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Ayn Rand: Razão, Egoísmo, Capitalismo

Half-length monochrome portrait photo of Ayn Rand, seated, holding a cigarette

I am not primarily an advocate of capitalism, but of egoism; and I am not primarily an advocate of egoism, but of reason. If one recognizes the supremacy of reason and applies it consistently, all the rest follows.

[127]

    Ayn Rand

Alguns amigos meus acreditam que se possa criar uma Ética a partir da Biologia (ou melhor, dos sentimentos empáticos de um mamífero hipersocial). Outros acham que a base seria a Razão, não as emoções.  Os Objetivistas, uma espécie de seita filosófica hiperracionalista (tenho quase certeza que sua guru Ayn Rand sofria de Transtorno de Personalidade Esquizóide), acham que a primeira opção é simplesmente dar um verniz biológico à ética judaico-cristã e seus derivados seculares (onde se prioriza a cooperação em vez da competição).

Muitos amigos ateus têm me reportado que a doutrina de Rand tem se espalhado em sua comunidade via Facebook (muita gente pedindo para que “Curtir” páginas de Rand.). Muitois não percebem que Rand, via seu discípulo Alan Greenspan, foi a grande influência ideológica que nos levou à nova Grande Depressão mundial e, possivelmente, a uma nova extrema-direita anarquista estilo Tea Party. Ou seja, no ideário de Rand, temos a sequência Razão -> Egoísmo -> Capitalismo Selvagem -> Caos Social. Ou talvez a egocentrismo de Rand esteja antes desta sequência…

This article is from TOS Vol. 3, No. 3. The full contents of the issue are listed here.

The Mystical Ethics of the New Atheists

Alan Germani

In the wake of the religiously motivated atrocities of 9/11, Sam Harris, Daniel Dennett, Richard Dawkins, and Christopher Hitchens have penned best-selling books in which they condemn religious belief as destructive to human life and as lacking any basis in reality.* On the premise that religious belief as such leads to atrocities, the “New Atheists,” as these four have come to be known, criticize religion as invalid, mind-thwarting, self-perpetuating, and deadly. As Sam Harris puts it: “Because each new generation of children is taught that religious propositions need not be justified in the way that others must, civilization is still besieged by the armies of the preposterous. We are, even now, killing ourselves over ancient literature. Who would have thought something so tragically absurd could be possible?”1 Read more [+]

Linguagens esfriam enquanto expandem…

 

 Languages cool as they expand: Allometric scaling and the decreasing need for new words

 

Alexander M. PetersenJoel N. TenenbaumShlomo HavlinH. Eugene StanleyMatjaz Perc
(Submitted on 11 Dec 2012)

We analyze the occurrence frequencies of over 15 million words recorded in millions of books published during the past two centuries in seven different languages. For all languages and chronological subsets of the data we confirm that two scaling regimes characterize the word frequency distributions, with only the more common words obeying the classic Zipf law. Using corpora of unprecedented size, we test the allometric scaling relation between the corpus size and the vocabulary size of growing languages to demonstrate a decreasing marginal need for new words, a feature that is likely related to the underlying correlations between words. We calculate the annual growth fluctuations of word use which has a decreasing trend as the corpus size increases, indicating a slowdown in linguistic evolution following language expansion. This “cooling pattern” forms the basis of a third statistical regularity, which unlike the Zipf and the Heaps law, is dynamical in nature.

Comments: 9 two-column pages, 7 figures; accepted for publication in Scientific Reports
Subjects: Physics and Society (physics.soc-ph); Statistical Mechanics (cond-mat.stat-mech); Computation and Language (cs.CL); Applications (stat.AP)
Journal reference: Sci. Rep. 2 (2012) 943
DOI: 10.1038/srep00943
Cite as: arXiv:1212.2616 [physics.soc-ph]
(or arXiv:1212.2616v1 [physics.soc-ph] for this version)

Submission history

Palestra no Instituto de Estudos Avançados (RP) sobre Ciência e Religião

 

sexta-feira, 9 de novembro de 2012

Ciência e Religião: quatro perspectivas

Escrito por 

Data e Horário: 26/11 às 14h30
Local: Salão de Eventos do Centro de Informática de Ribeirão Preto – CIRP/USP (localização)

O evento, que será apresentado por Osame Kinouchi, discutirá quatro diferentes visões sobre a interação entre Ciência e Religião: o conflito, a separação, o diálogo e a integração. Examinando as fontes de conflito recentes (Culture Wars), o professor sugere que elas têm origem no Romantismo Anticientífico, religioso ou laico.

Segundo Osame, a ideia de separação entre os campos Religioso e Científico já não parece ser viável devido aos avanços da Ciência em tópicos antes considerados metafísicos, tais como as origens do Universo (Cosmologia), da Vida (Astrobiologia), da Mente (Neurociências) e mesmo das Religiões (Neuroteologia, Psicologia Evolucionária e Ciências da Religião).
A palestra mostrará também que tentativas de integração forçada ou prematura entre Religião e Ciência correm o risco de derivar para a Pseudociência. Sendo assim, na visão do professor, uma posição mais acadêmica de diálogo de alto nível pode ser um antídoto para uma polarização cultural ingênua entre Ateísmo e Religiosidade.

Vídeo do evento

Islamismo com Twitter (I)

Me pareceu uma análise realista e intrigante:

Tecnologia da desinformação

Por Redação Link

Protestos contra vídeo sobre Maomé revelam que a fé do Oriente e os valores do Ocidente estão em conflito em uma praça pública global

Nathan Gardels, do Global Viewpoint*


“Esta praça pública global é o novo espaço de poder onde imagens competem e ideias são contestadas”. FOTO: Khalil Hamra/AP

Os fatos dos últimos dias no Oriente Médio são apenas um alerta para futuros distúrbios à medida que a democratização da mídia no Ocidente se depara com o despertar político no mundo árabe.

—-
• Siga o ‘Link’ no Twitter, no Facebook, no Google+ no Tumblr e no Instagram

Os hoje marginalizados jovens do Facebook podem ter iniciado a Primavera Árabe, que desencadeou – alguns diriam “libertou” – vozes contrárias ao Ocidente e que durante muito tempo foram caladas por autocratas brutais. Mas agora é a vez do YouTube agitar a região. O trailer de um filme chamado A Inocência dos Muçulmanos colocou a região em chamas à medida que o filme se propaga na internet.

