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Ethereum: Next-generation distributed cryptographic ledger

Ethereum: Next-generation distributed cryptographic ledger | Social Foraging | Scoop.it

Ethereum is a next-generation distributed cryptographic ledger that is designed to allow users to encode advanced transaction types, smart contracts and decentralized applications into the blockchain. Ethereum will support custom currencies or "colored coins", financial derivatives, and much more, but unlike many previous networks that attempted to accomplish the same thing Ethereum does not attempt to constrain users into using specific "features"; instead, the ledger includes a built-in Turing-complete programming language that can be used to construct any kind of contract that can be mathematically defined.

 

When the grand experiment that is bitcoin began, the anonymous wizard desired to test two parameters- a trustless, decentralized database enjoying security enforced by the austere relentlessness of cryptography and a robust transaction system capable of sending value across the world without intermediaries. Yet the past five years years have painfully demonstrated a third missing feature: a sufficiently powerful Turing-complete scripting language.

 

Up until this point, most innovation in advanced applications such as domain and identity registration, user-issued currencies, smart property, smart contracts, and decentralized exchange has been highly fragmented, and implementing any of these technologies has required creating an entire meta-protocol layer or even a specialized blockchain. Theoretically, however, each and every one of these innovations and more can potentially be made hundreds of times easier to implement, and easier to scale, if only there was a stronger foundational layer with a powerful scripting language for all of these protocols to build upon. And this need is what we seek to satisfy.

 

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Summit Europe: Artificial Intelligence Evolving From Disappointing to Disruptive

Summit Europe: Artificial Intelligence Evolving From Disappointing to Disruptive | Social Foraging | Scoop.it
Neil Jacobstein, Singularity University’s co-chair in AI and Robotics, has been thinking about artificial intelligence for a long time, and at a recent talk at Summit Europe, he wanted to get a few things straight. There’s AI, and then there’s AI.

Elon Musk recently tweeted this about Nick Bostrom’s book, Superintelligence: “We need to be super careful with AI. Potentially more dangerous than nukes.”

AI has long been a slippery term, its definition in near-constant flux. Ray Kurzweil has said AI is used to describe human capabilities just out of reach for computers—but when they master these skills, like playing chess, we no longer call it AI.

These days we use the term to describe machine learning algorithms, computer programs that autonomously learn by interacting with large sets of data. But we also use it to describe the theoretical superintelligent computers of the future.

According to Jacobstein, the former are already proving hugely useful in a range of fields—and aren’t necessarily dangerous—and the latter are still firmly out of reach.
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Cooperation and control in multiplayer social dilemmas

Cooperation and control in multiplayer social dilemmas | Social Foraging | Scoop.it
Direct reciprocity and conditional cooperation are important mechanisms to prevent free riding in social dilemmas. However, in large groups, these mechanisms may become ineffective because they require single individuals to have a substantial influence on their peers. However, the recent discovery of zero-determinant strategies in the iterated prisoner’s dilemma suggests that we may have underestimated the degree of control that a single player can exert. Here, we develop a theory for zero-determinant strategies for iterated multiplayer social dilemmas, with any number of involved players. We distinguish several particularly interesting subclasses of strategies: fair strategies ensure that the own payoff matches the average payoff of the group; extortionate strategies allow a player to perform above average; and generous strategies let a player perform below average. We use this theory to describe strategies that sustain cooperation, including generalized variants of Tit-for-Tat and Win-Stay Lose-Shift. Moreover, we explore two models that show how individuals can further enhance their strategic options by coordinating their play with others. Our results highlight the importance of individual control and coordination to succeed in large groups.
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Mapping the unconscious maintenance of a lost first language

