Sir Karl Popper

[...] … I do not really believe that we shall succeed in creating life artificially; but after having reached the moon and landed a spaceship or two on Mars, I realize that this disbelief of mine means very little. But computers are totally different from brains, whose function is not primarily to compute but to guide and balance an organism and help it to stay alive. It is for this reason that the first step of nature toward an intelligent mind was the creation of life, and I think that should we artificially create an intelligent mind, we would have to follow the same path. [...], Karl Popper – Popper, K. R. and Eccles, J. C. (1983), The Self and its Brain: An Argument for Interactionism, Routledge & Kegan Paul plc, London.

Strange Culture – A true story

Excerpt – “Dartmouth and the Liberating Arts“: [...] Crucially, Deming (Edward Deming) then argued that this indispensable foundation of trust and shared commitment must be allied to a rigorous understanding of how complex systems work to produce desired results. (…) two sides of the educational mission set forth by my predecessors, a mission that in this historical moment is more vital than ever: on the one hand, the passionate commitment to making the world a better place; on the other, the practical understanding of complex systems required to deliver solutions on a global scale. Passion and practicality: Either without the other will be inadequate to tackle the challenges we face today. [...] Jim Yong Kim, “Passion and Practicality: Dartmouth and the Liberating Arts“, new President at Dartmouth Univ.  at his inaugural address, Dartmouth Speeches, Sept. 2009.

Allow me to give you a starter. Albeit this is only the beginning. There is much more at stake over this 1 hour and 15 minutes movie drama documentary: [...] Did you read that the Japanese will be watching what’s going to be happening with American teenagers over the next 20 years, … and then they are going to decide to introduce GMO’s (Genetically Modified Organisms) into their food? [...]

Alternately teasing and terrifying, STRANGE CULTURE molds one man’s tragedy into an engrossing narrative. In 2004, Steve Kurtz (Thomas Jay Ryan), an associate professor of art at the State University of New York, Buffalo, was preparing an exhibition on genetically modified food for the Massachusetts Museum of Contemporary Art when his wife, Hope (Tilda Swinton), died in her sleep of heart failure. But when paramedics noticed petri dishes and other scientific paraphernalia in the home, they alerted the F.B.I.; within hours Mr. Kurtz found himself suspected of bioterrorism, his home quarantined and his wife’s body removed for autopsy. Filmmaker Lynn Hershman-Leeson bends the nonfiction form to her own unconventional will. The result is a fascinating collage of re-enactments, news clips and interviews, illuminating not only the implications of corporate meddling in the food chain but the ease with which innocent civilian behavior can become a suspicious act. [Text from the YouTube movie synopsis here]

Kids

Doomsday Machines and Bluff

On Bilateral Monopolies: [...] Mary has the world’s only apple, worth fifty cents to her. John is the world’s only customer for the apple, worth a dollar to him. Mary has a monopoly on selling apples, John has a monopoly (technically, a monopsony, a buying monopoly) on buying apples. Economists describe such a situation as bilateral monopoly. What happens? Mary announces that her price is ninety cents, and if John will not pay it, she will eat the apple herself. If John believes her, he pays. Ninety cents for an apple he values at a dollar is not much of a deal but better than no apple. If, however, John announces that his maximum price is sixty cents and Mary believes him, the same logic holds. Mary accepts his price, and he gets most of the benefit from the trade. This is not a fixed-sum game. If John buys the apple from Mary, the sum of their gains is fifty cents, with the division determined by the price. If they fail to reach an agreement, the summed gain is zero. Each is using the threat of the zero outcome to try to force a fifty cent outcome as favorable to himself as possible. How successful each is depends in part on how convincingly he can commit himself, how well he can persuade the other that if he doesn’t get his way the deal will fall through. Every parent is familiar with a different example of the same game. A small child wants to get her way and will throw a tantrum if she doesn’t. The tantrum itself does her no good, since if she throws it you will refuse to do what she wants and send her to bed without dessert. But since the tantrum imposes substantial costs on you as well as on her, especially if it happens in the middle of your dinner party, it may be a sufficiently effective threat to get her at least part of what she wants. Prospective parents resolve never to give in to such threats and think they will succeed. They are wrong. You may have thought out the logic of bilateral monopoly better than your child, but she has hundreds of millions of years of evolution on her side, during which offspring who succeeded in making parents do what they want, and thus getting a larger share of parental resources devoted to them, were more likely to survive to pass on their genes to the next generation of offspring. Her commitment strategy is hardwired into her; if you call her bluff, you will frequently find that it is not a bluff. If you win more than half the games and only rarely end up with a bargaining breakdown and a tantrum, consider yourself lucky.

