“I would like to thank flocks, herds, and schools for existing: nature is the ultimate source of inspiration for computer graphics and animation.” in Craig Reynolds, “Flocks, Herds, and Schools: A Distributed Behavioral Model“, (paper link) published in Computer Graphics, 21(4), July 1987, pp. 25-34. (ACM SIGGRAPH ’87 Conference Proceedings, Anaheim, California, July 1987.)
“There is an entire genealogy to be written from the point of view of the challenge posed by insect coordination, by “swarm intelligence.” Again and again, poetic, philosophical, and biological studies ask the same question: how does this “intelligent,” global organization emerge from a myriad of local, “dumb” interactions?” — Alex Galloway and Eugene Thacker, The Exploit.
[...] The interest in swarms was intimately connected to the research on emergence and “superorganisms” that arose during the early years of the twentieth century, especially in the 1920s. Even though the author of the notion of superorganisms was the now somewhat discredited writer Herbert Spencer,63 who introduced it in 1898, the idea was fed into contemporary discourse surrounding swarms and emergence through myrmecologist William Morton Wheeler. In 1911 Wheeler had published his classic article “The Ant Colony as an Organism” (in Journal of Morphology), and similar interests continued to be expressed in his subsequent writings. His ideas became well known in the 1990s in discussions concerning artificial life and holistic swarm-like organization. For writers such as Kevin Kelly, mentioned earlier in this chapter, Wheeler’s ideas regarding superorganisms stood as the inspiration for the hype surrounding emergent behavior.64 Yet the actual context of his paper was a lecture given at the Marine Biological Laboratory at Woods Hole in 1910.65 As Charlotte Sleigh points out, Wheeler saw himself as continuing the work of holistic philosophers, and later, in the 1910s and 1920s, found affinities with Bergson’s philosophy of temporality as well.66 In 1926, when emergence had already been discussed in terms of, for example, emergent evolution, evolutionary naturalism, creative synthesis, organicism, and emergent vitalism, Wheeler noted that this phenomenon seemed to challenge the basic dualisms of determinism versus freedom, mechanism versus vitalism, and the many versus the one.67 An animal phenomenon thus presented a crisis for the fundamental philosophical concepts that did not seem to apply to such a transversal mode of organization, or agencement to use the term that Wheeler coined. It was a challenge to philosophy and simultaneously to the physical, chemical, psychological, and social sciences, a phenomenon that seemed to cut through these seemingly disconnected spheres of reality.
In addition to Wheeler, one of the key writers on emergence – again also for Kelly in his Out of Control 68 – was C. Lloyd Morgan, whose Emergent Evolution (1927) proposed to see evolution in terms of emergent “relatedness”. Drawing on Bergson and Whitehead, Morgan rejected a mechanistic dissecting view that the interactions of entities “whether physical or mental” always resulted only in “mixings” that could be seen beforehand. Instead he proposed that the continuity of the mechanistic relations were supplemented with sudden changes at times. At times reminiscent of Lucretius’s view that there is a basic force, clinamen, that is the active differentiating principle of the world, Morgan focused on how qualitative changes in direction could affect the compositions and aggregates. He was interested in the question of the new and how novelty is possible. In his curious modernization of Spinoza, Morgan argued for the primacy of relations – or “relatedness,” to be accurate.69 Instead of speaking of agencies or activities, which implied a self-enclosed view of interactions, in Emergent Evolution Morgan propagated in a way an ethological view of the world. Entities and organisms are characterized by relatedness, the tendency to relate to their environment and, for example, other organisms. So actually, what emerge are relations:
“If it be asked: What is it that you claim to be emergent? the brief reply is: Some new kind of relation. Revert to the atom, the molecule, the thing (e.g. a crystal), the organism, the person. At each ascending step there is a new entity in virtue of some new kind of relation, or set of relations, within it, or, as I phrase it, intrinsic to it. Each exhibits also new ways of acting on, and reacting to, other entities. There are new kinds of extrinsic relatedness“.70
The evolutionary levels of mind, life, and matter are in this scheme intimately related, with the lower levels continuously affording the emergence of so-called higher functions, like those of humans. Different levels of relatedness might not have any understanding of the relations that define other levels of existence, but still these other levels with their relations affect the other levels. Morgan tried, nonetheless, to steer clear of the idealistic notions of humanism that promoted the human mind as representing a superior stage in emergence. His stance was much closer to a certain monism in which mind and matter are continuously in some kind of intimate correspondence whereby even the simplest expressions of life participate in a wider field of relatedness. In Emergent Evolution Morgan described relations as completely concrete. He emphasized that the issue is not only about relations in terms but as much about terms in relation, with concrete situations, or events, stemming from their relations.71 In a way, other views on emergence put similar emphasis on the priority of relations, expressing a kind of radical empiricism in the vein of William James. Drawing on E. G. Spaulding’s 1918 study The New Rationalism, Wheeler noted the unpredictable potentials in connectionism: a connected whole is more than (or at least nor reducible to) its constituent parts, implying the impossibility to find causal determination of aggregates. Whereas existing sciences might be able to recognize and track down certain relationships that they have normalized or standardized, the relations might still produce properties that are beyond those of the initial conditions – and thus also demand a vector of analysis that parts from existing theories – dealing with properties that open up only in relation to themselves (as a “law unto themselves”). 72 Instead, a more complicated mode of development was at hand, in which aggregates, or agencements, simultaneously involved various levels of reality. This also implied that aggregates, emergent orders, have no one direction but are constituted of relations that extend in various directions:
“We must also remember that most authors artificially isolate the emergent whole and fail to emphasize the fact that its parts have important relations not only with one another but also with the environment and that these external relations may contribute effectively towards producing both the whole and its novelty“.73 [...]