Mapping the unconscious maintenance of a lost first language | Social Foraging | Scoop.it
Optimal periods during early development facilitate the formation of perceptual representations, laying the framework for future learning. A crucial question is whether such early representations are maintained in the brain over time without continued input. Using functional MRI, we show that internationally adopted (IA) children from China, exposed exclusively to French since adoption (mean age of adoption, 12.8 mo), maintained neural representations of their birth language despite functionally losing that language and having no conscious recollection of it. Their neural patterns during a Chinese lexical tone discrimination task matched those observed in Chinese/French bilinguals who have had continual exposure to Chinese since birth and differed from monolingual French speakers who had never been exposed to Chinese. They processed lexical tone as linguistically relevant, despite having no Chinese exposure for 12.6 y, on average, and no conscious recollection of that language. More specifically, IA participants recruited left superior temporal gyrus/planum temporale, matching the pattern observed in Chinese/French bilinguals. In contrast, French speakers who had never been exposed to Chinese did not recruit this region and instead activated right superior temporal gyrus. We show that neural representations are not overwritten and suggest a special status for language input obtained during the first year of development.
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Viral Misinformation: The Role of Homophily and Polarization

Viral Misinformation: The Role of Homophily and Polarization | Social Foraging | Scoop.it

The spreading of unsubstantiated rumors on online social networks (OSN) either unintentionally or intentionally (e.g., for political reasons or even trolling) can have serious consequences such as in the recent case of rumors about Ebola causing disruption to health-care workers. Here we show that indicators aimed at quantifying information consumption patterns might provide important insights about the virality of false claims. In particular, we address the driving forces behind the popularity of contents by analyzing a sample of 1.2M Facebook Italian users consuming different (and opposite) types of information (science and conspiracy news). We show that users' engagement across different contents correlates with the number of friends having similar consumption patterns (homophily), indicating the area in the social network where certain types of contents are more likely to spread. Then, we test diffusion patterns on an external sample of 4,709 intentional satirical false claims showing that neither the presence of hubs (structural properties) nor the most active users (influencers) are prevalent in viral phenomena. Instead, we found out that in an environment where misinformation is pervasive, users' aggregation around shared beliefs may make the usual exposure to conspiracy stories (polarization) a determinant for the virality of false information.

 

Viral Misinformation: The Role of Homophily and Polarization
Aris Anagnostopoulos, Alessandro Bessi, Guido Caldarelli, Michela Del Vicario, Fabio Petroni, Antonio Scala, Fabiana Zollo, Walter Quattrociocchi

http://arxiv.org/abs/1411.2893


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Removing the brake: How to increase brain activity and memory

Removing the brake: How to increase brain activity and memory | Social Foraging | Scoop.it

Is it possible to rapidly increase (or decrease) the amount of information the brain can store? A new international study led by the Research Institute of the McGill University Health Centre (RI-MUHC) suggests is may be. Their research has identified a molecule that improves brain function and memory recall is improved. Published in the latest issue of Cell Reports, the study has implications for neurodevelopmental and neurodegenerative diseases, such as autism spectral disorders and Alzheimer’s disease.

 

“Our findings show that the brain has a key protein called FXR1P (Fragile X Related Protein 1) that limits the production of molecules necessary for memory formation,” says RI-MUHC neuroscientist Keith Murai, the study’s senior author and Associate Professor in the Department of Neurology and Neurosurgery at McGill University. “When this brake-protein is suppressed, the brain is able to store more information.”

 

Murai and his colleagues used a mouse model to study how changes in brain cell connections produce new memories. When FXR1P was selectively removed from certain parts of the brain, new molecules were produced. They strengthened connections between brain cells, which correlated with improved memory and recall in the mice.

 

“The role of FXR1P was a surprising result,” says Dr. Murai. “Previous to our work, no-one had identified a role for this regulator in the brain. Our findings have provided fundamental knowledge about how the brain processes information. We’ve identified a new pathway that directly regulates how information is handled and this could have relevance for understanding and treating brain diseases.” 

 

“Future research in this area could be very interesting,” he adds. “If we can identify compounds that control the braking potential of FXR1P, we may be able to alter the amount of brain activity or plasticity. For example, in autism, one may want to decrease certain brain activity and in Alzheimer’s disease, we may want to enhance the activity. By manipulating FXR1P, we may eventually be able to adjust memory formation and retrieval, thus improving the quality of life of people suffering from brain diseases.” 