Herman Kahn, a writer who specialized in thinking and writing about unfashionable topics such as thermonuclear war, came up with yet another variant of the game: the Doomsday Machine. The idea was for the United States to bury lots of very dirty thermonuclear weapons under the Rocky Mountains, enough so that if they went off, their fallout would kill everyone on earth. The bombs would be attached to a fancy Geiger counter rigged to set them off if it sensed the fallout from a Russian nuclear attack. Once the Russians know we have a Doomsday Machine we are safe from attack and can safely scrap the rest of our nuclear arsenal. The idea provided the central plot device for the movie Doctor Strangelove. The Russians build a Doomsday Machine but imprudently postpone the announcement they are waiting for the premier’s birthday until just after an American Air Force officer has launched a unilateral nuclear attack on his own initiative. The mad scientist villain was presumably intended as a parody of Kahn. Kahn described a Doomsday Machine not because he thought we should build one but because he thought we already had. So had the Russians. Our nuclear arsenal and theirs were Doomsday Machines with human triggers. Once the Russians have attacked, retaliating does us no good just as, once you have finally told your daughter that she is going to bed, throwing a tantrum does her no good. But our military, knowing that the enemy has just killed most of their friends and relations, will retaliate anyway, and the knowledge that they will retaliate is a good reason for the Russians not to attack, just as the knowledge that your daughter will throw a tantrum is a good reason to let her stay up until the party is over. Fortunately, the real-world Doomsday Machines worked, with the result that neither was ever used.

For a final example, consider someone who is big, strong, and likes to get his own way. He adopts a policy of beating up anyone who does things he doesn’t like, such as paying attention to a girl he is dating or expressing insufficient deference to his views on baseball. He commits himself to that policy by persuading himself that only sissies let themselves get pushed around and that not doing what he wants counts as pushing him around. Beating someone up is costly; he might get hurt and he might end up in jail. But as long as everyone knows he is committed to that strategy, other people don’t cross him and he doesn’t have to beat them up. Think of the bully as a Doomsday Machine on an individual level. His strategy works as long as only one person is playing it. One day he sits down at a bar and starts discussing baseball with a stranger also big, strong, and committed to the same strategy. The stranger fails to show adequate deference to his opinions. When it is over, one of the two is lying dead on the floor, and the other is standing there with a broken beer bottle in his hand and a dazed expression on his face, wondering what happens next. The Doomsday Machine just went off. With only one bully the strategy is profitable: Other people do what you want and you never have to carry through on your commitment. With lots of bullies it is unprofitable: You frequently get into fights and soon end up either dead or in jail. As long as the number of bullies is low enough so that the gain of usually getting what you want is larger than the cost of occasionally having to pay for it, the strategy is profitable and the number of people adopting it increases. Equilibrium is reached when gain and loss just balance, making each of the alternative strategies, bully or pushover, equally attractive. The analysis becomes more complicated if we add additional strategies, but the logic of the situation remains the same.

This particular example of bilateral monopoly is relevant to one of the central disputes over criminal law in general and the death penalty in particular: Do penalties deter? One reason to think they might not is that the sort of crime I have just described, a barroom brawl ending in a killing more generally, a crime of passion seems to be an irrational act, one the perpetrator regrets as soon as it happens. How then can it be deterred by punishment? The economist’s answer is that the brawl was not chosen rationally but the strategy that led to it was. The higher the penalty for such acts, the less profitable the bully strategy. The result will be fewer bullies, fewer barroom brawls, and fewer “irrational” killings. How much deterrence that implies is an empirical question, but thinking through the logic of bilateral monopoly shows us why crimes of passion are not necessarily undeterrable. [...]

in Chapter 8, David D. Friedman, “Law’s Order: What Economics Has to Do With Law and Why it Matters“, Princeton University Press, Princeton, New Jersey, 2000.

Note – Further reading should include David D. Friedman’s “Price Theory and Hidden Order“. Also, a more extensive treatment could be found on “Game Theory and the Law“, by Douglas G. Baird, Robert H. Gertner and Randal C. Picker, Cambridge, Mass: Harvard University Press, 1994.

No words necessary (II); The whole is greater than the sum of its parts

The Austrian composer Peter Ablinger transferred the frequency spectrum of one child’s voice to his computer controlled mechanical piano – A “speaking piano” reciting the Proclamation of the European Environmental Criminal Court at World Venice Forum 2009. It’s all in German, but what the piano says is all English, and it’s really neat to watch. All of a sudden the words of the Declaration become understandable to a European Environmental Criminal Court. Wien Modern was one out of ten cultural institutions asked for an artistic contribution to the event in Palazzo Ducale in Venice. The ambitious goal was to make this message audible with musical means, without falling back to a simple setting. [link]

[...] We hear sounds that obviously aren’t normal Music, but neither they are language, and one could say that sometimes, a bridging happens. Personally, I think you can understand individual words even without knowing the text, and the Eureka moment happens when you see the text, and suddenly, the language is there. [...]

(more on Perception, Gestalt, Art and Music, here and here)

The Chaotic solution – A network nurtures small failures in order that large failures don’t happen as often

“[…] QUESTION_HUMAN > If Control’s control is absolute, why does Control need to control?
ANSWER_CONTROL > Control…, needs time.
QUESTION_HUMAN > Is Control controlled by his need to control ?
ANSWER_CONTROL > Yes.
QUESTION_HUMAN > Why is Control need Humans, has you call them ?
ANSWER_CONTROL > Wait ! Wait…! Time are lending me…; Death needs time like a Junkie… needs Junk.
QUESTION_HUMAN > And what does Death need time for ?
ANSWER_CONTROL > The answer is so simple ! Death needs time for what it kills to grow in ! […]”, in Dead City Radio, William S. Burroughs / John Cale , 1990.

