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Learning to Learn: leveraging your circadian rhythm

Learning to Learn: leveraging your circadian rhythm | Social Foraging | Scoop.it

There are a few distinct, precious moments of heightened sensory elation that we can achieve through unique actions; whether that be hitting the sweet spot on your driver from the tee box, tossing that crumpled up piece of paper that started out as a great idea and delivering it perfectly into the waste basket 10 feet away, or something as simple as arriving at the perfect adjective when telling a story to a friend.

 

Achieving a greater sense of cognitive ability when interacting with either the external environment around you or the internal synapses of your own brain is an equally satisfying accomplishment that many believe would lead to immediate success. There is no special formula for arriving at a heightened rate of learning, enhanced memory, or sudden talent for verbiage; however there is a proven internal process that you can utilize in order to maximize your work output, in channeling your Circadian Rhythm.

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Social Foraging
Dynamics of Social Interaction
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Spices form the basis of food pairing in Indian cuisine

Culinary practices are influenced by climate, culture, history and geography. Molecular composition of recipes in a cuisine reveals patterns in food preferences. Indian cuisine encompasses a number of diverse sub-cuisines separated by geographies, climates and cultures. Its culinary system has a long history of health-centric dietary practices focused on disease prevention and promotion of health. We study food pairing in recipes of Indian cuisine to show that, in contrast to positive food pairing reported in some Western cuisines, Indian cuisine has a strong signature of negative food pairing; more the extent of flavor sharing between any two ingredients, lesser their co-occurrence. This feature is independent of recipe size and is not explained by ingredient category-based recipe constitution alone. Ingredient frequency emerged as the dominant factor specifying the characteristic flavor sharing pattern of the cuisine. Spices, individually and as a category, form the basis of ingredient composition in Indian cuisine. We also present a culinary evolution model which reproduces ingredient use distribution as well as negative food pairing of the cuisine. Our study provides a basis for designing novel signature recipes, healthy recipe alterations and recipe recommender systems.
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Science and Culture: Data visualization nurtures an artistic movement

Science and Culture: Data visualization nurtures an artistic movement | Social Foraging | Scoop.it
In recent years, new ways of visualizing data and networks have had an enormous influence on many areas of research, allowing, for example, thousands of data points to depict clear trends in science citations or genomic patterns. But the impact of these methods has extended beyond areas of scientific inquiry: their aesthetic has also caught the attention of artists, whose work is characterized by the representation of network topologies and complex patterns of nodes and links.
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Adaptive Dynamics of Extortion and Compliance

Adaptive Dynamics of Extortion and Compliance | Social Foraging | Scoop.it

Direct reciprocity is a mechanism for the evolution of cooperation. For the iterated prisoner’s dilemma, a new class of strategies has recently been described, the so-called zero-determinant strategies. Using such a strategy, a player can unilaterally enforce a linear relationship between his own payoff and the co-player’s payoff. In particular the player may act in such a way that it becomes optimal for the co-player to cooperate unconditionally. In this way, a player can manipulate and extort his co-player, thereby ensuring that the own payoff never falls below the co-player’s payoff. However, using a compliant strategy instead, a player can also ensure that his own payoff never exceeds the co-player’s payoff. Here, we use adaptive dynamics to study when evolution leads to extortion and when it leads to compliance. We find a remarkable cyclic dynamics: in sufficiently large populations, extortioners play a transient role, helping the population to move from selfish strategies to compliance. Compliant strategies, however, can be subverted by altruists, which in turn give rise to selfish strategies. Whether cooperative strategies are favored in the long run critically depends on the size of the population; we show that cooperation is most abundant in large populations, in which case average payoffs approach the social optimum. Our results are not restricted to the case of the prisoners dilemma, but can be extended to other social dilemmas, such as the snowdrift game. Iterated social dilemmas in large populations do not lead to the evolution of strategies that aim to dominate their co-player. Instead, generosity succeeds.

