Social Foraging
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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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The more gray matter you have, the more altruistic you are

The more gray matter you have, the more altruistic you are | Social Foraging | Scoop.it

The volume of a small brain region influences one's predisposition for altruistic behavior. Researchers from the University of Zurich show that people who behave more altruistically than others have more gray matter at the junction between the parietal and temporal lobe, thus showing for the first time that there is a connection between brain anatomy, brain activity and altruistic behavior.

 

Why are some people very selfish and others very altruistic? Previous studies indicated that social categories like gender, income or education can hardly explain differences in altruistic behavior. Recent neuroscience studies have demonstrated that differences in brain structure might be linked to differences in personality traits and abilities. Now, for the first time, a team of researchers from the University of Zurich headed by Ernst Fehr, Director of the Department of Economics, show that there is a connection between brain anatomy and altruistic behavior.

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Experience, corpulence and decision making in ant foraging

Social groups are structured by the decisions of their members. Social insects typically divide labour: some decide to stay in the nest while others forage for the colony. Two sources of information individuals may use when deciding whether to forage are their own experience of recent task performance and their own physiology, e.g. fat reserves (corpulence). The former is primarily personal information; the latter may give an indication of the food reserves of the whole colony. These factors are hard to separate because typically leaner individuals are also more experienced foragers. We designed an experiment to determine whether foraging specialisation is physiological or experience based (or both). We invented a system of automatic doors controlled by radio-tag information to manipulate task access and decouple these two sources of information.

 

Our results show that when information from corpulence and recent experience conflict, ants behave only in accordance with their corpulence. However, among ants physiologically inclined to forage (less corpulent ants), recent experience of success positively influenced their propensity to forage again. Hence, foraging is organised via long-term physiological differences among individuals resulting in a relatively stable response threshold distribution, with fine-tuning provided by short-term learning processes. Through these simple rules, colonies can organise their foraging effort both robustly and flexibly.

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WHY SLIM ANTS LISTEN TO THE COLLECTIVE STOMACH

A rumbly tummy is always a good sign that you need to get some food, but how do you know that you're hungry when you forage on behalf of a collective stomach? That is the problem faced by social insects. According to Elva Robinson from the University of York, UK, Temnothorax albipennis foragers are always the leanest occupants of the nest. However, ‘It's not as simple as the lean ants know when they're hungry and that triggers foraging’, explains Robinson, recalling that instead of consuming their honeydew load, slender foragers selflessly give it up to fatter nest mates. Robinson and her colleagues, Ofer Feinerman and Nigel Franks, wondered whether the skinnier ants forage because their mass has fallen below a critical threshold or whether the ants are motivated by their previous foraging experience and their slenderness is merely a side-effect of their frenetic lifestyle (p. 2653).

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Where will you be this time tomorrow? Smartphone data can guess within 20 metres

You may not know where you will be tomorrow, but your cell phone company might be able to guess.

 

UK researchers have developed an algorithm that can predict your future geographic location using data gathered from your friends’ smartphones.

 

In the study of two hundred people, the algorithm predicted the location of some users 24 hours later within 100 metres, others as close as 20 metres.

Mirco Musolesi, lead researcher and computer science lecturer at the University of Birmingham, said the algorithm is exploiting the synchronized rhythm of the city.

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Higgs boson gets set to music: Listen to the Higgs

Higgs boson gets set to music: Listen to the Higgs | Social Foraging | Scoop.it
Scientists generate a musical picture of so-called `God particle' by attaching musical notes to each data point. Read this blog post by Charles Cooper on Cutting EdgeYou may not be able to see the Higgs boson but now you can hear it.

 

Thanks to the labors of a team of researchers who attached musical notes to data that scientists believe correspond to the Higgs, the "sonification" of data points from the Atlas project at the Large Hadron Collider in Switzerland now lets listeners hear a melody with a distinctly Latin beat.

 

The team was comprised of Domenico Vicinanza, a researcher at Dante, Mariapaola Sorrentino of the ASTRA Project, and Giuseppe La Rocca of Catania's INFN..

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PyBrain: Python-Based Reinforcement Learning, Artificial Intelligence and Neural Network

PyBrain is a modular Machine Learning Library for Python. Its goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms.

 

PyBrain is short for Python-Based Reinforcement Learning, Artificial Intelligence and Neural Network Library. In fact, we came up with the name first and later reverse-engineered this quite descriptive "Backronym".