After the Portuguese President invented a new problem for our country (has we had not enough), here’s a brilliant and genius blog post counter response:

[...] Now only an expert can deal with the problem, Because half the problem is seeing the problem, And only an expert can deal with the problem, Only an expert can deal with the problem [...] So if there’s no expert dealing with the problem, It’s really actually twice the problem, Cause only an expert can deal with the problem, Only an expert can deal with the problem [...] Now in America we like solutions, We like solutions to problems, And there’s so many companies that offer solutions, Companies with names like Pet Solution, The Hair Solution. The Debt Solution. The World Solution. The Sushi Solution. Companies with experts ready to solve the problems. Cause only an expert can see there’s a problem. And only an expert can deal with the problem [...] Laurie Anderson, ‘Only an Expert’ lyrics.

Out of Control – The New Biology of Machines, Social Systems, and the Economic World, 1994’s Book (from Kevin Kelly web site) is a summary of what we know about self-sustaining systems, both living ones such as a tropical wetland, or an artificial one, such as a computer simulation of our planet. The last chapter of the book, “The Nine Laws of God,” is a distillation of the nine common principles that all life-like systems share. The major themes of the book are:

1) As we make our machines and institutions more complex, we have to make them more biological in order to manage them. 2) The most potent force in technology will be artificial evolution. We are already evolving software and drugs instead of engineering them. 3) Organic life is the ultimate technology, and all technology will improve towards biology. 4) The main thing computers are good for is creating little worlds so that we can try out the Great Questions. Online communities let us ask the question “what is a democracy; what do you need for it?” by trying to wire a democracy up, and re-wire it if it doesn’t work. Virtual reality lets us ask “what is reality?” by trying to synthesize it. And computers give us room to ask “what is life?” by providing a universe in which to create computer viruses and artificial creatures of increasing complexity. Philosophers sitting in academies used to ask the Great Questions; now they are asked by experimentalists creating worlds. 5) As we shape technology, it shapes us. We are connecting everything to everything, and so our entire culture is migrating to a “network culture” and a new network economics. 6) In order to harvest the power of organic machines, we have to instill in them guidelines and self-governance, and relinquish some of our total control.

The world of our own making has become so complicated that we must turn to the world of the born to understand how to manage it.

No words necessary

Video – ABB FlexPicker Robots (Source: http://www.botjunkie.com/ + http://www.abb.com/)

As well as, something at the lower pre-processing engineering level involving also Pattern Recognition, Image Analysis and Classification.  Not for  brownies, cookies or sausages. Since this is summer time, it relates with clams and bivalve in general. From the video, everything appears to be rather easy. But, they are not.

On Travel again!

Video – From November 9th 2007 till November 13th 2008, Christoph Rehage walked 4646 km, through China on his way back to Germany – one entire year on foot (http://www.thelongestway.com). This is much probably the best amateur travel short video I have ever seen on my life. Remembering me to the bones of some of my own travels. Travels anyway, are like women. You should keep them on your heart, not on your mouth.

Complex Systems and Alice in Wonderland

Video – Awesome choice by Tim Burton. It fits him like a glove. Here is the official Tim Burton’s Alice in Wonderland teaser trailer (just uploaded yesterday). Alice in Wonderland is directed by visionary director Tim Burton, of everything from Pee-Wee’s Big Adventure to Beetlejuice to Batman to Edward Scissor hands to Mars Attacks to Sleepy Hollow to Charlie and the Chocolate Factory to Sweeney Todd most recently. This is based on Lewis Carroll’s beloved series of books that were first published in 1865. Disney is bringing Tim Burton’s Alice in Wonderland to both digital 3D and 2D theaters everywhere on March 5th, 2010 early next year (more). Finally, just one personal thought. Soon, Tim Burton’s will stand for cinema, as what Jules Verne represented in literature.

In 1973, under several ongoing works on Co-Evolution and Evolutionary theory, L. van Alen proposed a new hypothesis: the Red Queen effect [1]. According to him, several different species will migth propably undergo and submit themselves to a continuous re-adapation [2,3], being it genetic or synaptic, only to end themselves at the point they started. A kind of arms races between species [4], potentially leading to specialization, as well as evolutionary Punctuated equilibria [5,6].

Van Alen chose the name “Red Queen” in allusion to the romance “Alice in Wonderland”, from Charles Lutwidge Dodgson (better known as Lewis Carroll) published in 1865. Over this country (Wonderland) it was usual to run as quick as you could, just to end yourself at the same place. The dialogs between Alice and the Red Queen are sintomatic:

[...] ‘Now! Now!’ cried the Queen. ‘Faster! Faster!’ And they went so fast that at last they seemed to skim through the air, hardly touching the ground with their feet, till suddenly, just as Alice was getting quite exhausted, they stopped, and she found herself sitting on the ground, breathless and giddy. The Queen propped her up against a tree, and said kindly, ‘You may rest a little, now. Alice looked round her in great surprise. ‘Why, I do believe we’ve been under this tree the whole time! Everything’s just as it was!’ ‘Of course it is,’ said the Queen. ‘What would you have it?’. ‘Well, in our country, said Alice, still panting a little, ‘you’d generally get to somewhere else – if you ran very fast for a long time as we’ve been doing.’ ‘A slow sort of country!’ said the Queen. ‘Now, here, I see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!‘ [...]