 


Via Dr. Stefan Gruenwald
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Carlos Rodrigues Cadre's curator insight, November 17, 4:28 PM

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Diane Johnson's curator insight, November 18, 9:21 AM

NGSS includes opportunities for students to understand and apply learning about information processing in biological systems

Lucile Debethune's curator insight, November 21, 5:45 AM

Parmi les nombreuses proteines du cerveau, cette recherche se concentre sur la proteines FXR1P, qui agit comme un frein à la production de molécule nécessaire à la formation de molécules. Travailler sur cette protéine pourait être un élément clef dans le traitement du fonctionnement anormal du cerveau.

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Goethe on the Psychology of Color and Emotion

Goethe on the Psychology of Color and Emotion | Social Foraging | Scoop.it
Color is an essential part of how we experience the world, both biologically and culturally. One of the earliest formal explorations of color theory came from an unlikely source — the German poet, artist, and politician Johann Wolfgang von Goethe, who in 1810 published Theory of Colours (public library; public domain), his treatise on the nature, function, and psychology of colors. Though the work was dismissed by a large portion of the scientific community, it remained of intense interest to a cohort of prominent philosophers and physicists, including Arthur Schopenhauer, Kurt Gödel, and Ludwig Wittgenstein.
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Twitter Firehose Reveals How Weather Affects Mood

Twitter Firehose Reveals How Weather Affects Mood | Social Foraging | Scoop.it

We’re all influenced by the weather but psychologists have struggled to gather convincing data revealing the correlation. So researchers are turning to Twitter instead.

 

Researchers have long known that the weather has a profound physiological impact. The human body reacts to sunlight by producing serotonin, a neurotransmitter that is strongly linked with feelings of well-being. Some people are more likely to be depressed during winter, a condition known as seasonal affective disorder or SAD.

But despite this evidence, psychologists have long failed to find a clear correlation between weather and mood. This area of study is littered with studies that show contradictory correlations and others that show no correlation at all.

Now Jiwei Li at Stanford University and a few pals aim to change that. These guys have mined geotagged tweets for indications of mood and then searched for correlations with the weather. They say that some moods are clearly correlated with certain types of weather or changes in the weather but sometimes in counterintuitive ways.

Li and co begin with a database of tweets geotagged to one of 32 major urban areas in the US, such as New York, Chicago, Los Angeles, San Franciso and so on. These had been filtered from a dataset of consisting of 10 per cent of all tweets posted in 2010 and 2011.

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Computing with silicon neurons: Scientists use artificial nerve cells to classify different types of data

Computing with silicon neurons: Scientists use artificial nerve cells to classify different types of data | Social Foraging | Scoop.it

Scientists from Berlin and Heidelberg use artificial nerve cells to classify different types of data. They can recognize handwritten numbers, or distinguish plant species based on their flowers.

 

A bakery assistant who takes the bread from the shelf just to give it to his boss who then hands it over to the customer? Rather unlikely. Instead, both work at the same time to sell the baked goods. Similarly, computer programs are more efficient if they process data in parallel rather than to calculate them one after the other. However, most programs that are applied still work in a serial manner.

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Video: Twitter usage reveals ebbs and flows of life in NYC

Next time you’re in New York City and wondering where the party’s at, or if you’re going to get stuck on 8th Avenue in traffic from the Rangers’ game, you might do well to consult an unlikely ally: Twitter. Scientists have analyzed 6 million geolocated, time-stamped tweets from New York City and the surrounding area and discovered a “heartbeat” that says a lot about how New Yorkers live. As seen above, the frequency and location of tweets swells and recedes rhythmically, with red representing higher than average use and blue representing lower than average. Unsurprisingly, the study, published today on the arXiv preprint server, found that the most prominent predictor of Twitter usage is our daily sleep cycle. But by analyzing the locations of the tweets, the team was also able to watch New Yorkers commute from the suburbs into Manhattan, gather at stadiums for sports events, head downtown during late-night hours, and more. The team also found that Twitter usage tended to increase in transportation hubs where users are presumably bored with nothing else to do. The scientists posit that analyzing large-scale social population dynamics could help us design safer and more efficient cities—a goal that anyone who has ever tried to squeeze into an F train in midtown during rush hour can certainly appreciate.
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Acceleration of evolutionary spread by long-range dispersal