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CultureLab: Artificially alive artwork tantalises and surprises

CultureLab: Artificially alive artwork tantalises and surprises | Social Foraging | Scoop.it

What if the buildings around you were alive, and responded to your touch? Hylozoism - the theory that everything is alive - is the philosophy behind Philip Beesley’s Hylozoic Series: Sibyl, an exhibit at the border of architecture and science fiction that is now on display in Australia at the 18th Biennale of Sydney.

 

Equal parts robotics, chemistry and prototypical architecture, the exhibit is a distributed network of interactive, moving and almost living elements. “I would say this is a work of sculpture and a work of architecture,” says Beesley, a Canadian artist and architect.

 

At first glance, the installation appears to be a rainforest winter wonderland suspended from the ceiling. But it is anything but whimsical: the technology behind this responsive environment can be found in touchscreens, and the science could inform the future of architecture.

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Computer that could outlive the universe a step closer

Computer that could outlive the universe a step closer | Social Foraging | Scoop.it

The heat-death of the universe need not bring an end to the computing age. A strange device known as a time crystal can theoretically continue to work as a computer even after the universe cools. A new blueprint for such a time crystal brings its construction a step closer.

 

Ordinary crystals are three-dimensional objects whose atoms are arranged in regular, repeating patterns – just like table salt. They adopt this structure because it uses the lowest amount of energy possible to maintain.

 

Earlier this year, Frank Wilczek, a theoretical physicist at the Massachusetts Institute of Technology, speculated that a similar structure might repeat regularly in the fourth dimension – time.

To translate the spatial symmetry of a regular crystal into the fourth dimension, the atoms in such a "time crystal" would have to constantly rotate and return to their original location. Crucially, they would also have to be in their lowest possible energy state as they do so, meaning that they would naturally continue to rotate even after the universe has succumbed to entropy and cooled to a uniform temperature – a state known as heat-death.

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Does diabetes hamper cognitive function by lowering the brain's cholesterol?

Low cholesterol is generally a good thing. But decreasing the amount of low-density lipoprotein—LDL, the "bad cholesterol"—is only one part of the body’s equation for a healthy balance of lipids. And although lowering cholesterol can be good for the heart, it’s not always great for the brain, which contains about a quarter of the body’s cholesterol.

 

Recent research has shown that drugs that lower cholesterol, such as statins, might put some individuals at risk for cognitive problems. And a new study suggests that diabetes, which affects cholesterol synthesis in the liver, might also be changing the rate these compounds are made in the brain.

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Quantifying and Analyzing the Network Basis of Genetic Complexity

Quantifying and Analyzing the Network Basis of Genetic Complexity | Social Foraging | Scoop.it

Genotype-to-phenotype maps exhibit complexity. This genetic complexity is mentioned frequently in the literature, but a consistent and quantitative definition is lacking. Here, we derive such a definition and investigate its consequences for model genetic systems. The definition equates genetic complexity with a surplus of genotypic diversity over phenotypic diversity. Applying this definition to ensembles of Boolean network models, we found that the in-degree distribution and the number of periodic attractors produced determine the relative complexity of different topology classes. We found evidence that networks that are difficult to control, or that exhibit a hierarchical structure, are genetically complex. We analyzed the complexity of the cell cycle network of Sacchoromyces cerevisiae and pinpointed genes and interactions that are most important for its high genetic complexity. The rigorous definition of genetic complexity is a tool for unraveling the structure and properties of genotype-to-phenotype maps by enabling the quantitative comparison of the relative complexities of different genetic systems. The definition also allows the identification of specific network elements and subnetworks that have the greatest effects on genetic complexity. Moreover, it suggests ways to engineer biological systems with desired genetic properties.

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Complexity of Color

Describing colors seems like a straightforward concept, regardless of the culture or language. In my mind, I imagine a process of naming a color in English and then finding the appropriate translation in the target language. For example, in Spanish, the color blue is azul and the color green is verde. It seems simple enough, but the reality is far more complex, especially when we begin to compare the English language with indigenous languages.

 

A recent BBC documentary examines the difference in color perception across cultures, and what they discovered is not as simple as one might think.

Researchers visited the Himba people of northern Namibia and asked them to describe the color of various natural objects. Much to my surprise, they said the sky was black and the water was white. But these are not simply different color names; the researchers found that the Himba have totally different categories of color. They also found that the way people categorize color even affects their ability to perceive differences between them. For example, the Himba have words to describe multiple shades of green, and as a result, they were able to perceive these differences much faster than Europeans. In contrast, the Himba do not have separate words to describe blue and green. For them, these two colors fall within the same category, and so the Himba were less able to tell them apart.