 
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Game Theory Calls Cooperation Into Question

Game Theory Calls Cooperation Into Question | Social Foraging | Scoop.it

When the manuscript crossed his desk, Joshua Plotkin, a theoretical biologist at the University of Pennsylvania, was immediately intrigued. The physicist Freeman Dyson and the computer scientist William Press, both highly accomplished in their fields, had found a new solution to a famous, decades-old game theory scenario called the prisoner’s dilemma, in which players must decide whether to cheat or cooperate with a partner. The prisoner’s dilemma has long been used to help explain how cooperation might endure in nature. After all, natural selection is ruled by the survival of the fittest, so one might expect that selfish strategies benefiting the individual would be most likely to persist. But careful study of the prisoner’s dilemma revealed that organisms could act entirely in their own self-interest and still create a cooperative community.

Press and Dyson’s new solution to the problem, however, threw that rosy perspective into question. It suggested the best strategies were selfish ones that led to extortion, not cooperation.

Plotkin found the duo’s math remarkable in its elegance. But the outcome troubled him. Nature includes numerous examples of cooperative behavior. For example, vampire bats donate some of their blood meal to community members that fail to find prey. Some species of birds and social insects routinely help raise another’s brood. Even bacteria can cooperate, sticking to each other so that some may survive poison. If extortion reigns, what drives these and other acts of selflessness?

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How brain waves guide memory formation: Neurons hum at different frequencies to tell the brain which memories it should store

How brain waves guide memory formation: Neurons hum at different frequencies to tell the brain which memories it should store | Social Foraging | Scoop.it
Our brains generate a constant hum of activity: As neurons fire, they produce brain waves that oscillate at different frequencies. Long thought to be merely a byproduct of neuron activity, recent studies suggest that these waves may play a critical role in communication between different parts of the brain.
A new study from MIT neuroscientists adds to that evidence. The researchers found that two brain regions that are key to learning — the hippocampus and the prefrontal cortex — use two different brain-wave frequencies to communicate as the brain learns to associate unrelated objects. Whenever the brain correctly links the objects, the waves oscillate at a higher frequency, called “beta,” and when the guess is incorrect, the waves oscillate at a lower “theta” frequency.
“It’s like you’re playing a computer game and you get a ding when you get it right, and a buzz when you get it wrong. These two areas of the brain are playing two different ‘notes’ for correct guesses and wrong guesses,” says Earl Miller, the Picower Professor of Neuroscience, a member of MIT’s Picower Institute for Learning and Memory, and senior author of a paper describing the findings in the Feb. 23 online edition of Nature Neuroscience.
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Using Artificial Intelligence to Solve #SEO | SEJ

Using Artificial Intelligence to Solve #SEO | SEJ | Social Foraging | Scoop.it
I recently wrote about how to statistically model any given set of search results, which I hope gives marketing professionals a glimpse into how rapidly the SEO industry is currently changing in 2015. In that article, I had mentioned that the search engine model should be able to “self-calibrate”, or take its algorithms and weightings of those algorithms, and correlate the modeled data against real-world data from public search engines, to find a precise search engine modeling of any environment.

But taking thousands of parameters and trying to find the best combination of those that can curve fit search engine results is what we in computer science call a NP-Hard problem. It’s astronomically expensive in terms of computational processing. It’s really hard.

So how can we accomplish this task of self-calibrating a search engine model? Well, it turns out that we will turn to the birds — yes, birds — to solve this incredibly hard problem.

Full Disclosure: I am the CTO of MarketBrew, a company that uses artificial intelligence to develop and host a SaaS-based commercial search engine model.
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Study follows the rise of individuals with the greatest influence on collective group behavior

Study follows the rise of individuals with the greatest influence on collective group behavior | Social Foraging | Scoop.it
Who takes charge during a disaster or at an accident scene? The question has intrigued sociologists since Gustave Le Bon first studied "herd behavior" in nineteenth-century France. The question of an individual's influence over the activity of a collective has perplexed researchers, in countless studies of this behavior, ever since.
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Role of the motor system in language knowledge