Meanwhile, since 2007 (even much earlier!) I have taken Alice into my own arms. In fact, she is not heavy at all. If you feel you should keep running, some should, have a read on “Co-Cognition, Neural Ensembles and Self-Organization“, extended abstract for a seminar talk at ISR – Institute for Systems and Robotics, Technical Univ. of Lisbon (IST), May 31, 2007. Written at Granada University, Spain, 29 May 2007.

[1] van Alen, L. (1973), “A New Evolutionary Law“, Evolutionary Theory, 1, pp. 1-30.
[2] Cliff D., Miller G.F. (1995), “Tracking the Red Queen: Measurements of Adaptive Progress in Co-Evolutionary Simulations“, in F. Moran, A. Moreno, J.J. Merelo and P. Cachon (editors) Advances in Artificial Life: Proceedings of the Third European Conference on Artificial Life (ECAL95). Lecture Notes in Artificial Intelligence 929, Springer- Verlag, pp.200-218.
[3] Cliff D., Miller G.F. (1996), “Co-Evolution of Pursuit and Evasion II: Simulation Methods and Results“. In P. Maes et al. (Eds.), From Animals to Animats IV, Procs. of the Fourth Int. Conf. on Simulation of Adaptive Behaviour, MIT Press, pp. 506-515.
[4] Dawkins R., Krebs J.R. (1979), “Arms Races between and within Species“. In Procs. of the Royal Society of London: Biological Sciences, nº. 205, pp. 489-511.
[5] Eldredge, N., Gould, S. J., “Punctuated equilibria: an alternative to phyletic gradualism“. In: Models In Paleobiology (Ed. by T. J. M. Schopf), 1972.
[6] Gould, S. J., & Eldredge, N., “Punctuated equilibria: the tempo and mode of evolution reconsidered“. Paleobiology, 3, 115-151, 1977.

One giant leap for Mankind

I remember my father awakening me around 10 PM (GMT) in order to see it along with all the family, over a old black and white TV monitor. I was 2 ½ years old. In the subsequent days, my dad’s only efforts, focus and struggle seem to be grabbing a rare copy of a historical Paris-Match solely dedicated to the mission. At that time, it was the only available international edition in the South of Portugal, and the few copies available disappeared in a blink of an eye, like pop-corns. He died one year later, but I still have it today by my side (check cover below).

Figure – Traverse map of Eagle’s Lunar Module (LM) landing site at Tranquility base (Apollo 11 mission, 20 July 1969). Taken from “Apollo 11 Preliminary Science Report“, NASA SP-214, page 52, fig. 3.16. The report is now freely available here (PDF format).

Although he released an album and numerous singles earlier, David Bowie first caught the eye and ear of the public in the autumn of 1969, when his space-age mini-melodrama “Space Oddity” reached the top five of the UK singles chart. It was also with this piece that Bowie appeared for the first time on TV in 1970 (original video). After a three-year period of experimentation he re-emerged in 1972 during the glam rock era as a flamboyant, androgynous alter ego Ziggy Stardust, spearheaded by the hit single “Starman” and the album The Rise and Fall of Ziggy Stardust and the Spiders from Mars. The relatively short-lived Ziggy persona epitomised a career often marked by musical innovation, reinvention and striking visual presentation (from youTube).

Figure – Paris Match nº 1058, Spécial Lune. LUNE Número Historique cover (16 August 1969).

Self-Organizing the Abstract

Figure – My first Swarm Painting SP0016 (Jan. 2002). This was done attaching the following algorithm into a robotic drawing arm. In order to do it however, pheromone distribution by the overall ant colony were carefully coded into different kinds of colors and several robotic pencils (check “The MC2 Project [Machines of Collective Conscience]“, 2001, and “On the Implicit and on the Artificial“, 2002). On the same year when the computational model appeared (2000) the concept was already extended into photography (check original paper) – using the pheromone distribution as photograms (“Einstein to Map” in the original article along with works like “Kafka to Red Ants” as well as subsequent newspaper articles). Meanwhile, in 2003, I was invited to give an invited talk over these at the 1st Art & Science Symposium in Bilbao (below). Even if I was already aware of Jeffrey Ventrella outstanding work as well as Ezequiel Di Paolo, it was there where we first met physically.

[] Vitorino Ramos, Self-Organizing the Abstract: Canvas as a Swarm Habitat for Collective Memory, Perception and Cooperative Distributed Creativity, in 1st Art & Science Symposium – Models to Know Reality, J. Rekalde, R. Ibáñez and Á. Simó (Eds.), pp. 59, Facultad de Bellas Artes EHU/UPV, Universidad del País Vasco, 11-12 Dec., Bilbao, Spain, 2003.