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Scientific study reveals that individuals cooperate according to their emotional state and their prior experiences

A study by researchers at Universidad Carlos III de Madrid and Universidad de Zaragoza has determined that when deciding whether to cooperate with others, people do not act thinking about their own reward, as had been previously believed, but rather individuals are more influenced by their own mood at the time and by the number of individuals with whom they have cooperated before.

 

In addition to previous studies, this research is also based on an experiment carried out by the Institute for Biocomputation and Physics of Complex Systems (BIFI) at the Universidad de Zaragoza, together with the Fundación Ibercivis and Universidad Carlos III de Madrid (UC3M), the largest study of its kind to date in real time regarding cooperation in society. It was carried out during this past December, with 1,200 Aragon secondary students participating, who interacted electronically in real time via a social conflict prototype known as the "Prisoner's Dilemma."

 

This game shows that the greatest benefit for individuals who interact is produced when both of them collaborate, but if one collaborates and the other does not, the latter will receive more benefits than the one who cooperates. On occasion, this allows an individual to take advantage of the cooperation of others, but if this tendency is extended, in the end, no one cooperates and as such, nobody obtains rewards.

 

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Apes With Apps

Apes With Apps | Social Foraging | Scoop.it

Have you ever watched a toddler play with an iPhone?

 

Most likely, the child was completely captivated and surprisingly adept at manipulating the tiny icons. Two-year-old Teco is no different. Sitting with his Motorola Xoom tablet, he’s rapt, his dark eyes fixed on the images, fingers pecking away at the touch screen. He can’t speak, but with the aid of the tablet app I created for him, he’s building a vocabulary that will likely total several thousand words. What’s more, he’ll be able to string those words together into simple sentences and ask questions, tell jokes, and carry on conversations.

 

Such talents wouldn’t seem exceptional in a human child, but Teco is an ape—a bonobo, to be precise. To the uninitiated, bonobos look very much like chimpanzees, but they are in fact a separate species with distinct physical and behavioral traits. More collaborative and sociable than their chimp cousins, bonobos also seem to be more adept at learning human language. And they are endangered, found in the wild only in the Democratic Republic of the Congo. Recent estimates put the wild bonobo population at between 10 000 and 50 000. Fewer than 150 live in captivity. Along with the chimpanzee, they are our species’ closest relatives.

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The Eyes Don’t Have It: Lie Detection and Neuro-Linguistic Programming

The Eyes Don’t Have It: Lie Detection and Neuro-Linguistic Programming | Social Foraging | Scoop.it

Proponents of Neuro-Linguistic Programming (NLP) claim that certain eye-movements are reliable indicators of lying. According to this notion, a person looking up to their right suggests a lie whereas looking up to their left is indicative of truth telling. Despite widespread belief in this claim, no previous research has examined its validity. In Study 1 the eye movements of participants who were lying or telling the truth were coded, but did not match the NLP patterning. In Study 2 one group of participants were told about the NLP eye-movement hypothesis whilst a second control group were not.

 

Both groups then undertook a lie detection test. No significant differences emerged between the two groups. Study 3 involved coding the eye movements of both liars and truth tellers taking part in high profile press conferences. Once again, no significant differences were discovered. Taken together the results of the three studies fail to support the claims of NLP. The theoretical and practical implications of these findings are discussed.

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How does an ant decide what to do?

How does an ant decide what to do? | Social Foraging | Scoop.it

We eat when we’re hungry, but social insects have to make decisions which will support the colony not just themselves. They typically divide labour as well as reproductive duties. Even in ant species such as Lasius niger where workers are not split into different physical ‘castes’, some workers stay in the nest while others leave to forage. It is often the younger ants who care for the nest while older ants leave to collect food.

 

Information that individuals could use to decide whether to forage includes their own experience of performing tasks, or their own physiology such as fat reserves. This was investigated in a recent paper published in the Journal for Experimental Biology.

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Living Cells Show How to Fix the Financial System

Living Cells Show How to Fix the Financial System | Social Foraging | Scoop.it

Over the past three decades, the global financial system has become more dynamic and interconnected, more concentrated and complicated than ever before. Financial engineering seems to know no limits to creating new instruments that link institutions in new ways. Is that a good thing? Or could the resulting financial network be too complex? Or, perhaps, complex in the wrong way?