Role of the motor system in language knowledge | Social Foraging | Scoop.it
All spoken languages express words by sound patterns, and certain patterns (e.g., blog) are systematically preferred to others (e.g., lbog). What principles account for such preferences: does the language system encode abstract rules banning syllables like lbog, or does their dislike reflect the increased motor demands associated with speech production? More generally, we ask whether linguistic knowledge is fully embodied or whether some linguistic principles could potentially be abstract. To address this question, here we gauge the sensitivity of English speakers to the putative universal syllable hierarchy (e.g., blif≻bnif≻bdif≻lbif) while undergoing transcranial magnetic stimulation (TMS) over the cortical motor representation of the left orbicularis oris muscle. If syllable preferences reflect motor simulation, then worse-formed syllables (e.g., lbif) should (i) elicit more errors; (ii) engage more strongly motor brain areas; and (iii) elicit stronger effects of TMS on these motor regions. In line with the motor account, we found that repetitive TMS pulses impaired participants’ global sensitivity to the number of syllables, and functional MRI confirmed that the cortical stimulation site was sensitive to the syllable hierarchy. Contrary to the motor account, however, ill-formed syllables were least likely to engage the lip sensorimotor area and they were least impaired by TMS. Results suggest that speech perception automatically triggers motor action, but this effect is not causally linked to the computation of linguistic structure. We conclude that the language and motor systems are intimately linked, yet distinct. Language is designed to optimize motor action, but its knowledge includes principles that are disembodied and potentially abstract.
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Human Face Recognition Found In Neural Network Based On Monkey Brains

Human Face Recognition Found In Neural Network Based On Monkey Brains | Social Foraging | Scoop.it
When neuroscientists use functional magnetic resonance imaging to see how a monkey’s brain responds to familiar faces, something odd happens. When shown a familiar face, a monkey’s brain lights up, not in a specific area, but in nine different ones.

Neuroscientists call these areas “face patches” and think they are neural networks with the specialised functions associated with face recognition. In recent years, researchers have begun to tease apart what each of these patches do. However, how they all function together is poorly understood.

Today, we get some insight into this problem thanks to the work of Amirhossein Farzmahdi at the Institute for Research on Fundamental Sciences in Tehran, Iran, and a few pals from around the world. These guys have built a number of neural networks, each with the same functions as those found in monkey brains. They’ve then joined them together to see how they work as a whole.

The result is a neural network that can recognise faces accurately. But that’s not all. The network also displays many of the idiosyncratic properties of face recognition in humans and monkeys, for example, the inability to recognise faces easily when they are upside down.
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A Graphic Biography of Darwin: the evolution of the father of evolution..Happy Birthday Darwin

A Graphic Biography of Darwin: the evolution of the father of evolution..Happy Birthday Darwin | Social Foraging | Scoop.it
Charles Darwin — father of evolution, decoder of human emotion, hopeless romantic, occasional grump — was born on February 12, 1809. From Smithsonian Books comes Darwin: A Graphic Biography (public library; UK) — a fine addition to outstanding graphic nonfiction, joining other famous graphic biographies of cultural icons like Richard Feynman, Hunter S. Thompson, The Carter Family, and Steve Jobs. Written by journalist Eugene Byrne and illustrated by cartoonist Simon Gurr, the story takes us into the life and times of Darwin — from a curious child on a “beeting” expedition to a patient young man persevering through the ups and downs of battling creationist oppression to a worldwide legend — tracing his intellectual adventures amidst the fascinating scientific world of the 1800s.
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Cooperate without looking: Why we care what people think and not just what they do

Evolutionary game theory typically focuses on actions but ignores motives. Here, we introduce a model that takes into account the motive behind the action. A crucial question is why do we trust people more who cooperate without calculating the costs? We propose a game theory model to explain this phenomenon. One player has the option to “look” at the costs of cooperation, and the other player chooses whether to continue the interaction. If it is occasionally very costly for player 1 to cooperate, but defection is harmful for player 2, then cooperation without looking is a subgame perfect equilibrium. This behavior also emerges in population-based processes of learning or evolution. Our theory illuminates a number of key phenomena of human interactions: authentic altruism, why people cooperate intuitively, one-shot cooperation, why friends do not keep track of favors, why we admire principled people, Kant’s second formulation of the Categorical Imperative, taboos, and love.
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Data Mining Reveals A Global Link Between Corruption and Wealth

Data Mining Reveals A Global Link Between Corruption and Wealth | Social Foraging | Scoop.it
One question that social scientists and economists have long puzzled over is how corruption arises in different cultures and why it is more prevalent in some countries than others. But it has always been difficult to find correlations between corruption and other measures of economic or social activity.