Bem-vindo ao nosso novo mundo, onde ninguém pode ser controlado – nem o Ocidente controla sua mídia social, tampouco os dirigentes árabes têm controle dos seus cidadãos libertados. Uma combinação inflamável. Read more [+]

Probabilidade de ocorrer um evento maior que o “11 de setembro” ultrapassa os 95%

Statisticians Calculate Probability Of Another 9/11 Attack

According to the statistics, there is a 50 per cent chance of another catastrophic terrorist attack within the next ten years

3 comments

THE PHYSICS ARXIV BLOG

Wednesday, September 5, 2012

Earthquakes are seemingly random events that are hard to predict with any reasonable accuracy. And yet geologists make very specific long term forecasts that can help to dramatically reduce the number of fatalities.

For example, the death toll from earthquakes in the developed world, in places such as Japan and New Zealand, would have been vastly greater were it not for strict building regulations enforced on the back of well-founded predictions that big earthquakes were likely in future.

The problem with earthquakes is that they follow a power law distribution–small earthquakes are common and large earthquakes very rare but the difference in their power is many orders of magnitude.

Humans have a hard time dealing intuitively with these kinds of statistics. But in the last few decades statisticians have learnt how to handle them, provided that they have a reasonable body of statistical evidence to go on.

That’s made it possible to make predictions about all kinds of phenomena governed by power laws, everything from earthquakes, forest fires and avalanches to epidemics, the volume of email and even the spread of rumours.

So it shouldn’t come as much of a surprise that Aaron Clauset at the Santa Fe Institute in New Mexico and Ryan Woodard at ETH, the Swiss Federal Institute of Technology, in Zurich have used this approach to study the likelihood of terrorist attacks.  Read more [+]

Física Estatística de eleições

Multimode Control Attacks on Elections

(Submitted on 11 Jul 2010)

In 1992, Bartholdi, Tovey, and Trick opened the study of control attacks on elections—attempts to improve the election outcome by such actions as adding/deleting candidates or voters. That work has led to many results on how algorithms can be used to find attacks on elections and how complexity-theoretic hardness results can be used as shields against attacks. However, all the work in this line has assumed that the attacker employs just a single type of attack. In this paper, we model and study the case in which the attacker launches a multipronged (i.e., multimode) attack. We do so to more realistically capture the richness of real-life settings. For example, an attacker might simultaneously try to suppress some voters, attract new voters into the election, and introduce a spoiler candidate. Our model provides a unified framework for such varied attacks, and by constructing polynomial-time multiprong attack algorithms we prove that for various election systems even such concerted, flexible attacks can be perfectly planned in deterministic polynomial time.

Comments: 41 pages, 2 tables
Subjects: Computer Science and Game Theory (cs.GT); Computational Complexity (cs.CC); Data Structures and Algorithms (cs.DS); Multiagent Systems (cs.MA)
ACM classes: I.2.11; F.2.2; F.1.3
Report number: URCS TR-2010-960
Cite as: arXiv:1007.1800v1 [cs.GT]

Local ePolitics Reputation Case Study

(Submitted on 11 Feb 2010)

More and more people rely on Web information and with the advance of Web 2.0 technologies they can increasingly easily participate to the creation of this information. Country-level politicians could not ignore this trend and have started to use the Web to promote them or to demote their opponents. This paper presents how candidates to a French mayor local election and with less budget have engineered their Web campaign and online reputation. After presenting the settings of the local election, the Web tools used by the different candidates and the local journalists are detailed. These tools are evaluated from a security point of view and the legal issues that they have created are underlined.

Comments: Published in the Proceedings of the IADIS 2009 e-Society International Conference
Subjects: Computers and Society (cs.CY)
Cite as: arXiv:1002.2297v1 [cs.CY]

Físicos explicam porque existem paradigmas e revoluções científicas de Kuhn

Por que a maior parte dos blogueiros de ciência e céticos são Popperianos? Kuhn é muito melhor, e pode ser modelado pela sociophysics…

Highly connected – a recipe for success

Authors: Krzysztof Suchecki, Andrea Scharnhorst, Janusz A. Holyst
(Submitted on 5 Jul 2010 (v1), last revised 6 Jul 2010 (this version, v2))

Abstract: In this paper, we tackle the problem of innovation spreading from a modeling point of view. We consider a networked system of individuals, with a competition between two groups. We show its relation to the innovation spreading issues. We introduce an abstract model and show how it can be interpreted in this framework, as well as what conclusions we can draw form it. We further explain how model-derived conclusions can help to investigate the original problem, as well as other, similar problems. The model is an agent-based model assuming simple binary attributes of those agents. It uses a majority dynamics (Ising model to be exact), meaning that individuals attempt to be similar to the majority of their peers, barring the occasional purely individual decisions that are modeled as random. We show that this simplistic model can be related to the decision-making during innovation adoption processes. The majority dynamics for the model mean that when a dominant attribute, representing an existing practice or solution, is already established, it will persists in the system. We show however, that in a two group competition, a smaller group that represents innovation users can still convince the larger group, if it has high self-support. We argue that this conclusion, while drawn from a simple model, can be applied to real cases of innovation spreading. We also show that the model could be interpreted in different ways, allowing different problems to profit from our conclusions.
Comments: 36 pages, including 5 figures; for electronic journal revised to fix missing co-author
Subjects: Physics and Society (physics.soc-ph)
Cite as: arXiv:1007.0671v2 [physics.soc-ph]

Manipulação e contrlole de eleições

The Shield that Never Was: Societies with Single-Peaked Preferences are More Open to Manipulation and Control

P. FaliszewskiE. HemaspaandraL. A. HemaspaandraJ. Rothe
(Submitted on 17 Sep 2009 (v1), last revised 19 Jun 2010 (this version, v2))

Much work has been devoted, during the past twenty years, to using complexity to protect elections from manipulation and control. Many results have been obtained showing NP-hardness shields, and recently there has been much focus on whether such worst-case hardness protections can be bypassed by frequently correct heuristics or by approximations. This paper takes a very different approach: We argue that when electorates follow the canonical political science model of societal preferences the complexity shield never existed in the first place. In particular, we show that for electorates having single-peaked preferences, many existing NP-hardness results on manipulation and control evaporate.