in (passage from), Jussi Parikka, “Insect Media: An Archaeology of Animals and Technology“, Chapter II – Genesis of Form: Insect Architecture and Swarms, (section) Emergence and Relatedness: A Radical Empiricism – take one, pp. 51-53, University of Minnesota Press, Minneapolis, 2011.
“I saw them hurrying from either side, and each shade kissed another, without pausing; Each by the briefest society satisfied. (Ants in their dark ranks, meet exactly so, rubbing each other’s noses, to ask perhaps; What luck they’ve had, or which way they should go.)” — Dante, Purgatorio, Canto XXVI.
Video documentary: A 15-minute program produced from February 1949 to April 1952, Kieran’s Kaleidoscope presented its writer and host in his well-acquainted role as the learned and witty guide to the complexities of human knowledge (Production Company: Almanac Films). This is probably the most genuinely entertaining of all the John Kieran‘s Kaleidoscope films. On Ant City (1949) [Internet Archive] produced by Paul F. Moss, the poor ants are anthropomorphized to the nth degree; we even hear the Wedding March when the “queen” and her drone fly away from the nest. Kieran‘s patter has never been more meandering; he sounds like a befuddled uncle narrating home movies. Clumsy but enjoyable.
[...] In conclusion, much elegant work has been done starting from activated mono-nucleotides. However, the prebiotic synthesis of a specific macromolecular sequence does not seem to be at hand, giving us the same problem we have with polypeptide sequences. Since there is no ascertained prebiotic pathway to their synthesis, it may be useful to try to conceive some working hypothesis. In order to do that, I would first like to consider a preliminary question about the proteins we have on our Earth: “Why these proteins … and not other ones?”. Discussing this question can in fact give us some clue as to how orderly sequences might have originated. [...] A grain of sand in the Sahara – This is indeed a central question in our world of proteins. How have they been selected out? There is a well-known arithmetic at the basis of this question, (see for example De Duve, 2002) which says that for a polypeptide chain with 100 residues, 20^100 different chains are in principle possible: a number so large that it does not convey any physical meaning. In order to grasp it somewhat, consider that the proteins existing on our planet are of the order of a few thousand billions, let us say around 10^13 (and with all isomers and mutations we may arrive at a few orders of magnitude more). This sounds like a large number. However, the ratio between the possible (say 20^100) and the actual chains (say 10^15) corresponds approximately to the ratio between the radius of the universe and the radius of a hydrogen atom! Or, to use another analogy, nearer to our experience, a ratio many orders of magnitude greater than the ratio between all the grains of sand in the vast Sahara and a single grain. The space outside “our atom”, or our grain of sand, is the space of the “never-born proteins”, the proteins that are not with us – either because they didn’t have the chance to be formed, or because they “came” and were then obliterated. This arithmetic, although trivial, bears an important message: in order to reproduce our proteins we would have to hit the target of that particular grain of sand in the whole Sahara. Christian De Duve, in order to avoid this “sequence paradox” (De Duve, 2002), assumes that all started with short polypeptides – and this is in fact reasonable. However, the theoretically possible total number of long chains does not change if you start with short peptides instead of amino acids. The only way to limit the final number of possible chains would be to assume, for example, that peptide synthesis started only under a particular set of conditions of composition and concentration, thus bringing contingency into the picture. As a corollary, then, this set of proteins born as a product of contingency would have been the one that happened to start life. Probably there is no way of eliminating contingency from the aetiology of our set of proteins. [...]
