Social Foraging
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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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Collective strategy for obstacle navigation during cooperative transport by ants

Collective strategy for obstacle navigation during cooperative transport by ants | Social Foraging | Scoop.it
Group cohesion and consensus have primarily been studied in the context of discrete decisions, but some group tasks require making serial decisions that build on one another. We examine such collective problem solving by studying obstacle navigation during cooperative transport in ants. In cooperative transport, ants work together to move a large object back to their nest. We blocked cooperative transport groups of Paratrechina longicornis with obstacles of varying complexity, analyzing groups' trajectories to infer what kind of strategy the ants employed. Simple strategies require little information, but more challenging, robust strategies succeed with a wider range of obstacles. We found that transport groups use a stochastic strategy that leads to efficient navigation around simple obstacles, and still succeeds at difficult obstacles. While groups navigating obstacles preferentially move directly toward the nest, they change their behavior over time; the longer the ants are obstructed, the more likely they are to move away from the nest. This increases the chance of finding a path around the obstacle. Groups rapidly changed directions and rarely stalled during navigation, indicating that these ants maintain consensus even when the nest direction is blocked. Although some decisions were aided by the arrival of new ants, at many key points, direction changes were initiated within the group, with no apparent external cause. This ant species is highly effective at navigating complex environments, and implements a flexible strategy that works for both simple and more complex obstacles.

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A neural code for emotion: tracking unconscious emotional influences – with fMRI

A neural code for emotion: tracking unconscious emotional influences – with fMRI | Social Foraging | Scoop.it
Our daily experience rides along the backdrop of a dynamic stream of mental states, characterized by spontaneous changes is mood or emotion. For instance, as
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The AP wants to use machine learning to automate turning print stories into broadcast ones

The AP wants to use machine learning to automate turning print stories into broadcast ones | Social Foraging | Scoop.it
The experiment is part of a larger effort by the news agency to incorporate automation into its journalism.
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Spur Projects: Tracking How the World is Feeling

Spur Projects: Tracking How the World is Feeling | Social Foraging | Scoop.it
Spur Projects, an Australian organization focusing on suicide prevention, has published the data from its “How Is the World Feeling?” mental health survey. This survey gathered data about people’s emotional well-being, including emotions such as “happy,” “anxious,” and “powerful,” as well as demographic information about participants, such as employment status and sexual orientation. Spur Projects conducted the survey from October 10-16, 2016, and received responses from 10,144 people from 104 countries.

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Airbnb open sources data-science-sharing platform

Airbnb open sources data-science-sharing platform | Social Foraging | Scoop.it
Most organizations have well established procedures for vetting and sharing computer code. But what about data analysis?

Important findings are often held in "a mixed bag of presentations, emails, and Google Docs," two members of Airbnb's engineering and data science team blogged at Medium in February. When someone in the organization wants to locate and use that existing work, they often have to track down updated code and waste time checking and reproducing earlier results. And then they'll typically distribute their own findings "through a presentation, email, or Google Doc, perpetuating the cycle."


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After considering various ideas on how to solve this problem, Airbnb created an internal Knowledge Repo, combining git version control and Markdown templates for reporting results. Airbnb recently open-sourced its Knowledge Repository Beta, seeking contributors to help move the project forward.


Git allows the same sort of peer review and version control that developers typically use to collaborate on code, while Markdown offers a mixture of text and code in a single, easily reproducible file. You can see RStudio's tutorial on R Markdown for more info of what Markdown in general can do. Markdown is available for other languages such as Python as well.
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Why is Google working on Angular 2 and Polymer?

Why is Google working on Angular 2 and Polymer? | Social Foraging | Scoop.it
At Google I/O in 2016 there were two browser focused technologies from the company. These are the Polymer project and Angular 2. It might be a bit hard to make sense of why the company is investing in these two overlapping and competing projects.

Angular 2 is a compelete web framework that allows developers to build client side applications that run both on the server with Node.js as well as in the browser. It's a major revision to the wildly successful Angular 1.x and while making major changes internally, it's still the same product.