Many animals can produce very complex intricate architectures that fulfil numerous functional and adaptive requirements (protection from predators, thermal regulation, substrate of social life and reproductive activities, etc). Among them, social insects are capable of generating amazingly complex functional patterns in space and time, although they have limited individual abilities and their behaviour exhibits some degree of randomness. Among all activities by social insects, nest building, cemetery organization and collective sorting, is undoubtedly the most spectacular, as it demonstrates the greatest difference between individual and collective levels. Trying to answer how insects in a colony coordinate their behaviour in order to build these highly complex architectures, scientists assumed a first hypothesis, anthropomorphism, i.e., individual insects were assumed to possess a representation of the global structure to be produced and to make decisions on the basis of that representation. Nest complexity would then result from the complexity of the insect’s behaviour. Insect societies, however, are organized in a way that departs radically from the anthropomorphic model in which there is a direct causal relationship between nest complexity and behavioural complexity. Recent works suggests that a social insect colony is a decentralized system composed of cooperative, autonomous units that are distributed in the environment, exhibit simple probabilistic stimulus-response behaviour, and have only access to local information. According to these studies at least two low-level mechanisms play a role in the building activities of social insects: Self-organization and discrete Stigmergy, being the latter a kind of indirect and environmental synergy. Based on past and present stigmergic models, and on the underlying scientific research on Artificial Ant Systems and Swarm Intelligence, while being systems capable of emerging a form of collective intelligence, perception and Artificial Life, done by Vitorino Ramos, and on further experiences in collaboration with the plastic artist Leonel Moura, we will show results facing the possibility of considering as “art”, as well, the resulting visual expression of these systems. Past experiences under the designation of “Swarm Paintings” conducted in 2001, not only confirmed the possibility of realizing an artificial art (thus non-human), as introduced into the process the questioning of creative migration, specifically from the computer monitors to the canvas via a robotic harm. In more recent self-organized based research we seek to develop and profound the initial ideas by using a swarm of autonomous robots (ARTsBOT project 2002-03), that “live” avoiding the purpose of being merely a simple perpetrator of order streams coming from an external computer, but instead, that actually co-evolve within the canvas space, acting (that is, laying ink) according to simple inner threshold stimulus response functions, reacting simultaneously to the chromatic stimulus present in the canvas environment done by the passage of their team-mates, as well as by the distributed feedback, affecting their future collective behaviour. In parallel, and in what respects to certain types of collective systems, we seek to confirm, in a physically embedded way, that the emergence of order (even as a concept) seems to be found at a lower level of complexity, based on simple and basic interchange of information, and on the local dynamic of parts, who, by self-organizing mechanisms tend to form an lived whole, innovative and adapting, allowing for emergent open-ended creative and distributed production.

On Life, aLife and Death

Fig. – Knight, Death and the Devil (1513). This is one of three metal engravings by Albrecht Dürer in a series called Meisterstiche (since I have started this blog, I have also chosen a woodcut engraving done by Dürer, – his Rhinoceros – for several reasons, one being that it appeared in Europe for the fisrt time trough Lisbon in 1515). The others are Melancholia I and Saint Jerome in His Study. The engraving is dated 1513, two hundred years after the dissolution of the Knights Templar in 1313. We see a skull in the bottom left corner; the night in full armour (shining armor?) carries a lance; behing him is a pig-snouted horned devil and he is passing Death on his pale horse, who is carrying an hourglass. Under the knight’s horse runs a long-haired retriever, a hunting dog. Dürer called this picture Reuter, which is, Rider. (source).

“Every evil leaves a sorrow in the memory, until the supreme evil, death,
wipes out all memories together with all life“. Leonardo da Vinci.

Carlos Gershenson (Complexes blog), some days ago just uploaded a short (5 pp.) philosophical essay about life, death and artificial life (*) (aLife), which I vividly recommend. He starts his “What Does Artificial Life Tell Us About Death?” with this precise Leonardo’s quote (above). Among other passages it’s interesting to see how different notions of death are deduced from a limited set of different notions of life (in many situations, opposing terms could be used to define each other). Carlos points us out to six currents, or lines of thought:

• If we consider life as self-production (Varela et al., 1974; Maturana and Varela, 1980, 1987; Luisi, 1998), then death will the the loss of that self-production ability.
• If we consider life as what is common to all living beings (De Duve, 2003, p. 8), then death implies the termination of that commonality, distinguishing it from other living beings.
• If we consider life as computation (Hopfield, 1994), then death will be the end (halting?) of that computing process.
• If we consider life as supple adaptation (Bedau, 1998), death implies the loss of that adaptation.
• If we consider life as a self-reproducing system capable of at least one thermodynamic work cycle (Kauffman, 2000, p. 4), death will occur when the system will be unable to perform thermodynamic work.
• If we consider life as information (a system) that produces more of its own information than that produced by its environment (Gershenson, 2007), then death will occur when the environment will produce more information than that produced by the system.

I was aware of Kauffman’s “blender thought experiment”, however Gershenson adds much more into it. A variation. He goes on like this. Nice reading:

[...] Focussing on our understanding of death, this will depend necessarily on our understanding of life, and vice versa. Throughout history there have been several explanations to both life and death, and it seems unfeasible that a consensus will be reached. Thus, we are faced with multiple notions of life, which imply different notions of death. However, generally speaking, if we describe life as a process, death can be understood as the irreversible termination of that process. The general notion of life as a process or organization (Langton, 1989; Sterelny and Griffiths, 1999; Korzeniewski, 2001) has expelled vitalism from scientific worldviews. Moreover, there are advantages in describing living systems from a functional perspective, e.g. it makes the notion of life independent of its implementation. This is crucial for artificial life. Also, we know that there is a constant flow of matter and energy in living systems, i.e. their physical components can change while the identity of the organism is preserved. In this respect, one can make a variation of Kauffman’s “blender thought experiment” (Kauffman, 2000): if you put a macroscopic living system in a blender and press “on”, after some seconds you will have the same molecules that the living system had. However, the organization of the living system is destroyed in the blending. Thus, life is an organizational aspect of living systems, not so much a physical aspect. Death occurs when this organization is lost. [...]