Figure – The ratio between the theoretical number of possible proteins and their actual number is many orders of magnitude greater than the ratio between all sand of the vast Sahara and a single grain of sand (caption on page 69).
[...] The other objection to the numerical meaning suggested by Figure (above) is that the maximum number of proteins is much smaller because a great number of chain configurations are prohibited for energetic reasons. This is reasonable. Let us then assume that 99.9999% of theoretically possible protein chains cannot exist because of energy reasons. This would leave only one protein out of one million, reducing the number of never-born proteins from, say, 10^60 to 10^54. Not a big deal. Of course one could also assume that the total number of energetically allowed proteins is extremely small, no larger than, say, 10^10. This cannot be excluded a priori, but is tantamount to saying that there is something very special about “our” proteins, namely that they are energetically special. Whether or not this is so can be checked experimentally as will be seen later in a research project aimed at this target. The assumption that “our” proteins have something special from the energetic point of view, would correspond to a strict deterministic view that claims that the pathway leading to our proteins was determined, that there was no other possible route. Someone adhering strictly to a biochemical anthropic principle might even say that these proteins are the way they are in order to allow life and the development of mankind on Earth. The contingency view would recite instead the following: if our proteins or nucleic acids have no special properties from the point of view of thermodynamics, then run the tape again and a different “grain of sand” might be produced – one that perhaps would not have supported life. Some may say at this point that proteins derive in any case from nucleic-acid templates – perhaps through a primitive genetic code. However, this is really no argument – it merely shifts the problem of the etiology of peptide chains to etiology of oligonucleotide chains, all arithmetic problems remaining more or less the same. [...] pp. 68-70, in Pier Luigi Luisi, “The Emergence of Life: From Chemical Origins to Synthetic Biology“, Cambridge University Press, US, 2006.
Photo – (Profligate Nature) Sintra Nov. 6 2011.
Photo – (Repeated Profligate Nature) Sintra Nov. 6 2011 (click to enlarge).
Ever tried to solve a problem where its own problem statement is changing constantly? Have a look on our approach:
Vitorino Ramos, David M.S. Rodrigues, Jorge Louçã, “Spatio-Temporal Dynamics on Co-Evolved Stigmergy“, in European Conference on Complex Systems, ECCS’11, Vienna, Austria, Sept. 12-16 2011.
Abstract: Research over hard NP-complete Combinatorial Optimization Problems (COP’s) has been focused in recent years, on several robust bio-inspired meta-heuristics, like those involving Evolutionary Computation (EC) algorithmic paradigms. One particularly successful well-know meta-heuristic approach is based on Swarm Intelligence (SI), i.e., the self-organized stigmergic-based property of a complex system whereby the collective behaviors of (unsophisticated) entities interacting locally with their environment cause coherent functional global patterns to emerge. This line of research recognized as Ant Colony Optimization (ACO), uses a set of stochastic cooperating ant-like agents to find good solutions, using self-organized stigmergy as an indirect form of communication mediated by artificial pheromone, whereas agents deposit pheromone-signs on the edges of the problem-related graph complex network, encompassing a family of successful algorithmic variations such as: Ant Systems (AS), Ant Colony Systems (ACS), Max-Min Ant Systems (Max-Min AS) and Ant-Q.
Albeit being extremely successful these algorithms mostly rely on positive feedback’s, causing excessive algorithmic exploitation over the entire combinatorial search space. This is particularly evident over well known benchmarks as the symmetrical Traveling Salesman Problem (TSP). Being these systems comprised of a large number of frequently similar components or events, the principal challenge is to understand how the components interact to produce a complex pattern feasible solution (in our case study, an optimal robust solution for hard NP-complete dynamic TSP-like combinatorial problems). A suitable approach is to first understand the role of two basic modes of interaction among the components of Self-Organizing (SO) Swarm-Intelligent-like systems: positive and negative feedback. While positive feedback promotes a snowballing auto-catalytic effect (e.g. trail pheromone upgrading over the network; exploitation of the search space), taking an initial change in a system and reinforcing that change in the same direction as the initial deviation (self-enhancement and amplification) allowing the entire colony to exploit some past and present solutions (environmental dynamic memory), negative feedback such as pheromone evaporation ensure that the overall learning system does not stables or freezes itself on a particular configuration (innovation; search space exploration). Although this kind of (global) delayed negative feedback is important (evaporation), for the many reasons given above, there is however strong assumptions that other negative feedbacks are present in nature, which could also play a role over increased convergence, namely implicit-like negative feedbacks. As in the case for positive feedbacks, there is no reason not to explore increasingly distributed and adaptive algorithmic variations where negative feedback is also imposed implicitly (not only explicitly) over each network edge, while the entire colony seeks for better answers in due time.