 

A look at biology -- which has been tinkering with network designs for billions of years -- suggests that the answer to the last question is most likely yes.

 

In “The Architecture of Complexity,” an extraordinarily original paper published 50 years ago, the economist, psychologist and artificial-intelligence pioneer Herbert Simon asked the question, Why does nature so consistently organize itself into hierarchies? Why, that is, are so many of its creations designed as systems of systems?

In biology, for example, cells organize into tissues, tissues into organs, organs into larger systems.

 

The cell itself contains a nucleus and a cell membrane, ribosomes and mitochondria. Our human organizations obviously also follow hierarchies, as do our buildings, technological devices, even our writing -- words make sentences, which build paragraphs, which then make up essays or chapters.

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Cyberwarfare, conservation and disease prevention could benefit from new network model

Computer networks are the battlefields in cyberwarfare, as exemplified by the United States' recent use of computer viruses to attack Iran's nuclear program. A computer model developed at the University of Missouri could help military strategists devise the most damaging cyber attacks as well as guard America's critical infrastructure. The model also could benefit other projects involving interconnected groups, such as restoring ecosystems, halting disease epidemics and stopping smugglers.

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Art of making things complex

Art of making things complex | Social Foraging | Scoop.it

‘Keep It Simple Silly’ is all very fine as rhetoric goes. The harsh truth is we end up making things complex, as evindenced in the Barclays’ controversy over manipulating Libor rates.

 

The story is really not about whether ants are rational creatures or not. Nor indeed is it about the presumed rationality of human behaviour — a defining principle for pretty much everything in economics.

 

One can actually argue both ways. If ants aren’t rational, that only strengthens the case for greater rationality among human beings. It is a case of, that’s-why-ants-are-the-lowly-creatures-that-they-are and-we-are-what-we-are.

 

On the other hand, one could argue that if even ants are expected to not behave rationally at all times (at the very least), can human beings be expected to do so? So out goes the theory of rational expectations guiding human behaviour.

 

But there is a third way of looking at it. Whether you are an Argentinean ant or a human being, all living creatures, whether by nature or by circumstances, are forced to choose more complex alternatives when simpler ones are available. “Keep It Simple Silly’’ is all very fine as rhetoric goes. The harsh truth is we end up making things complex for ourselves.

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A Gentle Introduction to Algorithm Complexity Analysis

A Gentle Introduction to Algorithm Complexity Analysis | Social Foraging | Scoop.it

A lot of programmers that make some of the coolest and most useful software today, such as many of the stuff we see on the Internet or use daily, don't have a theoretical computer science background. They're still pretty awesome and creative programmers and we thank them for what they build.

 

However, theoretical computer science has its uses and applications and can turn out to be quite practical. In this article, targeted at programmers who know their art but who don't have any theoretical computer science background, I will present one of the most pragmatic tools of computer science: Big O notation and algorithm complexity analysis. As someone who has worked both in a computer science academic setting and in building production-level software in the industry, this is the tool I have found to be one of the truly useful ones in practice, so I hope after reading this article you can apply it in your own code to make it better. After reading this post, you should be able to understand all the common terms computer scientists use such as "big O", "asymptotic behavior" and "worst-case analysis".

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Cellphone use linked to selfish behavior

Cellphone use linked to selfish behavior | Social Foraging | Scoop.it

Though cellphones are usually considered devices that connect people, they may make users less socially minded, finds a recent study from the University of Maryland's Robert H. Smith School of Business.

 

Marketing professors Anastasiya Pocheptsova and Rosellina Ferraro, with graduate student, Ajay T. Abraham, conducted a series of experiments on test groups of cellphone users. The findings appear in their working paper, "The Effect of Mobile Phone Use on Prosocial Behavior."

 

Prosocial behavior, as defined in the study, is action intended to benefit another person or society as a whole.

 

The researchers found that after a short period of cellphone use the subjects were less inclined to volunteer for a community service activity when asked, compared to the control-group counterparts. The cell phone users were also less persistent in solving word problems -- even though they knew their answers would translate to a monetary donation to charity.

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Little-Used Voice Assistants Are the Future of Smartphones

With the imminent arrival of Google‘s latest Android operating system later this month, Apple’s iOS upgrades this fall and Microsoft’s relentless pushto make Windows relevant to mobile devices, a lot of people are talking about smartphones and tablets. The next few months will also likely see an increasing number of people talking to these devices as well.