(*) even if, I do not recommend this Wikipedia entry. Extremely poor.

Can you trust your own eyes, or hears?

Fig. – Illusion created by Prof. Akiyoshi Kitaoka (Dep. of Psychology, Ritsumeikan Univ., Kyoto, Japan). If you don’t see any illusion at all, don’t worry. That’s exactly why this optical illusion is so great. The illusion is not there, or is it?! Meanwhile over his page, Akiyoshi warns: This page contains some works of “anomalous motion illusion”, which might make sensitive observers dizzy or sick. Should you feel dizzy, you had better leave this page immediately (more).

Where’s the illusion, right? Well,… what if I just tell you that no blue at all is used over this picture! No matter how strongly you want to believe you are seeing blue and green spirals here, there is no blue color in this image. There is only green, red and orange. What you think is blue is actually green. Don’t worry, … you are not daltonic. I mean, I’m a little bit but, you could check this out through Paint Shop Pro or Photoshop, if you need an affirmation. Indeed, these are just “Vain speculation un­deceived by the senses” (1670’s Scilla’s treatise) .

In fact, Relations here, between different colors (green, red and orange), are more important than each color by itself. Relations plus context are the key (more here over Generative Art, and here over Swarm Intelligence based Pattern Recognition). Through these relations, much probably using Gestalt’s principles (the German word Gestalt could be translated into “configuration or pattern”), here Akiyoshi manages to emerge us the blue color over our perception. This does not cheat a computer of course, however could cheat our own eyes. In other areas the opposite could also be found. For instance, Humans can easily recognize a car over background trees (segment it, in just tiny lapses of a second), while this natural task could be extremely painful for computers over some cases (here is one example).

Born in Prague (inspired by 1890’s works of Christian von Ehrenfels, Austrian philosopher), then later absorbed by a great and tremendous intellectual period occurred from Germany back to Austria (Bauhaus), the Gestalt Laws of Organization have guided the study of how people perceive visual components as organized patterns or wholes, instead of many different parts. I would say that most certainly some Wertheimer’s gestaltic principles were used in here: Figure and Ground, Similarity, Proximity or Contiguity, Continuity, Closure, Area, and Symmetry (check Gestalt Theory of Visual Perception). We could see this happening also in other areas, … in Music for instance:

[...] Gestalt theory first arose in 1890 as a reaction to the prevalent psychological theory of the time – atomism. Atomism examined parts of things with the idea that these parts could then be put back together to make wholes. Atomists believed the nature of things to be absolute and not dependent on context. Gestalt theorists, on the other hand, were intrigued by the way our mind perceives wholes out of incomplete elements [1, 2]. “To the Gestaltists, things are affected by where they are and by what surrounds them…so that things are better described as “more than the sum of their parts.” [1, p. 49]. Gestaltists believed that context was very important in perception. An essay by Christian von Ehrenfels discussed this belief using a musical example. Take a 12 note melody. Play it in one key, say the key of C. Now change to another key, say the key of A flat. There might not be any notes the same in the two songs, yet a person listening to it knows that it is the same tune. It is the relationships between the notes that give us the tune, the whole, not which notes make up the tune. [...], from “Gestalt Principles of Perception“, Bonnie Skaalid, Univ. of Saskatchewan, Canada, 1999.

Care for an contemporary example? Well, … the first thing that comes to my mind is DUB music genre. In fact, I do have several albums from different musicians over my house. Dub music evolved in Jamaica (1968) from early rastafarian instrumental reggae music and versions that incorporated fairly primitive reverbs and echo sound effects, being found by accident (engineer Byron Smith left the vocal track out by accident). Over decades, it inspired immense groups of musicians from well-known bands such as The Police, The Clash, UB40 up to reputed musicians such as Bill Laswell. Of course !, it was not far from what John Cage have made for the solo piano Music of Changes, to determine which notes should be used and when they should sound. In the fifty’s, Cage start it to use the mechanism of the I Ching (Chinese “Book of Changes”) in the composition of his music in order to provide a framework for his uses of chance.

Other most recent bands include, Leftfield, Massive Attack, Bauhaus, The Beastie Boys, Asian Dub Foundation, Underworld, Thievery Corporation, Gorillaz, Kruder & Dorfmeister, and DJ Spooky. But what is then so special about Dub? Well, one of this genre’s most striking features is the fact that some if not all musical sentences are incomplete. Those special sentences (Gestaltic, let me add), are normally followed by a pause. The most amazing thing however, is that us, Humans could perceive the entire sentence being formed on the back of our minds! So the music is not there, and at the same time, we are listening to two adjacent simultaneous melodies, as we were a composer. By just using relations among a few notes, we soon start to emerge a perception for the whole sentence, as if they were self-organizing! Being it extremely rhythmic, this often could lead us to a sweet soft state of overwhelming emotion, or exalted organic feel to the music .

As you will probably know by now, the same could happen over misplaced letters over an entire phrase. Even if some letters are not at their right proper place, at each word, we could still perceive the whole sentence meaning. Up to your gestaltic neurons to decipher.