In order to overcome this hard search space exploitation-exploration compromise, our present algorithmic approach follows the route of very recent biological findings showing that forager ants lay attractive trail pheromones to guide nest mates to food, but where, the effectiveness of foraging networks were improved if pheromones could also be used to repel foragers from unrewarding routes. Increasing empirical evidences for such a negative trail pheromone exists, deployed by Pharaoh’s ants (Monomorium pharaonis) as a ‘no entry‘ signal to mark unrewarding foraging paths. The new algorithm comprises a second order approach to Swarm Intelligence, as pheromone-based no entry-signals cues, were introduced, co-evolving with the standard pheromone distributions (collective cognitive maps) in the aforementioned known algorithms.
To exhaustively test his adaptive response and robustness, we have recurred to different dynamic optimization problems. Medium-size and large-sized dynamic TSP problems were created. Settings and parameters such as, environmental upgrade frequencies, landscape changing or network topological speed severity, and type of dynamic were tested. Results prove that the present co-evolved two-type pheromone swarm intelligence algorithm is able to quickly track increasing swift changes on the dynamic TSP complex network, compared to standard algorithms.
Keywords: Self-Organization, Stigmergy, Co-Evolution, Swarm Intelligence, Dynamic Optimization, Foraging, Cooperative Learning, Combinatorial Optimization problems, Dynamical Symmetrical Traveling Salesman Problems (TSP).
Fig. – Recovery times over several dynamical stress tests at the fl1577 TSP problem (1577 node graph) – 460 iter max – Swift changes at every 150 iterations (20% = 314 nodes, 40% = 630 nodes, 60% = 946 nodes, 80% = 1260 nodes, 100% = 1576 nodes). [click to enlarge]
” [...] What I refused to see is what the prisoner’s dilemma teaches: anyone who plays the “All Cooperate” strategy is a sucker, and incents the other to defect on every move. I now believe that the lesson of the prisoner’s dilemma is that a robust ethic succeeds where a weak one fails. Be fair, be strong, reward cooperation and punish defection, and you will have nothing to regret. [...] “, in An Ethic Based on the Prisoner’s Dilemma, The Ethical Spectacle, September, 1995.
[...] Martin Nowak is known for his many influential papers on cooperation and in theoretical biology. This book is a popular writing on his scientific adventures, personal motivations and collaborations. Given his work it is remarkable is that this book does contain nor mathematical equations neither graphical illustrations. Nowak is currently a professor of mathematics and biology at Harvard University. Moreover, he directs since 2003 his own research program on Evolutionary Dynamics. This program has been made possible by a 30 million pledge by Wall Street tycoon Jeffrey Epstein. This is just one ingredient of the remarkable story of Nowak scientific life. The book starts with laying out the puzzle of cooperation illustrated by the prisoner’s dilemma. If both players are selfish and rational they will defect. Why do we see so much cooperation in human societies and other domains of the biological world? This puzzle was introduced to Nowak by Karl Sigmund, a professor in mathematics from the University of Vienna, while Nowak was a student in biochemistry. Sigmund talked about the famous Axelrod tournament and Nowak got hooked. The tournament of Axelrod assumed that the strategies did not make errors. What if there are errors? Will Tit for Tat still be a good strategy? His analysis showed that a more promising strategy is a more Win Stay, Loose Shift. This strategy leads to cooperation if both agents do the same, and defect if not. Hence agents can forgive.