Comments: 38 pages, 2 figures
Subjects: Computer Science and Game Theory (cs.GT); Computational Complexity (cs.CC); Multiagent Systems (cs.MA); Physics and Society (physics.soc-ph)
ACM classes: I.2.11; F.2.2; F.1.3
Report number: URCS TR-2009-950
Cite as: arXiv:0909.3257v2 [cs.GT]

Futebol computacional


Eu duvido que esses modelos Poissonianos funcionem, mas fica 
como referencia: 

http://arxiv.org/abs/1004.2003 
The Socceral Force 

Norbert Bátfai 
(Submitted on 12 Apr 2010 (v1), last revised 22 Apr 2010 (this 
version, v2)) 
We have an audacious dream, we would like to develop a 
simulation and virtual reality system to support the decision 
making in European football (soccer). In this review, we 
summarize the efforts that we have made to fulfil this dream 
until recently. In addition, an introductory version of FerSML 
(Footballer and Football Simulation Markup Language) is 
presented in this paper. 
Comments: 20 pages, 13 figures, added FerSML 0.0.2 
Subjects: Artificial Intelligence (cs.AI); Software 
Engineering (cs.SE) 
MSC classes: 68T35 
ACM classes: H.5.1 
Cite as: arXiv:1004.2003v2 [cs.AI] 

http://arxiv.org/abs/1002.0797 
Soccer: is scoring goals a predictable Poissonian process? 

Andreas Heuer, Christian Mueller, Oliver Rubner 
(Submitted on 3 Feb 2010 (v1), last revised 3 Mar 2010 (this 
version, v2)) 
The non-scientific event of a soccer match is analysed on a 
strictly scientific level. The analysis is based on the 
recently introduced concept of a team fitness (Eur. Phys. J. B 
67, 445, 2009) and requires the use of finite-size scaling. A 
uniquely defined function is derived which quantitatively 
predicts the expected average outcome of a soccer match in 
terms of the fitness of both teams. It is checked whether 
temporary fitness fluctuations of a team hamper the 
predictability of a soccer match. 
To a very good approximation scoring goals during a match can 
be characterized as independent Poissonian processes with pre- 
determined expectation values. Minor correlations give rise to 
an increase of the number of draws. The non-Poissonian overall 
goal distribution is just a consequence of the fitness 
distribution among different teams. The limits of 
predictability of soccer matches are quantified. Our model-free 
classification of the underlying ingredients determining the 
outcome of soccer matches can be generalized to different types 
of sports events. 
Subjects: Data Analysis, Statistics and Probability 
(physics.data-an); Physics and Society (physics.soc-ph) 
Journal reference: Europhys. Lett. 89 (2010) 38007 
DOI: 10.1209/0295-5075/89/38007 
Cite as: arXiv:1002.0797v2 [physics.data-an] 

http://arxiv.org/abs/0909.4555 
Soccer matches as experiments: how often does the ‘best’ team 
win? 

G. K. Skinner, G. H. Freeman 
(Submitted on 24 Sep 2009) 
Models in which the number of goals scored by a team in a 
soccer match follow a Poisson distribution, or a closely 
related one, have been widely discussed. We here consider a 
soccer match as an experiment to assess which of two teams is 
superior and examine the probability that the outcome of the 
experiment (match) truly represents the relative abilities of 
the two teams. Given a final score, it is possible by using a 
Bayesian approach to quantify the probability that it was or 
was not the case that ‘the best team won’. For typical scores, 
the probability of a misleading result is significant. 
Modifying the rules of the game to increase the typical number 
of goals scored would improve the situation, but a level of 
confidence that would normally be regarded as satisfactory 
could not be obtained unless the character of the game was 
radically changed. 
Comments: Contact the corresponding author in case of 
difficulty in accessing the published paper 
Subjects: Physics and Society (physics.soc-ph); Data 
Analysis, Statistics and Probability (physics.data-an); 
Applications (stat.AP) 
Journal reference: Journal of Applied Statistics Vol. 36, 
No. 10, October 2009, 1087-1095 
DOI: 10.1080/02664760802715922 
Cite as: arXiv:0909.4555v1 [physics.soc-ph] 

http://arxiv.org/abs/0803.0614 
Fitness, chance, and myths: an objective view on soccer results 

Andreas Heuer, Oliver Rubner 
(Submitted on 5 Mar 2008 (v1), last revised 20 Mar 2009 (this 
version, v4)) 
We analyze the time series of soccer matches in a model-free 
way using data for the German soccer league (Bundesliga). We 
argue that the goal difference is a better measure for the 
overall fitness of a team than the number of points. It is 
shown that the time evolution of the table during a season can 
be interpreted as a random walk with an underlying constant 
drift. Variations of the overall fitness mainly occur during 
the summer break but not during a season. The fitness 
correlation shows a long-time decay on the scale of a quarter 
century. Some typical soccer myths are analyzed in detail. It 
is shown that losing but no winning streaks exist. For this 
analysis ideas from multidimensional NMR experiments have been 
borrowed. Furthermore, beyond the general home advantage there 
is no statistically relevant indication of a team-specific home 
fitness. Based on these insights a framework for a statistical 
characterization of the results of a soccer league is 
introduced and some general consequences for the prediction of 
soccer results are formulated. 
Comments: tex-file, 31 pages,16 figures 
Subjects: Data Analysis, Statistics and Probability 
(physics.data-an); Physics and Society (physics.soc-ph) 
DOI: 10.1140/epjb/e2009-00024-8 
Cite as: arXiv:0803.0614v4 [physics.data-an] 

Americanos revolucionam futebol

Em termos de esportes, é bem conhecida a fascinação dos americanos por estatísticas. Neste blog do New York Times você pode encontrar dados estatísticos minuto a minuto das partidas da Copa.  Muito interessante… para um físico estatístico.
Idéia para um paper: claramente as estatísticas para intervalos entre posse de bola, chutes a gol, escanteios e faltas não seguem uma distribuição de Poisson, mas lembram uma distribuição com lei de potência (com cut-off de 45 min, claro!) ou talvez uma log-normal. Para um exemplo, veja as estatísticas do jogo Uruguai vs França aqui. Dá para entender algo disso: a probabilidade de um escanteio seguir outro é alta e, quando um time está pressionando outro, os chutes a gol podem sair em sequência (não está claro a origem da distribuição não uniforme de faltas).
Na verdade, existem boas razões para se acreditar que o jogo de futebol não é Markoviano nem estacionário. Mas então, seria possível modelar (gerar) essas distribuições de modo simples?
Idéia: Coletar estatísticas desse blog (usando o Match Analysis?) e mostrar que essas distribuções não são Poisson. Daí propor um modelo que gere essas distribuições.