Next time you go to a rave party (I never did, neither pretend to), do think about the title of this post, the figure above, as well as on all those great past musicians, along with – unfortunately – awkward current DJ’s, who pass on for hours strident music mixes without knowing at all what Gestalt is all about! Oh, … by the way, should you feel extremely dizzy, do follow Akiyoshi’s advice: If you start feeling unwell when using this website (rave party), immediately cover one eye with your hand and then leave the page (leave the party). Do not close your both eyes because that can make the attack worse!

TENSEGRITY – English words I am in love with #2

Fig. – One of the images used by R. Fuller on his original article back in 1961 (Portfolio and Art News Annual, No.4). [...] There have been recent news references to structures which I have designed for firing to the Moon. Six hundred pounds is the approximate weight of my thirty-six foot diameter sphere self-openable from a thirty-six inch diameter ball. There can, and probably will, be much larger units, which I will discuss later in this disclosure. Of first interest to engineers and artist-conceivers is the fact that my potential prototypes of satellite- and moon-structures are tensional integrity, omni-triangulated, high-tensile-cabled, spherical nets in which local islands of compression act only as local sprit-stiffeners. The local stiffeners are so oriented that they angle inwardly and outwardly between comprehensively finite, exterior and interior, tensional, spherical nets, thus producing positive and negative waves of action and reaction in inter-stabilized dynamic equilibrium. [...]

Tensegrity: 1. Definition coined by R. Buckminster Fuller (architect, engineer and cosmologist), who is best known for his geodesic domes (surely, you will recognize some of these).  Tensegrity is a portmanteau of tensional integrity (check below some passages from his original article in Portfolio and Art News Annual, No.4, 1961). It refers to the integrity of structures as being based in a synergy between balanced tension and compression components. The term “synergetics” may refer more abstractly to synergetic systems of contrasting forces. 2. Structure using distributed tension to hold islands of compression. 3. “The tension-bearing members in these structures – whether Fuller’s domes or Snelson’s sculptures – map out the shortest paths between adjacent members (and are therefore, by definition, arranged geodesically). Tensional forces naturally transmit themselves over the shortest distance between two points, so the members of a tensegrity structure are precisely positioned to best withstand stress. For this reason, tensegrity structures offer a maximum amount of strength.” (Donald Ingber). 4. Was also a term used (unfortunately, let me add) by Carlos Cesar Arana Castaneda (guru! born 1925, Peru) to refer to some movements called magical passes (a series of meditative stretches, stances and movements) that he said were developed by Native American shamans who lived in Mexico in times prior to the Spanish conquest. 4. Tensegrity Ritual Suicides?! Patricia Partin and several other Tensegrity activists went missing after Castaneda’s death in 1998. Later Partin’s body was found in Death Valley Desert. She had apparently committed ritual suicide.

[...] One cannot patent geometry per se nor any separate differentiated-out, pure principle of nature’s operative processes. One can patent, however, the surprise complex behaviors of associated principles, where the behavior of the whole is unpredicted by the behavior of the parts, i.e. synergetic phenomena. The latter is what is known as an invention, a complex arrangement, not found in nature, though sometimes superficially similar to nature. Though superficially similar in patternings to Radiolaria and Flies’ Eyes, geodesic structuring is true invention. The Radiolaria collapse when taken out of water. Flies’ Eyes will not provide structural precedent or man-occupiable structures. [...]

[...] It is a sad fact that the world of patronized design is the last area of commonly accepted social behavior where piracy is considered ethical. Patrons hire designers to steal their competitors’ work. Patrons hire designers to steal other non-professional designers’ fresh-new crops of potential economic growth. Only by joining forces will the architect-, scientist-, engineer-artists be able to eliminate this intellectual cancer of the regenerative processes. [...]

[...] All these Geodesic events were news items simply because they were synergetic surprises, ergo contrary to the obvious. Copied geodesic ventures in higher modular frequency of triangular Geodesic subdivisioning, or other less symmetrical employments of the Geodesic structural integrity than I have as yet undertaken, do not constitute invention.Nor does the variation warrant exemption from the temporary economic authority granted to me as a patent. [...]

On Self-Regulated Swarms, Societal Memory, Speed and Dynamics

 

a) Dynamic Optimization Problems (DOP) tackled by Swarm Intelligence (in here a quick snapshot of the dynamic environment)

b) Swarm adaptive response over time, under severe dynamics, over the dynamic environment on the left (a).

Figs. – Check animated pictures in here. (a) A 3D toroidal fast changing landscape describing a Dynamic Optimization (DO) Control Problem (8 frames in total). (b) A self-organized swarm emerging a characteristic flocking migration behaviour surpassing in intermediate steps some local optima over the 3D toroidal landscape (left), describing a Dynamic Optimization (DO) Control Problem. Over each foraging step, the swarm self-regulates his population and keeps tracking the extrema (44 frames in total).

 [] Vitorino Ramos, Carlos Fernandes, Agostinho C. Rosa, On Self-Regulated Swarms, Societal Memory, Speed and Dynamics, in Artificial Life X – Proc. of the Tenth Int. Conf. on the Simulation and Synthesis of Living Systems, L.M. Rocha, L.S. Yaeger, M.A. Bedau, D. Floreano, R.L. Goldstone and A. Vespignani (Eds.), MIT Press, ISBN 0-262-68162-5, pp. 393-399, Bloomington, Indiana, USA, June 3-7, 2006.