Acceleration of evolutionary spread by long-range dispersal | Social Foraging | Scoop.it
The spreading of evolutionary novelties across populations is the central element of adaptation. Unless populations are well mixed (like bacteria in a shaken test tube), the spreading dynamics depend not only on fitness differences but also on the dispersal behavior of the species. Spreading at a constant speed is generally predicted when dispersal is sufficiently short ranged, specifically when the dispersal kernel falls off exponentially or faster. However, the case of long-range dispersal is unresolved: Although it is clear that even rare long-range jumps can lead to a drastic speedup—as air-traffic–mediated epidemics show—it has been difficult to quantify the ensuing stochastic dynamical process. However, such knowledge is indispensable for a predictive understanding of many spreading processes in natural populations. We present a simple iterative scaling approximation supported by simulations and rigorous bounds that accurately predicts evolutionary spread, which is determined by a trade-off between frequency and potential effectiveness of long-distance jumps. In contrast to the exponential laws predicted by deterministic “mean-field” approximations, we show that the asymptotic spatial growth is according to either a power law or a stretched exponential, depending on the tails of the dispersal kernel. More importantly, we provide a full time-dependent description of the convergence to the asymptotic behavior, which can be anomalously slow and is relevant even for long times. Our results also apply to spreading dynamics on networks with a spectrum of long-range links under certain conditions on the probabilities of long-distance travel: These are relevant for the spread of epidemics.
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Computation of Emotions - Peter Robinson

Computation of Emotions - Peter Robinson | Social Foraging | Scoop.it
The importance of emotional expression as part of human communication has been understood since the seventeenth century, and has been explored scientifically since Charles Darwin and others in the nineteenth century.  Recent advances in Psychology have greatly improved our understanding of the role of affect in communication, perception, decision-making, attention and memory.  At the same time, advances in technology mean that it is becoming possible for machines to sense, analyse and express emotions.  We can now consider how these advances relate to each other and how they can be brought together to influence future research in perception, attention, learning, memory, communication, decision-making and other applications.

This talk will survey recent advances in theories of emotion and affect, their embodiment in computational systems, the implications for general communications, and broader applications.  The combination of new results in psychology with new techniques of computation on new technologies will enable new applications in commerce, education, entertainment, security, therapy and everyday life.  However, there are important issues of privacy and personal expression that must also be considered.
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A Reappraisal of How to Build Modular, Reusable Models of Biological Systems

A Reappraisal of How to Build Modular, Reusable Models of Biological Systems | Social Foraging | Scoop.it
Biological researchers increasingly rely on computational models to integrate biological systems knowledge, test hypotheses, and forecast system behavior. The expanding size of these models requires solutions for managing their complexity. Modularity, a time-tested design principle for managing complexity, can be applied within the biological modeling field to parallelize work, automate composition, and promote effective model sharing. As modelers of complex biological systems, we aim to apply modular production to accelerate our efforts and have therefore investigated several currently available approaches for modular modeling. We argue that some traditional features of modularity, in particular the isolation of a module's contents from the rest of the system, can impede model sharing and composition when applied within the context of biological simulation. Alternative approaches that can automatically interface model components based on the biological meaning of their contents (their semantics) avoid these limitations. Our conclusions have strategic implications for the design of systems biology, synthetic biology, and integrated physiological modeling technologies, as well as community-level model curation efforts.
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Earl Miller on Biology of Consciousness: Bridging the Mind-Body Gap?

Earl Miller on Biology of Consciousness: Bridging the Mind-Body Gap? | Social Foraging | Scoop.it
The mind-body problem was first raised, rather circuitously, as a non-problem by Aristotle more than 2,000 years ago. He postulated that, "It is not necessary to ask whether soul and body are one, just as it is not necessary to ask whether the wax and its shape are one." Plato disagreed, as he thought that souls could transmigrate during reincarnation. But a more radical opponent to Aristotle's theory arose about two millenniums later in the person of René Descartes. He tried to rip Aristotle's theory apart. His philosophy introduced the notion of dualism, opposing "the surrounding spirits" that directed thoughts to the mechanism of the human body. Can today's advances in neurobiology help us make a decision on the matter?