The analysis of strategies that do well in direct reciprocity is one of the five chapters in which Nowak discuss five ways in which the prisoner’s dilemma can be solved. The second chapter is on indirect reciprocity. In a landmark paper with Karl Sigmund Nowak showed that when agents derive information on their reputation (image score) cooperation can evolve in one-shot prisoner’s dilemma. The third chapter is on spatial games and features another landmark paper on spatial chaos. This paper, written with Lord Robert May, shows that cooperation can evolve if agents interact with neighbours and imitate the best strategy of their neighbours. The forth chapter is on group selection. This controversial approach is now better known as multi-level selection. Finally, the fifth chapter is on kin-selection, the first theory on cooperation based on genetic relatedness. The discussion on the five ways to overcome the prisoner’s dilemma is especially interesting due to the discussion on the scientific process. How long hikes with Sigmund let to inspirations that let Nowak drop all other activities he was working on. How chance meetings let to new ideas. How he got, to Oxford, Princeton and finally Harvard.
In the second part of the book discusses cooperation in biology. It covers his applications to the origins of life, the study of cancer and the dominance of ant colonies. This work might be less familiar to the readers of JASSS. Especially the work on cancer, defectors in our own biology, can lead to practical applications. The final part of the book focuses on human societies. Humans are called supercooperators since they are the only organism that uses all five ways to solve social dilemmas. First the evolution of language is discussed. Nowak made important contributions to the study of language by simulating agents benefiting from mutual understanding in language games. According to Nowak, the emergence of language is the most important development in life since 600 million years. It resulted to new types of cooperation. Especially in the context of indirect reciprocity it is key to have language. We need gossip and other types of information transmission to derive reliable estimates on the reputation of strangers.
Then Nowak discusses public goods and the use of costly punishment to derive cooperation. This is the only part of the book where he discusses empirical research. With two graduate students he performed experiments which showed that punishment is not something special, but in line with earlier work on reciprocity and tit for tat. Then Nowak continues with his recent work on network theory and set theory. The book closes with a reflection on the consequences of his work. Cooperation is a crucial ingredient to evolution, but there always will be cycles. The question is how to re-establish cooperation after it has been collapsed. This book provides a nice overview of the findings of Nowak’s work. Note however, that Nowak has substantial work in other areas of research not discussed in the book such as infectious diseases. Together with science writer Roger Highfield, Nowak provides an inspirational story on science in practice. This covers the importance of his mentors in his early years, and his current role of a mentor to his students at Harvard. In conclusion, this is a marvellous book. Although I may not always agree with the findings of Nowak’s research, it is a motivating account on the messy practice of science. I highly recommend this book for students and faculty in social simulation and science in general. [...], Reviewed by Marco A. Janssen
(Arizona State University) on JASSS 2011 [Nowak, Martin, Supercooperators: Altruism, Evolution, and Why We Need Each Other to Succeed, ISBN 9781439100189 (pb), Free Press (The): New York, NY, 2011].
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.
Photo – (Dominoes I) Left alone in the previous night, an empty dominoes table at Sanlúcar de Guadiana (one of my favorite places – taken last weekend; Oct. 2 2011).
Picture – Beautiful and rhizomatic (let me add) neutrino track events photo taken by LNS at MIT (The Conrad Research Group, link).
“We are very much astonished by this result, but a result is never a discovery until other people confirm it. When you get such a result you want to make sure you made no mistakes, that there are no nasty things going on you didn’t think of. We spent months and months doing checks and we have not been able to find any errors. If there is a problem, it must be a tough, nasty effect, because trivial things we are clever enough to rule out.” ~ Antonio Ereditato, coordinator of the Opera project (Oscillation Project with Emulsion-tRacking Apparatus), Guardian (link), UK, 22 Sept. 2011.
“It is sometimes said that we should never believe a scientific theory until it is verified by experiment. But a famous astronomer has also stated that we should never believe an observation until it is confirmed by a theory.” ~ João Magueijo, Faster Than the Speed of Light, Penguin books, Feb. 2004 (early published in 2003).
So …, you and me -we all now- can change (e.g.) emails at 299.798,454 meters per second (warning: “suddenly ongoing” number hypotheses by a ‘clever‘ science team coordinator). That’s roughly a fraction of 20 parts per million more than last week (as the standard light speed stands for 299.792,458 m/s); i.e. 6 Km/s more (six, not … let us say nine Km more, still buzzes me for other reasons). Not -by all means-, reaching this amazing speed, I decided to depict (above) two different quotes for their stark contrast (all those underlined parts, made me smile a little, having in mind all the rest in context).