Michal Paulus and Ladislav Kristoufek at Charles University in Prague, Czech Republic have for the first time found a correlation between the perception of corruption in different countries and their economic development.

The data they use comes from Transparency International, a non-profit campaigning organisation based in Berlin, Germany, and which defines corruption as the misuse of public power for private benefit. Each year, this organisation publishes a global list of countries ranked according to their perceived levels of corruption. The list is compiled using at least three sources of information but does not directly measure corruption, because of the difficulties in gathering such data.
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Rick Frank's curator insight, February 11, 6:08 AM

Really? Who would have guessed?

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Researchers use games to evolve AI brains | Games

Researchers use games to evolve AI brains | Games | Social Foraging | Scoop.it
The current complexity of the human brain is impressive enough on its own, but to imagine that humanity’s defining organ reached this peak through generations of evolution is even more mind-boggling. Neuroscientists are learning more about the brain all the time through new kinds of research, and at the University of Wisconsin-Madison’s School of Medicine and Public Health, researchers are studying how neural networks evolve by teaching computers to play video games.
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Data Mining Indian Recipes Reveals New Food Pairing Phenomenon

Data Mining Indian Recipes Reveals New Food Pairing Phenomenon | Social Foraging | Scoop.it
The food pairing hypothesis is the idea that ingredients that share the same flavors ought to combine well in recipes. For example, the English chef Heston Blumenthal discovered that white chocolate and caviar share many flavors and turn out to be a good combination. Other unusual combinations that seem to confirm the hypothesis include strawberries and peas, asparagus and butter, and chocolate and blue cheese.

But in recent years researchers have begun to question how well this hypothesis holds in different cuisines. For example, food pairing seems to be common in North American and Western European cuisines but absent in cuisines from southern Europe and East Asia.

Today, Anupam Jain and pals at the Indian Institute of Technology Jodhpur say the opposite effect occurs in Indian cuisine. In this part of the world, foods with common flavors are less likely to appear together in the same recipe. And the presence of certain spices make the negative food pairing effect even stronger.
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Networks Reveal the Connections of Disease: the hidden biological missteps that make us sick.

Networks Reveal the Connections of Disease: the hidden biological missteps that make us sick. | Social Foraging | Scoop.it
efan Thurner is a physicist, not a biologist. But not long ago, the Austrian national health insurance clearinghouse asked Thurner and his colleagues at the Medical University of Vienna to examine some data for them. The data, it turned out, were the anonymized medical claims records — every diagnosis made, every treatment given — of most of the nation, which numbers some 8 million people. The question was whether the same standard of care could continue if, as had recently happened in Greece, a third of the funding evaporated. But Thurner thought there were other, deeper questions that the data could answer as well.

In a recent paper in the New Journal of Physics, Thurner and his colleagues Peter Klimek and Anna Chmiel started by looking at the prevalence of 1,055 diseases in the overall population. They ran statistical analyses to uncover the risk of having two diseases together, identifying pairs of diseases for which the percentage of people who had both was higher than would be expected if the diseases were uncorrelated — in other words, a patient who had one disease was more likely than the average person to have the other. They applied statistical corrections to reduce the risk of drawing false connections between very rare and very common diseases, as any errors in diagnosis will get magnified in such an analysis. Finally, the team displayed their results as a network in which the diseases are nodes that connect to one another when they tend to occur together.
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Iterated Prisoner’s Dilemma contains strategies that dominate any evolutionary opponent

Iterated Prisoner’s Dilemma contains strategies that dominate any evolutionary opponent | Social Foraging | Scoop.it
The two-player Iterated Prisoner’s Dilemma game is a model for both sentient and evolutionary behaviors, especially including the emergence of cooperation. It is generally assumed that there exists no simple ultimatum strategy whereby one player can enforce a unilateral claim to an unfair share of rewards. Here, we show that such strategies unexpectedly do exist. In particular, a player X who is witting of these strategies can (i) deterministically set her opponent Y’s score, independently of his strategy or response, or (ii) enforce an extortionate linear relation between her and his scores. Against such a player, an evolutionary player’s best response is to accede to the extortion. Only a player with a theory of mind about his opponent can do better, in which case Iterated Prisoner’s Dilemma is an Ultimatum Game.
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Science vs Conspiracy: Collective Narratives in the Age of Misinformation