História da sociofísica III

Sociophysics http://www.eoht.info/page/Sociophysics

In science, sociophysics is the study of social phenomena from a physics perspective. The subject seems to deal with thermodynamics in part; albeit, the majority of theories in this field seem to be on statistical extrapolations or phase transition models.

A noted researcher in the field is physicist Serge Galam claims that he has been in the field of sociophysics since the late 1970s. [1] A noted researcher in this field is Canadian political scientist Paris Arnopoulos and his 1993 book Sociophysics, in which he speculates on heat, pressure, temperature, entropy, and volumes of societies. [3]

At the 2008 international workshop on socio physics, at Torino, Italy, the focus was on the statistical physics modeling of large scale social phenomena, such as opinion formation, cultural dissemination, the origin and evolution of language, crowd behavior, social contagion; where it was stated that previous years had witnessed the attempt to study collective phenomena emerging from the interactions of individuals as elementary units in social structures. The workshop worked to promote effective cooperation between physicists and social scientists. [2]

See also

Social physics

Social chemistry

Socio-thermodynamics

Sociological thermodynamics

References1. Galam, Serge. (2004). “Sociophysics: a Personal Testimony.”, Laboratory of Heterogeneous and Disorderly Environments, Paris. Arxiv.org.

2. Sociophysics – International Workshop, ISI Foundation, Torino, Italy, 26-29 May 2008.

3. Arnopoulos, Paris. (2005). Sociophysics: Cosmos and Chaos in Nature and Culture (thermics, pgs. 26-31). Nova Publishers, 1993 first edition.

Further reading

● Chakrabarti, Bikas K. Chakraborti, Anirban, and Chatterjee, Arnab. (2006). Econophysics and Sociophysics: Trends and Perspectives. Wiley-VCH.

Psicohistória e Sociofísica

É uma estranha coincidência que o livro de Charles Galton Darwin (The Next Million Years) tenha surgido quase simultaneamente com o clássico Fundação de Isaac asimov. Será que houve influência mútua?
Update: Parece que Darwin leu Asimov, pois os contos foram publicados a partir de 1942:
Foundation was originally a series of eight short stories published in Astounding Magazine between May 1942 and January 1950. According to Asimov, the premise was based on ideas set forth in Edward Gibbon‘s History of the Decline and Fall of the Roman Empire, and was invented spontaneously on his way to meet with editor John W. Campbell, with whom he developed the concept.[2]
Original trilogy
The first four stories were collected, along with a new story taking place before the others, in a single volume published by Gnome Press in 1951 as Foundation. The remainder of the stories were published in pairs as Foundation and Empire (1952) and Second Foundation (1953), resulting in the “Foundation Trilogy”, as the series was known for decades.[3]
Later sequels
In 1981, after the series had long been considered one of the most important works of modern science fiction,[1] Asimov was persuaded by his publishers to write a fourth book, which became Foundation’s Edge (1982).[4]
Two years later, Asimov followed up with yet another sequel, Foundation and Earth (1983), and five years later, the prequels Prelude to Foundation and Forward the Foundation. During the lapse between writing the sequels and prequels, Asimov tied in his Foundation series with his various other series, creating a single unified universe of his best-known works.
Psychohistory (fictional)

From Wikipedia, the free encyclopedia

For the study of the psychological motivation of historical and current events, see psychohistory.
Psychohistory, a fictional science in Isaac Asimov‘s Foundation universe, combines history, sociology, and mathematical statistics to make (nearly) exact predictions of the collective actions of very large groups of people, such as the Galactic Empire.

Contents

1 Axioms
2 The Prime Radiant
3 Development
4 Limitations
5 Asimov on psychohistory
6 Asimovian psychohistory and similar concepts in other fiction
7 Beyond fiction
8 In role-playing games
9 Literary influences
10 See also
11 Notes and references
12 External links

Axioms

Psychohistory depends on the idea that, while one cannot foresee the actions of a particular individual, the laws of statistics as applied to large groups of people could predict the general flow of future events. Asimov used the analogy of a gas: an observer has great difficulty in predicting the motion of a single molecule in a gas, but can predict the mass action of the gas to a high level of accuracy. (Physicists know this as the Kinetic theory.) Asimov applied this concept to the population of his fictional Galactic Empire, which numbered a quintillion. The character responsible for the science’s creation, Hari Seldon, established two axioms:

  • that the population whose behaviour was modeled should be sufficiently large ;
  • that the population should remain in ignorance of the results of the application of psychohistorical analyses

There is a third underlying axiom of Psychohistory, which is trivial and thus not stated by Seldon in his Plan:

  • that Human Beings are the only sentient intelligence in the Galaxy.

Econofísica prevê estouro de bolha no IBOVESPA

A recente queda do IBOVESPA de 19.9% desde seu record histórico foi prevista por Didier Sornette?

Wednesday, June 02, 2010

Econophysicist Accurately Forecasts Gold Price Collapse


The first results from the Financial Bubble Experiment will have huge implications for econophysics

There are good reasons to think that stock markets are fundamentally unpredictable. Many econophysicists believe for example, that the data from these markets bear a startling resemblance to other data from seemingly unconnected phenomena, such as the size of earthquakes, forest fires and avalanches, which defy all efforts of prediction. 