Surprised?! Don’t be. Science, fortunately moves on precisely this way. If a paradigmatic change occurs, that’s a healthy signal, not the contrary. My concern here today is not about change (along with their implications and applications, which could be huge), but rather -instead- when that change happened and to tribute those who have made that paradigm shift possible, creating an entire new research field possible to be exploited, Albert Einstein included. Ironically, the Ereditato OPERA et al. team paper starts on page 1 (image below) with a stream of no less than more than 100 authors, and it ends (conclusions, page 22) with an – at least – “enigmatic” phrase: We deliberately do not attempt any theoretical or phenomenological interpretation of the results (the full 24 pages work could be retrieved from arXiv). Having this in mind, I wonder if this recent paper did not forgot to mention someone.
Superluminal theory or commonly know as Faster-than-light (FTL) communications and travel refer to the propagation of information or matter faster than the speed of light, a field with an enormous potential. Under the special theory of relativity (Wikipedia link), a particle (that has mass) with subluminal velocity needs infinite energy to accelerate to the speed of light, although special relativity does not forbid the existence of particles that travel faster than light at all times.
The “world” however seems to forget a paper done in 1998 by João Magueijo (Imperial College, London) on the Varying speed of light (VSL) theory of cosmology, proposing precisely that light speed was much higher in the early universe, by 60 orders of magnitude faster than its present value. João, was in fact the pioneer of VSL (along with John Moffat‘s early works). Their work starts like this (abstract):
“We consider the cosmological implications of light traveling faster in the early Universe. We propose a prescription for deriving corrections to the cosmological evolution equations while the speed of light c is changing. We then show how the horizon, flatness, and cosmological constant problems may be solved. We also study cosmological perturbations in this scenario and show how one may solve the homogeneity and isotropy problems. As it stands, our scenario appears to most easily produce extreme homogeneity, requiring structure to be produced in the Standard Big Bang epoch. Producing significant perturbations during the earlier epoch would require a rather careful design of the function c(t). The large entropy inside the horizon nowadays can also be accounted for in this scenario. “, in Andreas Albrecht and João Magueijo; “A time varying speed of light as a solution to cosmological puzzles“, Physical Review D, Phys.Rev.D59:043516,1999 (the full 14 pages work published later in 1999 could be retrieved from arXiv).
Picture – João Magueijo (Imperial College, London).
A major work, onto which all his energies were necessary. Andreas and João fighted for years for their publication to pass the main journals, like Nature and Science. Later on, Magueijo decides to discuss his personal struggles pursuing VSL in his 2003 book, Faster Than The Speed of Light, The Story of a Scientific Speculation. For those who have actually read the book (not many let me say), do know that he spends most of its pages discussing, not VSL, but rather the counter aspect of conservationism and reductionism in Science, Academia and research. He does not spare Portugal also. Born in Évora (Alentejo, southern Portugal) in 1967, he mentions over several passages: I will never return. I now agree with him. Back in 2000 I spoke with several foreign as well as Portuguese physicists. No one knew him, or his work. Or if they did (yes, some did), nobody cared. They still do. For them, it was a sacrilege to open a little variation on Einstein‘s theory.
For what I have seen these days on newspapers and TV, the same conservationism keeps ruling, even if the media keeps inviting the most prominent commentators on the field, … the same as usual. Independently from the variation, they keep saying the same, or being skeptic. But I keep wondering if what they have is really a pure genuine scientific skepticism. Not surprised at all, let me add. Over my life, I have met mathematicians that do not know what a Voronoi tessellation is. Increasingly, the same goes on for a Johnson-Mehl. Or Portuguese physicists who have never heard about Per Bak‘s self-organized criticality. A massive mass-media delivered oblivion. Now gone worldwide, it seems.
Being skeptic is crucial (at some point). It’s one of the key ingredients in Science. Not however, when much before this present 2011 buzz OPERA paper, a small team on the other side of the planet, in Australia, verified experimentally that Magueijo was right, a few months after his 1999 work (funny, … Einstein‘s theory was experimentally proved on São Tomé and Príncipe, also abroad, near the Equator). I do remember the news back then, but … hey, after one decade now, I do not have the link anymore – sorry, I’m not a physicist. Neither a mathematician. With patience, one of these days I will google it out. My memory is not what it was.
Fortunately, Magueijo‘s memory is not like ours. He knows where the right guys are. Or if he – by one good reason- misses them (as it was the case here), he goes after them. Not happy with Faster than Light, in 2009, he decided to publish a second book: A Brilliant Darkness, an impressive account of the life and science of the vanished Italian physicist Ettore Majorana. For that, he random-walks the entire Italy, from one point to another, during months, even taking boats back and forth, grasping Majorana memoirs and the “fatal” accident and disappearance, still unsolved. Now that, I absolutely recommend as a good reading for some Italian science team coordinators.