Science vs Conspiracy: Collective Narratives in the Age of Misinformation | Social Foraging | Scoop.it
The large availability of user provided contents on online social media facilitates people aggregation around shared beliefs, interests, worldviews and narratives. In spite of the enthusiastic rhetoric about the so called collective intelligence unsubstantiated rumors and conspiracy theories—e.g., chemtrails, reptilians or the Illuminati—are pervasive in online social networks (OSN). In this work we study, on a sample of 1.2 million of individuals, how information related to very distinct narratives—i.e. main stream scientific and conspiracy news—are consumed and shape communities on Facebook. Our results show that polarized communities emerge around distinct types of contents and usual consumers of conspiracy news result to be more focused and self-contained on their specific contents. To test potential biases induced by the continued exposure to unsubstantiated rumors on users’ content selection, we conclude our analysis measuring how users respond to 4,709 troll information—i.e. parodistic and sarcastic imitation of conspiracy theories. We find that 77.92% of likes and 80.86% of comments are from users usually interacting with conspiracy stories.
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Computational Anthropology Reveals How the Most Important People in History Vary by Culture

Computational Anthropology Reveals How the Most Important People in History Vary by Culture | Social Foraging | Scoop.it
Data mining Wikipedia people reveals some surprising differences in the way eastern and western cultures identify important figures in history, say computational anthropologists.

 

The study of differences between cultures has been revolutionized by the internet and the behavior of individuals online. Indeed, this phenomenon is behind the birth of the new science of computational anthropology.

 

One particularly fruitful window into the souls of different cultures is Wikipedia, the crowd-sourced online encyclopedia with over 31 million articles in 285 different languages. One important category consists of articles about significant people. And not just anyone can appear. Wikipedia has specific criteria that notable people must meet to merit inclusion.

 

So an interesting question is how the most important people vary from one language version of Wikipedia to another. Clearly, these differences must arise from the cultural forces that determine notability (or notoriety) in different parts of the world.

 

Today, Peter Gloor at the Massachusetts Institute of Technology in Cambridge and a few pals say they have calculated the  most significant people in four different language versions of Wikipedia—English, German, Chinese and Japanese. And they say important differences emerge, not just in the names that appear, but in the broader make-up of the lists.

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FIN – the thumb-ring that aims to take human-machine interaction to the next level

FIN – the thumb-ring that aims to take human-machine interaction to the next level | Social Foraging | Scoop.it
Wearable technology market is still in early evolution stages with growing adoption in segments such as fitness and wellness, healthcare and medical, industrial and military and infotainment sectors. According to industry reports, the global wearable technology market is expected to reach USD 5.8 billion in 2018.

There are multiple factors that have contributed to this rise & evolution of the wearable market. The recent technology advancements – comprising of an integration of compactness, portability, usability, data, analytics & other multi functionalities in one product – has led to a booming industry. A change in consumer paradigm has also contributed to the rise of this industry. The innovation and product mindset is rapidly evolving in India and Indian entrepreneurs are waking up to this. Indian entrepreneurs are optimistic about this opportunity & are aiming create products of global relevance.
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Dynamics of gene circuits shapes evolvability

Dynamics of gene circuits shapes evolvability | Social Foraging | Scoop.it
To what extent does the dynamical mechanism producing a specific biological phenotype bias the ability to evolve into novel phenotypes? We use the interpretation of a morphogen gradient into a single stripe of gene expression as a model phenotype. Although there are thousands of three-gene circuit topologies that can robustly develop a stripe of gene expression, the vast majority of these circuits use one of just six fundamentally different dynamical mechanisms. Here we explore the potential for gene circuits that use each of these six mechanisms to evolve novel phenotypes such as multiple stripes, inverted stripes, and gradients of gene expression. Through a comprehensive and systematic analysis, we find that circuits that use alternative mechanisms differ in the likelihood of reaching novel phenotypes through mutation. We characterize the phenotypic transitions and identify key ingredients of the evolutionary potential, such as sensitive interactions and phenotypic hubs. Finally, we provide an intuitive understanding on how the modular design of a particular mechanism favors the access to novel phenotypes. Our work illustrates how the dynamical mechanism by which an organism develops constrains how it can evolve. It is striking that these dynamical mechanisms and their impact on evolvability can be observed even for such an apparently simple patterning task, performed by just three-node circuits.
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The spontaneous emergence of conventions: An experimental study of cultural evolution