 

Voice assistants such as Siri, which Apple introduced with the iPhone 4S last year, and Google’s Voice Actions, which has been available on Android phones for the past couple of years, have thus far been little more than a novelty. Smartphone and tablet users are more comfortable relying on their fingers to navigate touch-screen gadgets, and the quality of voice-activated software has done little to win them over.

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Groups vote on hive locations: Honeybees in a colony select a new hive location via range voting.

Groups vote on hive locations: Honeybees in a colony select a new hive location via range voting. | Social Foraging | Scoop.it

"Thomas Seeley, a biologist at Cornell University, has been looking into the uncanny ability of honeybees to make good decisions. With as many as 50,000 workers in a single hive, honeybees have evolved ways to work through individual differences of opinion to do what's best for the colony. If only people could be as effective in boardrooms, church committees, and town meetings, Seeley says, we could avoid problems making decisions in our own lives.

 

"During the past decade, Seeley, Kirk Visscher of the University of California, Riverside, and others have been studying colonies of honeybees (Apis mellifera) to see how they choose a new home. In late spring, when a hive gets too crowded, a colony normally splits, and the queen, some drones, and about half the workers fly a short distance to cluster on a tree branch. There the bees bivouac while a small percentage of them go searching for new real estate. Ideally, the site will be a cavity in a tree, well off the ground, with a small entrance hole facing south, and lots of room inside for brood and honey. Once a colony selects a site, it usually won't move again, so it has to make the right choice.

"To find out how, Seeley's team applied paint dots and tiny plastic tags to identify all 4,000 bees in each of several small swarms that they ferried to Appledore Island, home of the Shoals Marine Laboratory. There, in a series of experiments, they released each swarm to locate nest boxes they'd placed on one side of the half-mile-long (one kilometer) island, which has plenty of shrubs but almost no trees or other places for nests.

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UK's flying ant swarms counted

UK's flying ant swarms counted | Social Foraging | Scoop.it

Scientists attempt to count the number of places flying ants appear in the UK, as they swarm across cities during their mating flights.

 

"By running the flying ant survey we can learn more about the ecology and behaviour of ants," said Dr Mark Downs, of the Society of Biology.

The charity aims to shed new light on the reasons they appear all over the country at the same time.

The results will be announced during National Biology Week in October.

 

The seasonal appearance of flying ants occurs when they embark on their "nuptial" or "mating" flight, in the first step to founding a new colony.

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The crayola-fication of the world: How we gave colors names, and it messed with our brains (part I)

The crayola-fication of the world: How we gave colors names, and it messed with our brains (part I) | Social Foraging | Scoop.it

In Japan, people often refer to traffic lights as being blue in color. And this is a bit odd, because the traffic signal indicating ‘go’ in Japan is just as green as it is anywhere else in the world. So why is the color getting lost in translation? This visual conundrum has its roots in the history of language.

 

Blue and green are similar in hue. They sit next to each other in a rainbow, which means that, to our eyes, light can blend smoothly from blue to green or vice-versa, without going past any other color in between. Before the modern period, Japanese had just one word, Ao, for both blue and green. The wall that divides these colors hadn’t been erected as yet. As the language evolved, in the Heian period around the year 1000, something interesting happened. A new word popped into being – midori – and it described a sort of greenish end of blue. Midori was a shade of ao, it wasn’t really a new color in its own right.

 

One of the first fences in this color continuum came from an unlikely place – crayons. In 1917, the first crayons were imported into Japan, and they brought with them a way of dividing a seamless visual spread into neat, discrete chunks. There were different crayons for green (midori) and blue (ao), and children started to adopt these names. But the real change came during the Allied occupation of Japan after World War II, when new educational material started to circulate. In 1951, teaching guidelines for first grade teachers distinguished blue from green, and the word midori was shoehorned to fit this new purpose.

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“Why Do We Have to Learn This Stuff?”—A New Genetics for 21st Century Students

Several years ago, our biology program decided to develop a new second-year “Fundamentals of Genetics” course to replace the third-year course that was our legacy from David Suzuki and Tony Griffiths. Although our new syllabus radically altered how the core concepts are taught, I now think the changes were much too conservative because we'd ignored how drastically the role of genetics has changed. Below I first describe the problems we originally identified and how we addressed them, and then consider the bigger problem of moving introductory genetics courses into the 21st century.

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