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Jeremy England, a 31-year-old assistant professor at the Massachusetts Institute of Technology, has derived a mathematical formula that he believes explains this capacity. The formula, based on established physics, indicates that when a group of atoms is driven by an external source of energy (like the sun or chemical fuel) and surrounded by a heat bath (like the ocean or atmosphere), it will often gradually restructure itself in order to dissipate increasingly more energy. This could mean that under certain conditions, matter inexorably acquires the key physical attribute associated with life. The simulation results made me think of Jojo's attempts to make a self-assembling space structure. Seems he may have been on the right track, just not thinking big enough

:-P Thanks Thijs... I do not agree with the premise of the article that a possible correlation of energy dissipation in living systems and their fitness means that one is the cause for the other - it may just be that both go hand-in-hand because of the nature of the world that we live in. Maybe there is such a drive for pre-biotic systems (like crystals and amino acids), but once life as we know it exists (i.e., heredity + mutation) it is hard to see the need for an amendment of Darwin's principles. The following just misses the essence of Darwin: "If England's approach stands up to more testing, it could further liberate biologists from seeking a Darwinian explanation for every adaptation and allow them to think more generally in terms of dissipation-driven organization. They might find, for example, that "the reason that an organism shows characteristic X rather than Y may not be because X is more fit than Y, but because physical constraints make it easier for X to evolve than for Y to evolve." Darwin's principle in its simplest expression just says that if a genome is more effective at reproducing it is more likely to dominate the next generation. The beauty of it is that there is NO need for a steering mechanism (like maximize energy dissipation) any random set of mutations will still lead to an increase of reproductive effectiveness. BTW: what does "better at dissipating energy" even mean? If I run around all the time I will have more babies? Most species that prove to be very successful end up being very good at conserving energy: trees, turtles, worms. Even complexity of an organism is not a recipe for evolutionary success: jellyfish have been successful for hundreds of millions of years while polar bears are seem to be on the way out.

for the ACT architects .... Can we do the same for the Moon Village? We brainstorm on some mathematical simplified objectives for growing the settlement (taking inputs from the modular growth, resources, terrain suitability etc ....), we define some simple rules for growth and we optimize. ..... easy peasy (i am serious)

i agree, with most of the parameters that would actually be really cool. but doesn't it get very messy once economy plays a large factor?

We can start studying the ideal case, or add also some economical constraints on the settlement layout ...

... related to the new mathematical proof of emergence of structures in random graphs.

For the Barabasi fans ...

Bartolomé call's workshop paper ... with some nice words also for the ACT "I want to congratulate the Advanced Concepts Team of the ESA and the Faculty of Mathematics and Physics of Ljubljana for this initiative." congrats Sante and Pacome again!

loads of new solution classes to the three body problem found by Bulgarians ... Francesco and Sante, you will love these

ups, should have looked at diigo before ... Luis was faster again

did you see this?

DARPA funded the development of a new computer chip that's hardwired to make simple mistakes but can help computers understand the world. Your math teacher lied to you. Sometimes getting your sums wrong is a good thing. So says Joseph Bates, cofounder and CEO of Singular Computing, a company whose computer chips are hardwired to be incapable of performing mathematical calculations correctly.

The whole concept boils down to approximate computing it seems to me. In a presentation I attended once I prospected if the same kind of philosophy could be used as a radiation hardness design approach, the short conclusion being that surely will depend on the functionality intended.

... each act member should have one, together with the mug... :) Se also http://www.youtube.com/watch?feature=player_embedded&v=y3sHTKrGdKI

I want one too! On a side note, his story about transformers is a nice illustration that being able to express something in a mathematical equation is not equivalent to understanding something.

ever heard of the Erdős-Bacon number? :-)

and actors probably ask who cares about Erdős :) The network of actors who co-star in movies is a famous one among networks people. Kevin Bacon became famous in that network because of fans of his who could from memory trace the paths of a large number of actors back to him :) see: http://en.wikipedia.org/wiki/Six_Degrees_of_Kevin_Bacon#History If you have you publications in http://academic.research.microsoft.com/, it gives you a nice tool to visualize your graph up to Erdős. Apparently I have a path of length 4, and several of length 5: http://academic.research.microsoft.com/VisualExplorer#36695545&1112639

and for the actors http://oracleofbacon.org/

paywall skipping: http://www.ncmis.cas.cn/kxcb/jclyzs/201202/W020120203526011739796.pdf

Event Horizon - a modern myth?