A quick scroll through the names of biology laboratories worldwide -- from Connecticut to London, to Sataima, Japan -- might throw up names like "Molecular Psychiatry" or "Receptors and Cognition" suggesting they have begun to bridge the mind-body gap, long the preserve of philosophers. "What language does the brain use to generate consciousness?" Francis Crick, the scientist who discovered DNA, once asked. But have scientists really understood the real nature of consciousness? And if it's a language, why are its grammar and syntax not better understood? Scientists are looking to be the first to propose an unified theory of consciousness.

Research in the 1950s led scientists to call the brain, like the heart, a "battery" and a "hive." The examination of the brain has generally taken place along these lines. Electrophysiology (the discipline that examines the brain as a "battery") studies the electrical waves that flow between neurons, or ensembles of neurons, and Biochemistry (the "hive") approaches the brain's function through measurements of the interactions between brain molecules as they catalyze, regulate, replicate and destroy. Unfortunately no biochemical substrate have been proposed to correlate with consciousness yet. Only electrophysiological studies have proposed such correlates.

Current advances in Electrophysiology and Consciousness trace their way back to research done by Crick himself in the 1990s, his late research period. He and his colleague, Christof Koch, were the first to propose that visual awareness correlates with certain brain regions electrical waves. Using electroencephalography, a way of recording electrical activity along the scalp, they worked out that these waves were being fired at 40 Hertz (1). In other words, from all the electrical activity generated by the brain, they isolated a frequency -- 40 Hertz -- of the electrical waves involved in attention. These ways were called gamma waves.
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Artificial intelligence is now creating its own magic tricks

Artificial intelligence is now creating its own magic tricks | Social Foraging | Scoop.it
You might not have to be a professional magician to come up with clever tricks in the near future. Researchers at Queen Mary University of London have developed artificial intelligence that can create magic tricks (specifically, those based on math) all on its own. Once their program learns the basics of creating magic jigsaws and "mind reading" stunts, it can generate many variants of these tricks by itself. This could be particularly handy if you like to impress your friends on a regular basis -- you could show them a new card trick every time without having to do much work.

The best part? You can try some of these computer-generated tricks yourself. The 12 Magicians of Osiris magic jigsaw is available as a web pack, and you can download the Android component for one card trick, Phoney, from Google Play. Neither will give you as much satisfaction as developing tricks from scratch, but they're proof that computers can do more with math than solve equations.
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Rethinking natural altruism: Simple reciprocal interactions trigger children’s benevolence

Rethinking natural altruism: Simple reciprocal interactions trigger children’s benevolence | Social Foraging | Scoop.it
A very simple reciprocal activity elicited high degrees of altruism in 1- and 2-y-old children, whereas friendly but nonreciprocal activity yielded little subsequent altruism. In a second study, reciprocity with one adult led 1- and 2-y-olds to provide help to a new person. These results question the current dominant claim that social experiences cannot account for early occurring altruistic behavior. A third study, with preschool-age children, showed that subtle reciprocal cues remain potent elicitors of altruism, whereas a fourth study with preschoolers showed that even a brief reciprocal experience fostered children’s expectation of altruism from others. Collectively, the studies suggest that simple reciprocal interactions are a potent trigger of altruism for young children, and that these interactions lead children to believe that their relationships are characterized by mutual care and commitment.
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Static network structure can stabilize human cooperation

Static network structure can stabilize human cooperation | Social Foraging | Scoop.it
The evolution of cooperation in network-structured populations has been a major focus of theoretical work in recent years. When players are embedded in fixed networks, cooperators are more likely to interact with, and benefit from, other cooperators. In theory, this clustering can foster cooperation on fixed networks under certain circumstances. Laboratory experiments with humans, however, have thus far found no evidence that fixed network structure actually promotes cooperation. Here, we provide such evidence and help to explain why others failed to find it. First, we show that static networks can lead to a stable high level of cooperation, outperforming well-mixed populations. We then systematically vary the benefit that cooperating provides to one’s neighbors relative to the cost required to cooperate (b/c), as well as the average number of neighbors in the network (k). When b/c > k, we observe high and stable levels of cooperation. Conversely, when b/c ≤ k or players are randomly shuffled, cooperation decays. Our results are consistent with a quantitative evolutionary game theoretic prediction for when cooperation should succeed on networks and, for the first time to our knowledge, provide an experimental demonstration of the power of static network structure for stabilizing human cooperation.
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Lost in the City: Revisiting Milgram's Experiment in the Age of Social Networks