Some go as far as to say that these phenomena are governed by the same fundamental laws so that if one is unpredictable, then they all are. 
And yet financial markets may be different. Last year, this blog covered an extraordinary forecasts made by Didier Sornette at the Swiss Federal Institute of Technology in Zurich, who declared that the Shanghia Composite Index was a bubble market and that it would collapse within a certain specific period of time.
Much to this blog’s surprise, his prediction turned out to be uncannily correct.
Sornette says there are two parts to his forecasting method. First, he says bubbles are markets experiencing greater-then-exponential growth. That makes them straightforward to spot, something that surprisingly hasn’t been possible before. 
Second, he says these bubble markets display the tell signs of the human behaviour that drives them. In particular, people tend to follow each other and this result in a kind of herding behaviour that causes prices to fluctuate in a periodic fashion. 
However, the frequency of these fluctuations increases rapidly as the bubble comes closer to bursting. It’s this signal that Sornette uses in predicting a change from superexponential growth to some other regime (which may not necessarily be a collapse).
While Sornette’s success last year was remarkable it wasn’t entirely convincing as this blog pointed out at the time
“The problem with this kind of forecast is that it is difficult interpret the results. Does it really back Sornette’s hypothesis that crashes are predictable? How do we know that he doesn’t make these predictions on a regular basis and only publicise the ones that come true? Or perhaps he modifies them as the due date gets closer so that they always seem to be right (as weather forecasters do). It’s even possible that his predictions influence the markets: perhaps they trigger crashes Sornette believes he can spot.”
That’s when Sornette announced an brave way of test his forecasting method which he calls the Financial Bubble Experiment. His idea is to make a forecast but keep it secret. He posts it in encrypted form to the arXiv which time stamps it and ensures that no changes can be made.
Then, six months later, he reveals the forecast and analyses how successful it has been. 
Today, we can finally see the analysis of his first set of predictions made 6 months ago.
Back then, Sornette and his team identified four markets that seemed to be experiencing superexponential growth and the tell tale signs of an imminent bubble burst.
These were:the IBOVESPA Index of 50 brazillian stocks, a Merrill Lynch Corporate Bond Indexthe spot price of goldcotton futures
These predictions had mixed success. First let’s look at the failures. Sornette says that it now turns out that the Merill Lynch Index was in the process of collapse when Sornette made the original prediction six months ago. So that bubble burst long before Sornette said it would. And cotton futures are still climbing in a bubble market that has yet to collapse. So much for those forecasts.
However, Sornette and his team were spot on with their other predictions. Both the IBOVESPA Index and the spot price of gold changed from superexponential growth to some other kind of regime in the time frame that Sornette predicted. That’s an impressive result by anybody’s standards.
And the team says it can do better. They point out that they learnt a substantial amount during the first six months of the experiment. They have used this experience to develop a tool called a “bubble index” which they can use to determine the probability that a market that looks like a bubble actually is one. 
This should help to make future forecasts even more accurate. Had this tool been available six months ago, for example, it would have clearly showed that the Merrill Lynch index had already burst, they say. If Sornette continues with this type of success it’s likely that others will want to copy his method. An interesting question is what will happen to the tell tale herding behaviour once large numbers of analysts start looking for and betting on it.
It’s tempting to imagine that this extra information would have a calming effect on otherwise volatile markets. But the real worry is that it could have exactly the opposite effect: that predictions of the imminent collapse whether accurate or not would lead to violent corrections. That will have big implications for econophysics and those who practice it. 
Either way, Sornette is continuing with the experiment. He has already sealed his set of predictions for the next six months and will reveal them on 1 November. We’ll be watching. 
The Financial Bubble Experiment: Advanced Diagnostics and Forecasts of Bubble Terminations Volume I

História da sociofísica II

The Next Million Years

In famous publication, The Next Million Years is a 1952 book written by C.G. Darwin notable as being the first-ever published document outlining a theory using the terms “human thermodynamics” and “human molecule” in unison. [1] Original copies sell for as much as $395 dollars. The book was reprinted in 1953 and 1973. The Next Million Years is one of the founding books in the history of human thermodynamics.

OverviewIn short, Darwin argued that humans were molecules, that assemblies of humans constituted “conservative dynamical systems”, and that one could use statistical thermodynamics, particularly American mathematical physicist Willard Gibbs version of it, to predict the course of the next million years of human evolution. In his book, according to a 1953 review by Time magazine, Darwin, a theoretical physicist, invades sociological territory where many sociologists fear to tread. [2] He bases his reasoning about man’s future on what is sometimes called “social physics“: the idea that the behavior of humans in very large numbers can be predicted by the statistical methods that physicists use with large numbers of molecules. Accordingly, in the gas phase, the motions of single molecules are unpredictable: they may move fast or slow and zigzag in any direction, but the impacts of billions of gas molecules against a restraining surface produce a steady push that obeys definite and rather simple laws. In the same manner, Darwin believes, the actions of individual humans are erratic and sometimes remarkable, but the behavior of large numbers of them over long periods of time is as predictable as the pressure of gas. All that is needed is to determine the basic, averaged-out properties of humanmolecules.”

In Darwin’s view, according to the review, “human molecules have one fundamental property that dominates all others: they tend to increase their numbers up to the absolute limit of their food supply”. [2]

References

1. Darwin, Charles G. (1952). The Next Million Years (chapter one). London: Rupert Hart-Davis.

2. Staff Writer. (1953). “Million-Year Prophecy”. Time, Monday, Jan. 19.

Further reading

● Jessop, Brent. (2008). “A Darwin’s Look into The Next Million Years” (four part review), March 3. Knowledge Driven Revolution.com

● Bates, Marson. (1954). “Reviewed work: The Next Million Years by Charles G. Darwin.” American Anthropologist, New Series, Vol. 56, No. 2, Part. 1. Apr. pg. 337.

História da sociofísica I

Social physics

In science, social physics is the study of social systems and social phenomena from the perspective of physics.

History

The term social physics was first introduced by Belgian statistician Adolphe Quetelet in his 1835 book Essay on Social Physics: Man and the Development of his Faculties, in which he outlines the project of a social physics and describes his concept of the “average man” (l’homme moyen) who is characterized by the mean values of measured variables that follow a normal distribution and collects data about many such variables. [5]

When French social philosopher Auguste Comte, who had also used the term social physics, in his 1842 work, discovered that Quetelet had appropriated the term ‘social physics’ prior to him, Comte found it necessary to invent the term ‘sociologie’ (sociology) because he disagreed with Quetelet’s collection of statistics.

Comte defined social physics as the study of the laws of society or the science of civilization. [1] Specifically, in part six of series of books, written between 1830 and 1842, on the subject of Positive Philosophy, Comte argued that social physics would complete the scientific description of the world that Galileo, Newton, and others had begun: [4] “Now that the human mind has grasped celestial and terrestrial physics, mechanical and chemical, organic physics, both vegetable and animal, there remains one science, to fill up the series of sciences or observation—social physics. This is what men have now most need of; and this it is the principal aim of the present work to establish.”