GR is valid on large scales and is, therefore, a simplification of the unknown GUT. As such, the mathematical solutions obtained in GR are strictly speaking valid only within GR. Certainly, the solution called black hole is an extremely heavy object and at the same time extremely small - a point without geometrical extension. The latter is heavily in conflict with the validity range of the underlying theory and, hence, makes lots of people (including experts unlike me) question the concept of black holes despite the fact that something has been "observed" which fits into this concept. Regarding the movie: Event Horizon might be a myth but it emphasizes what Sante said in on of his presentations: Don't use a black hole for travelling, take the worm hole instead. The constructor of Event Horizon created a black hole not considering that the damn thing has no exit...where did he think the Event Horizon would end?

Echoing this, in 2009 Google researchers Alon Halevy, Peter Norvig, and Fernando Pereira penned an article under the title The Unreasonable Effectiveness of Data. In it, they describe the surprising insight that given enough data, often the choice of mathematical model stops being as important - that particularly for their task of automated language translation, "simple models and a lot of data trump more elaborate models based on less data." If we make the leap and assume that this insight can be at least partially extended to fields beyond natural language processing, what we can expect is a situation in which domain knowledge is increasingly trumped by "mere" data-mining skills. I would argue that this prediction has already begun to pan-out: in a wide array of academic fields, the ability to effectively process data is superseding other more classical modes of research.

What is the best (wisest) size for a group of individuals? Couzin and Kao put together a series of mathematical models that included correlation and several cues. In one model, for example, a group of animals had to choose between two options-think of two places to find food. But the cues for each choice were not equally reliable, nor were they equally correlated. The scientists found that in these models, a group was more likely to choose the superior option than an individual. Common experience will make us expect that the bigger the group got, the wiser it would become. But they found something very different. Small groups did better than individuals. But bigger groups did not do better than small groups. In fact, they did worse. A group of 5 to 20 individuals made better decisions than an infinitely large crowd. The problem with big groups is this: a faction of the group will follow correlated cues-in other words, the cues that look the same to many individuals. If a correlated cue is misleading, it may cause the whole faction to cast the wrong vote. Couzin and Kao found that this faction can drown out the diversity of information coming from the uncorrelated cue. And this problem only gets worse as the group gets bigger.

Couzin research was the starting point that co-inspired PaGMO from the very beginning. We invited him (and he came) at a formation flying conference for a plenary here in ESTEC. You can see PaGMO as a collective problem solving simulation. In that respect, we learned already that the size of the group and its internal structure (topology) counts and cannot be too large or too random. One of the project the ACT is running (and currently seeking for new ideas/actors) is briefly described here (http://esa.github.io/pygmo/examples/example2.html) and attempts answering the question :"How is collective decision making influenced by the information flow through the group?" by looking at complex simulations of large 'archipelagos'.

Vortices in the South Atlantic are mathematically equivalent to black holes, say physicists, an idea that could lead to new ways of understanding how currents transport oil and garbage across oceans Black holes are regions of spacetime in which gravity is strong enough to prevent anything escaping, even light.

Seems looking into turbulence is a source of innovative concepts. After the black hole modelling here was found a mathematical expression which describes "how turbulence can alter the shape and course of a flock of birds, a swarm of insects or even an algal bloom (phytoplankton!) and could help us to better predict them". More relevant for motions in air and sea, rather than space, where the fluids are dense enough to exhibit turbulence ; but what about a swarm moving in and exploring an exoplanet's atmosphere?

this is how they do it :-)

But seriously, my PhD project title from now on becomes: Robotic mOdels maThematIcal Cognition (eROTIC)

your thesis title fits perfectly then ...

cheers to luca for pointing out the management one. netlogo model "demonstrating mathematically that organizations would become more efficient if they promoted people at random."

you mean "your management" at your current place?

Yes, it is not what is written? Indeed, it is already implemented. You are talking with the director of the Institute. I have been unlucky with the toss.