary hierarchies. Holland lays out a path for developing the framework that emphasizes agents, niches, theory, and mathematical models. He discusses, among other topics, theory construction; signal-processing agents; networks as representations of signal/boundary interaction; adaptation; recombination and reproduction; the use of tagged urn models (adapted from elementary probability theory) to represent boundary hierarchies; finitely generated systems as a way to tie the models examined into a single framework; the framework itself, illustrated by a simple finitely generated version of the development of a multi-celled organism; and Markov processes.

in, Introduction to John H. Holland, “Signals and Boundaries – Building blocks for Complex Adaptive Systems“, Cambridge, Mass. : ©MIT Press, 2012.

The Notificator (London, 1935). First Twitter?

Fig. – For a small sum Londoners may leave messages for friends in public spaces. When writing on “notificator” messages moves up behind window, remaining in view for two hours.  Known as the “notificator,” the new machine was installed in streets, stores, railroad stations or other public places where individuals may leave messages for friends. Appeared in the American Modern Mechanix magazine (August, 1935) (via Modern Mechanix blog) + Maikelnai’s blog).

World’s first Twitter? Hell no! First World Twitter is kind of old, … it were Public Bathrooms !! As well as Hobo signs.

408 seconds of positive feedback

Video – Merci! (referred also as Bodhisattva in metro), short film by Belgian director Christine Rabette awarded in 2003 with a Golden Wave for best Short Film (Court-Métrage), now climbing to more than a half-million views on YouTube. Along with yawning and the flu, few things are as contagious and viral as laughter. After all, we are humans not androids, for god’s sake!

[…] In contrast to negative feedback, positive feedback (f+) generally promotes changes in the system (the majority of SO systems use them). The explosive growth of the human population provides a familiar example of the effect of positive feedback. The snowballing autocatalytic effect of f+ takes an initial change in a system (due to amplification of fluctuations; a minimal and natural local cluster of objects could be a starting point) and reinforces that change in the same direction as the initial deviation. Self-enhancement, amplification, facilitation, and autocatalysis are all terms used to describe positive feedback [9]. Another example could be provided by the clustering or aggregation of individuals. Many birds, such as seagulls nest in large colonies. Group nesting evidently provides individuals with certain benefits, such as better detection of predators or greater ease in finding food. The mechanism in this case is imitation2: birds preparing to nest are attracted to sites where other birds are already nesting, while the behavioral rule could be synthesized as “I nest close where you nest”. The key point is that aggregation of nesting birds at a particular site is not purely a consequence of each bird being attracted to the site per se. Rather, the aggregation evidently arises primarily because each bird is attracted to others (check for further references on [7,9]). On social insect societies, f+ could be illustrated by the 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. Fireflies flashing in synchrony [49] follow the 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 yawning3, or even just thinking of yawning, can trigger a yawn [9]. There is however one associated risk, generally if f+ 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. Indeed, the amplifying nature of  f+ means that it has the potential to produce destructive explosions or implosions in any process where it plays a role. Thus the behavioral rule may be more complicated than initially suggested, possessing both an autocatalytic as well as an antagonistic aspect. In the case of fish [9], the minimal behavioral rule could be “I nest where others nest, unless the area is overcrowded”. In this case both the positive and negative feedback may be coded into the behavioral rules of the fish. Finally, in other cases one finds that the inhibition arises automatically, often simply from physical constraints. […], in, Social Cognitive Maps, Swarm Collective Perception and Distributed Search on Dynamic Landscapes.

Black Swan – Financial Markets (part II)

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 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

 

 

On Financial Markets

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.