PDF paper.

Wasps, bees, ants and termites all make effective use of their environment and resources by displaying collective “swarm” intelligence. Termite colonies – for instance – build nests with a complexity far beyond the comprehension of the individual termite, while ant colonies dynamically allocate labor to various vital tasks such as foraging or defense without any central decision-making ability. Recent research suggests that microbial life can be even richer: highly social, intricately networked, and teeming with interactions, as found in bacteria. What strikes from these observations is that both ant colonies and bacteria have similar natural mechanisms based on Stigmergy and Self-Organization in order to emerge coherent and sophisticated patterns of global foraging behavior. Keeping in mind the above characteristics we propose a Self-Regulated Swarm (SRS) algorithm which hybridizes the advantageous characteristics of Swarm Intelligence as the emergence of a societal environmental memory or cognitive map via collective pheromone laying in the landscape (properly balancing the exploration/exploitation nature of our dynamic search strategy), with a simple Evolutionary mechanism that trough a direct reproduction procedure linked to local environmental features is able to self-regulate the above exploratory swarm population, speeding it up globally. In order to test his adaptive response and robustness, we have recurred to different dynamic multimodal complex functions as well as to Dynamic Optimization Control problems, measuring reaction speeds and performance. Final comparisons were made with standard Genetic Algorithms (GAs), Bacterial Foraging strategies (BFOA), as well as with recent Co-Evolutionary approaches. SRS’s were able to demonstrate quick adaptive responses, while outperforming the results obtained by the other approaches. Additionally, some successful behaviors were found: SRS was able to maintain a number of different solutions, while adapting to unforeseen situations even when over the same cooperative foraging period, the community is requested to deal with two different and contradictory purposes; the possibility to spontaneously create and maintain different sub-populations on different peaks, emerging different exploratory corridors with intelligent path planning capabilities; the ability to request for new agents (division of labor) over dramatic changing periods, and economizing those foraging resources over periods of intermediate stabilization. Finally, results illustrate that the present SRS collective swarm of bio-inspired ant-like agents is able to track about 65% of moving peaks traveling up to ten times faster than the velocity of a single individual composing that precise swarm tracking system. This emerged behavior is probably one of the most interesting ones achieved by the present work. 

 

Stigmergic Optimization (Springer Book)

Abraham, Ajith; Grosan, Crina; Ramos, Vitorino (Eds.), Stigmergic Optimization, Studies in Computational Intelligence (series), Vol. 31, Springer-Verlag, ISBN: 3-540-34689-9, 295 p., Hardcover, 2006.

TABLE OF CONTENTS (short /full) / CHAPTERS:

[1] Stigmergic Optimization: Foundations, Perspectives and Applications.
[2] Stigmergic Autonomous Navigation in Collective Robotics.
[3] A general Approach to Swarm Coordination using Circle Formation.
[4] Cooperative Particle Swarm Optimizers: a powerful and promising approach.
[5] Parallel Particle Swarm Optimization Algorithms with Adaptive
 Simulated Annealing.
[6] Termite: a Swarm Intelligent Routing algorithm for Mobile
 Wireless ad-hoc Networks.
[7] Linear Multiobjective Particle Swarm Optimization.
[8] Physically realistic Self-Assembly Simulation system.
[9] Gliders and Riders: A Particle Swarm selects for coherent Space-time Structures in Evolving Cellular Automata.
[10] Stigmergic Navigation for Multi-agent Teams in Complex Environments.
[11] Swarm Intelligence: Theoretical proof that Empirical techniques are Optimal.
[12] Stochastic Diffusion search: Partial function evaluation in Swarm Intelligence Dynamic Optimization.

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.

EXAPTIVE – English words I am in love with #1

Fig. – The famous frontispiece from Scilla’s treatise of 1670 defending the organic nature of fossils. The solid young man, representing the truth of sensory experi­ence, shows a fossil sea urchin in his right hand to a wraithlike figure represent­ing the former style of speculative thinking. With his left hand, the solid figure points to other fossils found in Sicily. The text proclaims: “Vain speculation un­deceived by the senses.” (from, Stephen Jay Gould, “The Structure Of Evolutionary Theory”, The Belknap Press of Harvard University Press”, Cambridge, Massachusetts, 2002).

Exaptation: 1. The use of a biological structure or function for a purpose other than that for which it initially evolved. 2. An evolutionary process in which a given adaptation is first naturally selected for, and subsequently used by the organism for something other than its original, intended purpose. 3. Exaptations – Features (such as feathers) that evolved by selection for one purpose (such as warmth) and were later adapted to a new purpose (such as flight). [more]. Exaptive: to show exaptation – featuring it.

Our rock stars aren’t like your rock stars

Video – “Intel Star” TV ad – Who’s your rock star? – Rather than focusing on a new product, the 2009 “Sponsors of Tomorrow” ad campaign celebrates what makes Intel different culture, personality, heroes – and ways Intel has helped change the world for over 40 years. Featuring Ajay Bhatt co-inventor of USB !

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.