Back in 2001, living in a cheap hotel, for several weeks, in Kensington Road, while working daily at the Imperial College for a project aiming for new types of Neural Networks for Pollution control and forecasting, while the cold rain shuffled the windows outside, several times my thoughts went on what are the 10 key features present in a good scientist. I will spare you what I consider to be my 10 list (mail me one day if you feel curiosity about them) – anyway here are my first three: (3) honesty, (2) imagination and (1) courage. João, as I believe, had it all, namely the first one in tremendous proportions. 30 meters away from the Queen’s tower, daily on a cave, at the Imperial College main pub by 5 P.M, I had a couple of pints. Everyday I wished he was there, joining me: he do loves a good beer too. But he was definitively elsewhere on the campus, probably over another nearby pub at that hour. Never saw him. Never thought of climbing from my lab to his, in order to say hello. After one month, I left London.
For his amazing work and courage, as I said earlier last week over Twitter (link): “João Magueijo rocks! Neutrinos too. Both can travel faster than light. :-)“. Above all, those erratic neutrinos should be smiling now. Probably, by 60 orders of magnitude faster than its present value.
David M.S. Rodrigues, Jorge Louçã, Vitorino Ramos, “From Standard to Second Order Swarm Intelligence Phase-space maps“, in European Conference on Complex Systems, ECCS’11, Vienna, Austria, Sept. 12-16 2011.
Abstract: Standard Stigmergic approaches to Swarm Intelligence encompasses the use of a set of stochastic cooperating ant-like agents to find optimal solutions, using self-organized Stigmergy as an indirect form of communication mediated by a singular artificial pheromone. Agents deposit pheromone-signs on the edges of the problem-related graph to give rise to a family of successful algorithmic approaches entitled Ant Systems (AS), Ant Colony Systems (ACS), among others. These mainly rely on positive feedback’s, to search for an optimal solution in a large combinatorial space. The present work shows how, using two different sets of pheromones, a second-order co-evolved compromise between positive and negative feedback’s achieves better results than single positive feedback systems. This follows the route of very recent biological findings showing that forager ants, while laying attractive trail pheromones to guide nest mates to food, also gained foraging effectiveness by the use of pheromones that repelled foragers from unrewarding routes. The algorithm presented here takes inspiration precisely from this biological observation.
The new algorithm was exhaustively tested on a series of well-known benchmarks over hard NP-complete Combinatorial Optimization Problems (COP’s), running on symmetrical Traveling Salesman Problems (TSP). Different network topologies and stress tests were conducted over low-size TSP’s (eil51.tsp; eil78.tsp; kroA100.tsp), medium-size (d198.tsp; lin318.tsp; pcb442.tsp; att532.tsp; rat783.tsp) as well as large sized ones (fl1577.tsp; d2103.tsp) [numbers here referring to the number of nodes in the network]. We show that the new co-evolved stigmergic algorithm compared favorably against the benchmark. The algorithm was able to equal or majorly improve every instance of those standard algorithms, not only in the realm of the Swarm Intelligent AS, ACS approach, as in other computational paradigms like Genetic Algorithms (GA), Evolutionary Programming (EP), as well as SOM (Self-Organizing Maps) and SA (Simulated Annealing). In order to deeply understand how a second co-evolved pheromone was useful to track the collective system into such results, a refined phase-space map was produced mapping the pheromones ratio between a pure Ant Colony System (where no negative feedback besides pheromone evaporation is present) and the present second-order approach. The evaporation rate between different pheromones was also studied and its influence in the outcomes of the algorithm is shown. A final discussion on the phase-map is included. This work has implications in the way large combinatorial problems are addressed as the double feedback mechanism shows improvements over the single-positive feedback mechanisms in terms of convergence speed and on major results.
Keywords: Stigmergy, Co-Evolution, Self-Organization, Swarm Intelligence, Foraging, Cooperative Learning, Combinatorial Optimization problems, Symmetrical Traveling Salesman Problems (TSP), phase-space.
Fig. – Comparing convergence results between Standard algorithms vs. Second Order Swarm Intelligence, over TSP fl1577 (click to enlarge).
Picture – (click to enlarge) We all are on a huge spacecraft full of water, … the big blue marble. The new OMEGA watch campaign, Planet Ocean, features a giant swarm of sardines in deep blue ocean along with a well known quote from Buzz Aldrin, the astronaut (Wien, Sept. 2011).