Lost in the City: Revisiting Milgram's Experiment in the Age of Social Networks | Social Foraging | Scoop.it

As more and more users access social network services from smart devices with GPS receivers, the available amount of geo-tagged information makes repeating classical experiments possible on global scales and with unprecedented precision. Inspired by the original experiments of Milgram, we simulated message routing within a representative sub-graph of the network of Twitter users with about 6 million geo-located nodes and 122 million edges. We picked pairs of users from two distant metropolitan areas and tried to find a route between them using local geographic information only; our method was to forward messages to a friend living closest to the target. We found that the examined network is navigable on large scales, but navigability breaks down at the city scale and the network becomes unnavigable on intra-city distances. This means that messages usually arrived to the close proximity of the target in only 3–6 steps, but only in about 20% of the cases was it possible to find a route all the way to the recipient, in spite of the network being connected.

 

Szüle J, Kondor D, Dobos L, Csabai I, Vattay G (2014) Lost in the City: Revisiting Milgram's Experiment in the Age of Social Networks. PLoS ONE 9(11): e111973. http://dx.doi.org/10.1371/journal.pone.0111973


Via NESS, Complexity Digest
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Hyper-Brain Networks Support Romantic Kissing in Humans

Hyper-Brain Networks Support Romantic Kissing in Humans | Social Foraging | Scoop.it
Coordinated social interaction is associated with, and presumably dependent on, oscillatory couplings within and between brains, which, in turn, consist of an interplay across different frequencies. Here, we introduce a method of network construction based on the cross-frequency coupling (CFC) and examine whether coordinated social interaction is associated with CFC within and between brains. Specifically, we compare the electroencephalograms (EEG) of 15 heterosexual couples during romantic kissing to kissing one’s own hand, and to kissing one another while performing silent arithmetic. Using graph-theory methods, we identify theta–alpha hyper-brain networks, with alpha serving a cleaving or pacemaker function. Network strengths were higher and characteristic path lengths shorter when individuals were kissing each other than when they were kissing their own hand. In both partner-oriented kissing conditions, greater strength and shorter path length for 5-Hz oscillation nodes correlated reliably with greater partner-oriented kissing satisfaction. This correlation was especially strong for inter-brain connections in both partner-oriented kissing conditions but not during kissing one’s own hand. Kissing quality assessed after the kissing with silent arithmetic correlated reliably with intra-brain strength of 10-Hz oscillation nodes during both romantic kissing and kissing with silent arithmetic. We conclude that hyper-brain networks based on CFC may capture neural mechanisms that support interpersonally coordinated voluntary action and bonding behavior.

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Inner Workings: Breaking down bees' dances

Inner Workings: Breaking down bees' dances | Social Foraging | Scoop.it
Worker bees in the United Kingdom have taken a new job—collecting data for researchers at the University of Sussex. Margaret Couvillon and her colleagues have devised an environmental monitoring system that uses foraging honey bees and their “waggle” dances to measure land quality. The technique could help scientists assess the ecological effects of different land use schemes, they say.
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An evolutionary, ecosystem view of economies

An evolutionary, ecosystem view of economies | Social Foraging | Scoop.it
To understand market perturbations like crashes and bubbles, SFI Distinguished Professor Geoffrey West and three co-authors advocate a revised view that treats an economy like biologists would think about an ecosystem rife with evolutionary dynamics.
"Here, we emphasize the importance of an ecosystems perspective: it is precisely due to the web of interdependencies among all companies that the unrestrained growth of one, or a few, companies leads to systematic imbalance."
The growth of such imbalances, they say, is a result of evolutionary processes often leading to feedback loops. Drawing on their recent paper in Proceedings of the Royal Society A, for example, the authors suggest that two mechanisms "act as catalysts for the emergence of a crisis. The first is banks copying the business models of the most (short-term) successful bank, which leads to loss of both diversity and resilience. The second is investors such as fund managers increasing their appetite for risk by trying to outperform competitors."
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Twitter open sourced a recommendation algorithm for massive datasets