In the opening page to his Social Physics, Comte gives the following situation: “The theories of social science are still, even in the minds of the best thinkers, completely implicated with the theologico-metaphysical philosophy (which he says is ‘in a state of imbecility’); and are even supposed to be, by a fatal separation from all other science, condemned to remain so involved forever.” It is interesting, how in the year 2010, the same dogmatic view remains.

In recent years, building on the development of the kinetic theory of gases (1859) and statistical mechanics (1872), founded during the last half of the 19th century, some authors have begun to incorporate a statistical thermodynamic perspective in models of social physics in which people are viewed as atoms or molecules (human molecules) such that the law of large numbers yields social behaviors such as, for instance, the 80-20 rule, wherein, typically, 80 percent of a country’s wealth is distributed among 20 percent of the population. [2]

Implications

When one applies statistical thought or the “logic of large numbers” to society, according to English chemist and physicist Philip Ball, the concept of human free will is the first question in the minds of those encountering the new “physics of society” for the first time. The debate on this topic, according to Ball, began to rage in the 19th century and still preoccupies sociologists today. [3]

See also

Social thermodynamics

Sociological thermodynamics

Socio-thermodynamics

Social atom

Social bond

Sociophysics

Social pressure

Social temperature

References

1. (a) Ball, Philip. (2004). Critical Mass – How One Things Leads to Another, (pg. 58). New York: Farrar, Straus and Giroux.(b) Nisbet, Robert A. (1970). The Social Bond – an Introduction to the Study of Society, (pg. 29). New York: Alfred A Knopf.

2. Buchanan, Mark. (2007). The Social Atom – why the Rich get Richer, Cheaters get Caught, and Your Neighbor Usually Looks Like You, (pgs. x-xi). New York: Bloomsbury.

3. Ball, Philip. (2004). Critical Mass – How One Things Leads to Another (pgs. 71-72). New York: Farrar, Straus and Giroux.

4. Comte, Auguste. (1856). Social Physics: from the Positive Philosophy. New York: Calvin Blanchard.

5. (a) Quetelet, Adolphe. (1835). Essay on Social Physics: Man and the Development of his Faculties (Sur l’homme et le Développement de ses Facultés, ou Essai de Physique Sociale, Vol. 1, Vol. 2). Paris: Imprimeur-Libraire.

(b) Quetelet, Adolphe. (1842). Treatise on Man: and the Development of His Faculties. Ayer Publishing. Further reading

● Foley, Vernard. (1976). The Social Physics of Adam Smith (thermodynamics, pgs. 191-94; entropy, pg. 199). Purdue University Press.

● Iberall, A.S. (1985). “Outlining Social Physics for Modern Societies: Locating Cultures, Economics, and Politics: the Enlightenment Reconsidered.” (abstract), Proc Natl Acad Sci USA, 82(17): 5582-84.

● Mirowski, Philip. (1989). More Heat than Light: Economics as Social Physics, Physics as Nature’s Economics. Cambridge University Press.

● Urry, John. (2004). “Small Worlds and the New ‘Social Physics’,” (html) (abstract) Global Networks, 4(2): 109-30. External links

Physics of Society – A collection of articles by English chemist and physicst Phillip Ball.

Novas metáforas físicas em Economia


Parodiando Engels, “todo economista vivo é escravo de um físico morto”. A questão não é se novas idéias e conceitos físicos podem ser aplicados às ciências econômicas e sociais, mas por que os velhos conceitos da física newtoniana (“equilíbrio”, “forças” econômicas, “tensão” social etc.) permanecem no discurso sócio-econômico.

The (unfortunate) complexity of the economy

Jean-Philippe Bouchaud
(Submitted on 6 Apr 2009)

This article is a follow-up of a short essay that appeared in Nature 455, 1181 (2008) [arXiv:0810.5306]. It has become increasingly clear that the erratic dynamics of markets is mostly endogenous and not due to the rational processing of exogenous news. I elaborate on the idea that spin-glass type of problems, where the combination of competition and heterogeneities generically leads to long epochs of statis interrupted by crises and hyper-sensitivity to small changes of the environment, could be metaphors for the complexity of economic systems. I argue that the most valuable contribution of physics to economics might end up being of methodological nature, and that simple models from physics and agent based numerical simulations, although highly stylized, are more realistic than the traditional models of economics that assume rational agents with infinite foresight and infinite computing abilities.

Subjects: General Finance (q-fin.GN); Physics and Society (physics.soc-ph)
Journal reference: Physics World, April 2009, p.28-32
Cite as: arXiv:0904.0805v1 [q-fin.GN]

Publicaram antes a minha idéia (e a do Dante Chialvo tamém)!

Quando Tiago estava trabalhando em seu mestrado, ele veio para a LASCON – Latin American School of Computational Neuroscience, em julho de 2008. Na cantina do Walter, Roque lembra que discutimos a questão do subsampling em sistemas críticos (inclusive com esta palavra). Sugeri ao Tiago que fizesse uma simulação em um sistema simples (por exemplo, a rede aleatória excitável que Mauro e eu trabalhamos em 2006, o modelo OFC (que tem relações com modelos de neurônios integra dispara) ou mesmo um modelo de pilha de areia tradicional.
Alguns meses mais tarde, Chialvo deu a mesma idéia para Tiago e Mauro (e fez questão de anotar em um guardanapo a a idéia, a data e as pessoas presentes, e pediu para todos assinarem!). Não sei se ele usou a palavra subsampling, acredito que sim. Desta vez, Tiago acreditou na idéia (o meu problema é que santo de casa não faz milagre…) e fez as simulações. Batata: subsampling em sistemas críticos gera distribuições que fogem às leis de potência, ficam mais parecidas com log-normais ou exponenciais extendidas.
Mas como o mérito é de quem publica primeiro… acho que Tiago, Mauro, Sidarta, Nicolelis, Chialvo e eu ficamos chupando o dedo… E o duro é que nem houve uma citaçãozinha (por exemplo, sobre o uso do parâmetro de branching sigma em modelos de SOC, acho que a Carmem Prado e eu fomos uns dos primeiros a explorar isso consistentemente (ou pelo menos popularizamos essa idéia…). Bom, é claro que tudo se esclarece com Vespignani, Zapperi, Dickman e outros, por exemplo neste belissimo paper com delicioso título:

How self-organized criticality works: A unified mean-field picture

Saiu no BMC:

Subsampling effects in neuronal avalanche distributions recorded in vivo

Viola Priesemann1,2 email, Matthias HJ Munk3 email and Michael Wibral4 email

1Department of Neurophysiology, Max Planck Institute for Brain Research, Deutschordenstrasse 46, D-60528 Frankfurt am Main, Germany

2Group for Neural Theory, DEC, Ecole Normale Supérieure, Collège de France, 3, rue d’Ulm, 75005 Paris, France

3Deptartment of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Spemannstrasse 38, D-72076 Tübingen, Germany

4MEG Unit, Brain Imaging Centre, J.W. Goethe University, Heinrich Hoffmann Strasse 10, D-60528 Frankfurt am Main, Germany

author email corresponding author email

BMC Neuroscience 2009, 10:40doi:10.1186/1471-2202-10-40

The electronic version of this article is the complete one and can be found online at:http://www.biomedcentral.com/1471-2202/10/40

Received: 1 October 2008
Accepted: 29 April 2009
Published: 29 April 2009

© 2009 Priesemann et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Many systems in nature are characterized by complex behaviour where large cascades of events, or avalanches, unpredictably alternate with periods of little activity. Snow avalanches are an example. Often the size distribution f(s) of a system’s avalanches follows a power law, and the branching parameter sigma, the average number of events triggered by a single preceding event, is unity. A power law for f(s), and sigma = 1, are hallmark features of self-organized critical (SOC) systems, and both have been found for neuronal activity in vitro. Therefore, and since SOC systems and neuronal activity both show large variability, long-term stability and memory capabilities, SOC has been proposed to govern neuronal dynamics in vivo. Testing this hypothesis is difficult because neuronal activity is spatially or temporally subsampled, while theories of SOC systems assume full sampling. To close this gap, we investigated how subsampling affects f(s) and sigma by imposing subsampling on three different SOC models. We then compared f(s) and sigma of the subsampled models with those of multielectrode local field potential (LFP) activity recorded in three macaque monkeys performing a short term memory task.

Results

Neither the LFP nor the subsampled SOC models showed a power law for f(s). Both, f(s) and sigma, depended sensitively on the subsampling geometry and the dynamics of the model. Only one of the SOC models, the Abelian Sandpile Model, exhibited f(s) and sigma similar to those calculated from LFP activity.

Conclusion

Since subsampling can prevent the observation of the characteristic power law and sigma in SOC systems, misclassifications of critical systems as sub- or supercritical are possible. Nevertheless, the system specific scaling of f(s) and sigma under subsampling conditions may prove useful to select physiologically motivated models of brain function. Models that better reproduce f(s) and sigma calculated from the physiological recordings may be selected over alternatives.

PS: Promessas para o futuro: 1) Levar bloco de notas e caneta na cantina do Walter. 2) Fazer eu mesmo as simulações, pelo menos os resultados provisórios. 3) Aprender com o Chialvo.

PS2: O fato de a mesma palavra (não tão comum) ser usada no mesmo contexto me sugere que alguém conversou no cafezinho com alguém, que conversou no cafezinho com alguém, que conversou no cafezinho com a Viola Priesemann. A rede social da ciência tem grau médio de separação igual a 3 ou 4. Isso é um perigo!Quem será que foi que não manteve a boca fechada? Muito provavelmente, fui eu mesmo… Ou então, é mais um caso de descoberta simultânea.

Update: Viola submeteu o trabalho em 1 de outubro de 2008. Eu falei com oTiago em julho de 2008 (update: na verdade foi em janeiro de 2008) e Dante teve a idéia meses depois, sem ter tido nenhum contato comigo. Logo, não houve tempo para difusão da idéia na rede social, eles não teriam tempo para fazer este (ótimo) paper com tantos detalhes e experimentos. Conclusão: foi um caso de a idéia estar no ar… a velha telepatia científica. A menos que Viola et al. sejam realmente rápidos em escrever e publicar…

Porque os físicos estatísticos computacionais são tão espertos?

Biology, Sociology, Geology by Computational Physicists

(Monograph Series on Nonlinear Science and Complexity)

Stauffer, Dietrich, Oliveira, Suzana Moss de, Oliveira, Paulo Murilo Castro de and Martins, Jorge Simoes de Sa

Elsevier: Amsterdam, 2006
ISBN 0444521461 (pb)
Comprar aqui.

Reviewed by
Frank Schweitzer and Markus Geipel
ETH Zurich, Switzerland

“Physicists pretend not only to know everything, but also to know everything better. This applies in particular to computational statistical physicists like us”. These are the very first two sentences of the book reviewed here. In a nutshell, the authors point the reader at their position on approaching phenomena as diverse as biological aging and speciation (chapters 3, 4), languages (chapter 5) or earthquakes (chapter 7).

What is special about Biology, Sociology, Geology by Computational Physicists? First of all the fact that the authors approach these topics without the burden of frameworks and know how, immanent to these disciplines. Thus, compared to the predominant doctrine, they exhilarate the reader with a fresh, diametrical and sometimes odd perspective.

In this respect, the authors follow their predecessor book Evolution, Money, War and Computers, where also a plethora of topics in various scientific disciplines is explored. Common to both books, statistical physics and computer simulations are creatively used to explain the most diverse phenomena. While the predecessor book had a strong bias towards biological aging, the new one treats the different subjects more equally.

Albeit, in-depth analysis of the topics discussed is not the authors intention. They rather prefer a reductionistic, sometimes a somewhat superficial way of presenting the problem under consideration, with a strong bias towards their own toy models. The KISS (“Keep it simple and stupid”) principle flourishes throughout the book, which is good and bad at the same time. It is good because their computer simulations allow the reader to get a first insight into the dynamics of a model without being fed with all details. In many cases, this seems to be a good starting point for further investigations, and scientists obsessed with the idea of putting as much as possible into their computer simulations could be impressed by the results obtained already from basic models. The downside of that approach, as always with the KISS principle, is the pitfall of oversimplification.

For the social scientist, the models discussed in Chapter 6 “Social Science” could be of special interest. Here, the topics range from retirement demography, self-organization of hierarchies and opinion dynamics to traffic jams, networks, social percolation and legal physics (each with a special subsection, about 50 pages in total). Again, compactness and boldness in interpretation is a trademark of the authors style. In chapter 6.2 for example they give insights into the self-organization of social hierarchies in mere four pages. More specifically, they extend one particular model, the Bonabeau model, and courageously interpret the simulation results – a two dimensional curve – as the “transition from the more egalitarian nomadic society to agricultural life with property of land, cities and nobility” (188).