“Standing on the Moon looking back at Earth – this lovely place you just came from – you see all the colours, and you know what they represent. Having left the water planet, with all that water brings to Earth in terms of colour and abudance life, the absence of water and atmosphere on the desolate surface of the Moon gives rise to a stark contrast.”, ~ Buzz Aldrin, astronaut.
Picture – The European Conference on Complex Systems (ECCS’11 – link) at one of the main Austrian newspapers Der Standard: “Die ganze Welt als Computersimulation” (link), Klaus Taschwer, Der Standard, 14 September [click to enlarge - photo taken at the conference on Sept. 15, Vienna 2011].
“Take Darwin, for example: would Caltech have hired Darwin? Probably not. He had only vague ideas about some of the mechanisms underlying biological Evolution. He had no way of knowing about genetics, and he lived before the discovery of mutations. Nevertheless, he did work out, from the top down, the notion of natural selection and the magnificent idea of the relationship of all living things.” Murray Gell-Mann in “Plectics“, excerpted from The Third Culture: Beyond the Scientific Revolution by John Brockman (Simon & Schuster, 1995).
To be honest, I didn’t enjoy this title, but all of us had a fair share with journalists, now and then by now. After all, 99% of us don’t do computer simulation. We are all after the main principles, and their direct applications.
During 5 days (12-16 Sept.), with around 700 attendees the Vienna 2011 conference evolved around main important themes as Complexity & Networks (XNet), Current Trends in Game Theory, Complexity in Energy Infrastructures, Emergent Properties in Natural and Artificial Complex Systems (EPNACS), Complexity and the Future of Transportation Systems, Econophysics, Cultural and Opinion Dynamics, Dynamics on and of Complex Networks, Frontiers in the Theory of Evolution, and – among many others – Dynamics of Human Interactions.
For those who know me (will definitely understand), I was mainly attending those sessions underlined above, the last one (Frontiers in Evolution) being one of my favorites, among all these ECCS years. All in all, the conference had highly quality works (daily, we had about 3-4 works I definitely think should be followed in the future) and to those, more attention should be deserved (my main critics to the conference organization goes in here). Naturally, the newspaper article also reflects on the FuturICT, being historically one of the major scientific European projects ever done (along, probably, with the Geneva LHC), which teams spread across Europe, including Portugal with a representative team of 7 members present on the conference, led by Jorge Louçã, the former editor and organizer on the previous ECCS’10 last year in Lisbon.
Video – “… they forgot to say: in principle!“. Ricard Solé addressing the topic of a Morphospace for Biological Computation at ECCS’11 (European Conference on Complex Systems), while keeping is good humor on.
Let me draw anyway your attention to 4 outstanding lectures: Peter Schuster (link) on the first day, dissected on the source of Complexity in Evolution, battling among – as he puts it – two paradoxes: (1) Evolution is an enormously complex process, and (2) biological evolution on Earth proceeds from lower towards higher complexity. Earlier on that morning – opening the conference -, Murray Gell-Mann (link) who co-founded the Santa Fe Institute in 1984, gave a wonderful lecture on Generalized Entropies. Besides his age, the 1969 Nobel Prize in physics for his work on the theory of elementary particles, gladly turned his interest in the 1990s to the theory of Complex Adaptive Systems (CAS). Next, Albert-László Barabási (link), tamed Complexity on Controlling Networks. Finally, at the last day, closing the conference in pure gold, Ricard Solé (link) addressed the topic of a Morphospace for Biological Computation, an amazing lecture with a powerful topic to which – nevertheless – I felt he had little time (20 minutes), for such a rich endeavor. However – by no means -, he have lost his good humor during the talk (check my video above). Next year, the conference will be held in Brussels, and by just judging at the poster design, it promises. Go ants, go … !
Picture – The European Conference on Complex Systems (ECCS’12 – link) poster design for next year in Brussels.
Photo – Young Glenn Gould in February 1946 with his English Setter dog, Nick.
Darwin by Peter Greenaway (1993) – Although British director Peter Greenaway is best known for feature films like The Cook, the Thief, His Wife and Her Lover, Prospero’s Books, and The Pillow Book, he has also completed several highly respected projects for television, including this 53-minute exploration (now free) of the life and work of Charles Darwin. Darwin is structured around 18 separate tableaux, each focusing on another chapter in the naturalist’s life, and each consisting of just one long uninterrupted shot. Other than the narrator’s voice-over, there is no dialogue.
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