Twitter open sourced a recommendation algorithm for massive datasets | Social Foraging | Scoop.it
Twitter recently open sourced an algorithm designed to ease the process of running recommendation engines at large scale. Called DIMSUM, the algorithm pre-processes pairs of possible matches so the other algorithms in the process don’t waste resources on poor choices.
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Humans have innate grasp of probability - Study of Indigenous Maya

Humans have innate grasp of probability - Study of Indigenous Maya | Social Foraging | Scoop.it
People overrate the chances of dying in a plane crash and guess incorrectly at the odds that a coin toss will yield 'heads' after a string of several 'tails'. Yet humans have an innate sense of chance, a study of indigenous Maya people suggests. Adults in Guatemala who have never learned a formal number system or a written language did as well as formally educated adults and children at estimating the probability of chance events1, the researchers found.
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A typology of street patterns

A typology of street patterns | Social Foraging | Scoop.it
We propose a quantitative method to classify cities according to their street pattern. We use the conditional probability distribution of shape factor of blocks with a given area and define what could constitute the ‘fingerprint’ of a city. Using a simple hierarchical clustering method, these fingerprints can then serve as a basis for a typology of cities. We apply this method to a set of 131 cities in the world, and at an intermediate level of the dendrogram, we observe four large families of cities characterized by different abundances of blocks of a certain area and shape. At a lower level of the classification, we find that most European cities and American cities in our sample fall in their own sub-category, highlighting quantitatively the differences between the typical layouts of cities in both regions. We also show with the example of New York and its different boroughs, that the fingerprint of a city can be seen as the sum of the ones characterizing the different neighbourhoods inside a city. This method provides a quantitative comparison of urban street patterns, which could be helpful for a better understanding of the causes and mechanisms behind their distinct shapes.
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How cultures around the world make decisions

How cultures around the world make decisions | Social Foraging | Scoop.it
Is the American obsession with individual freedom really such a great idea? What other cultures know about how to make good choices.

Sit down at a restaurant in France, and there’s a menu. Salmon with rice. French beans. Wine. If you ask for potatoes instead of rice, the restaurant will say no. Because it is their menu. Not yours. To an American, this is nearly unfathomable.

One American model: Give me personal autonomy or give me death.

“In terms of fetishizing the idea of choice, the U.S. is the absolute pinnacle,” says Barry Schwartz, professor of social theory and social change at Swarthmore College and author of The Paradox of Choice. “We want to be able to choose everything that matters, as well as the things that don’t.”
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Using synchronous Boolean networks to model several phenomena of collective behavior

In this paper, we propose an approach for modeling and analysis of a number of phenomena of collective behavior. By collectives we mean multi-agent systems that transition from one state to another at discrete moments of time. The behavior of a member of a collective (agent) is called conforming if the opinion of this agent at current time moment conforms to the opinion of some other agents at the previous time moment. We presume that at each moment of time every agent makes a decision by choosing from the set {0,1} (where 1-decision corresponds to action and 0-decision corresponds to inaction). In our approach we model collective behavior with synchronous Boolean networks. We presume that in a network there can be agents that act at every moment of time. Such agents are called instigators. Also there can be agents that never act. Such agents are called loyalists. Agents that are neither instigators nor loyalists are called simple agents. We study two combinatorial problems. The first problem is to find a disposition of instigators that in several time moments transforms a network from a state where a majority of simple agents are inactive to a state with a majority of active agents. The second problem is to find a disposition of loyalists that returns the network to a state with a majority of inactive agents. Similar problems are studied for networks in which simple agents demonstrate the contrary to conforming behavior that we call anticonforming. We obtained several theoretical results regarding the behavior of collectives of agents with conforming or anticonforming behavior. In computational experiments we solved the described problems for randomly generated networks with several hundred vertices. We reduced corresponding combinatorial problems to the Boolean satisfiability problem (SAT) and used modern SAT solvers to solve the instances obtained.
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