Different chapters vary in difficulty and compactness, though. Thus, even the unprepared reader will find chapters accessible to him. In general the book is aimed at those who are to some extend familiar with the disciplines discussed. Some technical terms or concepts such as “Hamming Distance” or “Diploid” should ring a bell, as they are only very briefly outlined. As long as one is not too much interested in the theories underlying the specific models, the book gives a short, but mostly entertaining view of a variety of current topics from different disciplines.

Another positive aspect of the book is the appendix chapter, which provides a rich pool of lean Fortran program listings related to the topics discussed in the different chapters. These listings shall “encourage readers to start their own simulation” as the authors point out and they are in fact quite simple to understand.

The reference section impresses as a rather complete list of papers mainly from the field of interdisciplinary physics. On a second glimpse, one realizes that the list is only of limited use because no titles of the papers are given at all (if only to give a hint about their content) and the reader has to be familar with the partially cryptic abbreviaton of the journal names from various fields.

All in all, Biology, Sociology, Geology by Computational Physicists is a book for the open minded reader and the connoisseur of interdisciplinary physics. They will, in particular, like the fresh and homourous, sometimes ironic style in which the authors comment about their own research and may obtain hints for further research. So, to quote the authors at the very end: “keep our minds open, without demanding immediate large-scale applications”.

Estudo computacional sobre polarização ideológica

A dar uma olhada. Isso parece contar a história da polarização ideológica nos EUA e uma polarização similar, em menor escala, no Brasil.

Hate: no choice. Agent simulations

(Submitted on 19 Aug 2009)

We report our recent simulations on the social processes which — in our opinion — lie at the bottom of hate. First simulation deals with the so-called Heider balance where initial purely random preferences split the community into two mutually hostile groups. Second simulation shows that once these groups are formed, the cooperation between them is going to fail. Third simulation provides a numerical illustration of the process of biased learning; the model indicates that lack of objective information is a barrier to new information. Fourth simulation shows that in the presence of a strong conflict between communities hate is unavoidable.

Comments: 17 pages, 5 figures
Subjects: Physics and Society (physics.soc-ph)
Cite as: arXiv:0908.2692v1 [physics.soc-ph]

Guerreiros altruístas

Guerras modelaram altruísmo humano, dizem pesquisadores

RICARDO BONALUME NETO

da Folha de S.Paulo

A guerra na Pré-História era frequente e altamente letal, mas essa luta constante está ligada ao surgimento de comportamentos altruístas na espécie humana. E quando os grupos humanos atingiram determinado tamanho, criava-se o potencial para uma revolução no comportamento e na cultura.
É o que indicam dois estudos publicados na edição de hoje da revista científica “Science”.
José Manuel Ribeiro/Reuters
Figura de 10 mil anos com cavalos copulando é uma das primeiras que dão a ideia de movimento, afirmam pesquisadores em artigos
Samuel Bowles, do Instituto Santa Fé (EUA) e da Universidade de Siena (Itália), usou dados arqueológicos e etnográficos sobre populações de caçadores-coletores e mostrou que a mortalidade produzida pelos conflitos poderia ter promovido a predisposição para ajudar membros de grupos não diretamente aparentados.
O guerreiro “altruísta” é aquele que está disposto a sacrificar a vida em prol da sobrevivência do grupo.Mas quão precisas são as estimativas de populações pré-históricas, ou da mortalidade das guerras mais remotas?
“É surpreendente –e um pouco reconfortante– que os conjuntos de dados etnográficos e arqueológicos resultem em quase a mesma estimativa -14% de mortalidade”, disse Bowles à Folha.
Revoluções
Já os pesquisadores Adam Powell; Stephen Shennan e Mark Thomas, do University College, de Londres, afirmam que o tamanho das populações explicaria o motivo de comportamentos socioculturais modernos terem surgido na África há 90 mil anos, desaparecido há 65 mil anos e ressurgido na Europa 45 mil anos atrás.
“Por comportamento moderno, nós queremos dizer um salto radical em complexidade cultural e tecnológica, que torna nossa espécie única. Isso inclui comportamento simbólico, como arte abstrata e realista, decoração corporal usando contas, ocre ou kits de tatuagem; instrumentos musicais, artefatos de osso, chifre e marfim; lâminas de pedra e tecnologia de caça mais sofisticada, como arcos, bumerangues e redes”, afirma Powell.
Em geral, os pesquisadores especulavam que essa revolução cultural tivesse surgido por conta do aumento do cérebro humano. Mas os autores lembram que esse comportamento só surgiu cerca de 100 mil anos depois de ter aparecido o ser humano anatomicamente moderno, e que em alguns casos as inovações foram perdidas.
Eles argumentam com cálculos sobre o tamanho das antigas populações, que mostram que só quando elas atingem uma determinada massa crítica é que as inovações podem surgir e ser transmitidas.
Ruth Mace, também do University College, de Londres, discutiu as duas pesquisas em artigo também na edição de hoje da “Science”. “Os dois estudos sugerem que a estrutura demográfica das nossas populações ancestrais determinava como a evolução social procederia”, diz Mace.
Ela lembra que os biólogos tendem a achar que a seleção natural darwiniana, o motor da evolução, age principalmente em indivíduos e em genes. Mas novos estudos têm procurado mostrar que a seleção também age no grupo social.
“Definir altruísmo também é sempre problemático. Aqui ele é definido como um comportamento que ajuda o grupo, mas que pode ser custoso ao indivíduo”, disse Mace à Folha.
Bowles diz que procurou usar dados apenas sobre populações de caçadores-coletores que não faziam grande uso de animais ou plantas domesticados, pois ele queria manter o foco sobre as condições que existiam há 100 mil anos, e não há 10 mil, quando a agricultura e a pecuária já existiam. Ficaram de fora, assim, dados sobre a guerra entre os índios Yanomami da fronteira Brasil-Venezuela, “o povo feroz”.
“O outro artigo é consistente com o meu trabalho. Mas a questão é muito diferente. Uma população mais densa não apenas cria oportunidades para troca, mas também para conflitos”, comenta Bowles.