The spontaneous emergence of conventions: An experimental study of cultural evolution | Social Foraging | Scoop.it
How do shared conventions emerge in complex decentralized social systems? This question engages fields as diverse as linguistics, sociology, and cognitive science. Previous empirical attempts to solve this puzzle all presuppose that formal or informal institutions, such as incentives for global agreement, coordinated leadership, or aggregated information about the population, are needed to facilitate a solution. Evolutionary theories of social conventions, by contrast, hypothesize that such institutions are not necessary in order for social conventions to form. However, empirical tests of this hypothesis have been hindered by the difficulties of evaluating the real-time creation of new collective behaviors in large decentralized populations. Here, we present experimental results—replicated at several scales—that demonstrate the spontaneous creation of universally adopted social conventions and show how simple changes in a population’s network structure can direct the dynamics of norm formation, driving human populations with no ambition for large scale coordination to rapidly evolve shared social conventions.
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Hudooku, the online platform that connects forum discussions

Hudooku, the online platform that connects forum discussions | Social Foraging | Scoop.it
The question that gave rise to Hudooku.com was: “Is there a better way to break down the silos of knowledge that exist on the internet?” Hudooku means quest or search in Kannada and is a platform to connect people anywhere in the world so that they can exchange insights and experiences quickly and efficiently on any topic. It gives users access to forums from any website on the subject that he or she is looking for and is also available as a mobile app for android and iOS.
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Ebola Epidemic Should End In May, Say Disease Modellers

Ebola Epidemic Should End In May, Say Disease Modellers | Social Foraging | Scoop.it
On 17 March 2014, doctors diagnosed a single case of Ebola in the county of Lofa in Liberia, West Africa. This was the first, patient zero, in an epidemic that has so far infected more than 20,000 people and killed almost 8000.

On 15 August, the World Health Organisation and other bodies began a major drive in Liberia to halt the epidemic. The strategy has two parts. The first aims to limit the spread of the disease from people who have been infected by ensuring that everyone with symptoms goes to an official treatment centre.

The second is to prevent the spread of the disease after death by ensuring that every Ebola victim is buried in a way that prevents further infection. That means wearing protective clothing to place the body in a body bag and then in a coffin before transporting it to a grave. Finally, the aid workers must disinfect the victim’s home and ensure appropriate washing for all those involved in the disposal of the body.
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Interplay of approximate planning strategies

Humans routinely formulate plans in domains so complex that even the most powerful computers are taxed. To do so, they seem to avail themselves of many strategies and heuristics that efficiently simplify, approximate, and hierarchically decompose hard tasks into simpler subtasks. Theoretical and cognitive research has revealed several such strategies; however, little is known about their establishment, interaction, and efficiency. Here, we use model-based behavioral analysis to provide a detailed examination of the performance of human subjects in a moderately deep planning task. We find that subjects exploit the structure of the domain to establish subgoals in a way that achieves a nearly maximal reduction in the cost of computing values of choices, but then combine partial searches with greedy local steps to solve subtasks, and maladaptively prune the decision trees of subtasks in a reflexive manner upon encountering salient losses. Subjects come idiosyncratically to favor particular sequences of actions to achieve subgoals, creating novel complex actions or “options.”
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Hidden Personality Traits Revealed Through Your Favorite Ice Cream Flavor

Hidden Personality Traits Revealed Through Your Favorite Ice Cream Flavor | Social Foraging | Scoop.it
Vanilla is one of the simplest of ice cream flavors, but its fans are actually likely to be colorful, impulsive, idealistic risk-takers who "rely more on intuition than logic," according to studies conducted by neurologist Dr. Alan Hirsch, founder of the Smell and Taste Treatment and Research Foundation. Vanilla lovers were also emotionally expressive and successful in close relationships. As for the research: Hirsch uses various standardized psychiatric test results to make statistical correlations, explaining that the same part of the brain (the limbic lobe) is responsible for both personality traits and food preference. Interestingly, Hirsch says the taste for your favorite ice cream is set during childhood and tends to remain consistent throughout your life. 
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