Polymer on the other hand is a project that aims to let developers use the latest native Web Platform features today. It's essentially an interim solution to provide a layer that will enable technologies that only exist today as specifications. In essence Polymer does not create any new features.

Essentially where Angular 2 aims to create a custom framework, Polymer aims to bridge features until they are natively available in browsers. Traditionally JavaScript has been used to bridge functionalities like this, but the goal of Polymer is essentially to use less JavaScript and let native browser features take this over.
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Mary Meeker's 2016 internet trends report: The internet is slowing down, messaging is taking on the home screen, and voice search is big.

The internet is slowing down, messaging is taking on the home screen, and voice search is big.
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Decoding Spontaneous Emotional States in the Human Brain

Decoding Spontaneous Emotional States in the Human Brain | Social Foraging | Scoop.it
Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

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Stimulation-Based Control of Dynamic Brain Networks

Stimulation-Based Control of Dynamic Brain Networks | Social Foraging | Scoop.it
The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement.

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How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences

The weight with which a specific outcome feature contributes to preference quantifies a person’s ‘taste’ for that feature. However, far from being fixed personality characteristics, tastes are plastic. They tend to align, for example, with those of others even if such conformity is not rewarded. We hypothesised that people can be uncertain about their tastes. Personal tastes are therefore uncertain beliefs. People can thus learn about them by considering evidence, such as the preferences of relevant others, and then performing Bayesian updating. If a person’s choice variability reflects uncertainty, as in random-preference models, then a signature of Bayesian updating is that the degree of taste change should correlate with that person’s choice variability. Temporal discounting coefficients are an important example of taste–for patience. These coefficients quantify impulsivity, have good psychometric properties and can change upon observing others’ choices. We examined discounting preferences in a novel, large community study of 14–24 year olds. We assessed discounting behaviour, including decision variability, before and after participants observed another person’s choices. We found good evidence for taste uncertainty and for Bayesian taste updating. First, participants displayed decision variability which was better accounted for by a random-taste than by a response-noise model. Second, apparent taste shifts were well described by a Bayesian model taking into account taste uncertainty and the relevance of social information. Our findings have important neuroscientific, clinical and developmental significance.

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The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color

The Sapir-Whorf hypothesis holds that our thoughts are shaped by our native language, and that speakers of different languages therefore think differently. This hypothesis is controversial in part because it appears to deny the possibility of a universal groundwork for human cognition, and in part because some findings taken to support it have not reliably replicated. We argue that considering this hypothesis through the lens of probabilistic inference has the potential to resolve both issues, at least with respect to certain prominent findings in the domain of color cognition. We explore a probabilistic model that is grounded in a presumed universal perceptual color space and in language-specific categories over that space. The model predicts that categories will most clearly affect color memory when perceptual information is uncertain. In line with earlier studies, we show that this model accounts for language-consistent biases in color reconstruction from memory in English speakers, modulated by uncertainty. We also show, to our knowledge for the first time, that such a model accounts for influential existing data on cross-language differences in color discrimination from memory, both within and across categories. We suggest that these ideas may help to clarify the debate over the Sapir-Whorf hypothesis.
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Modelling the Evolution of Social Structure

Modelling the Evolution of Social Structure | Social Foraging | Scoop.it
Although simple social structures are more common in animal societies, some taxa (mainly mammals) have complex, multi-level social systems, in which the levels reflect differential association. We develop a simulation model to explore the conditions under which multi-level social systems of this kind evolve. Our model focuses on the evolutionary trade-offs between foraging and social interaction, and explores the impact of alternative strategies for distributing social interaction, with fitness criteria for wellbeing, alliance formation, risk, stress and access to food resources that reward social strategies differentially. The results suggest that multi-level social structures characterised by a few strong relationships, more medium ties and large numbers of weak ties emerge only in a small part of the overall fitness landscape, namely where there are significant fitness benefits from wellbeing and alliance formation and there are high levels of social interaction. In contrast, ‘favour-the-few’ strategies are more competitive under a wide range of fitness conditions, including those producing homogeneous, single-level societies of the kind found in many birds and mammals. The simulations suggest that the development of complex, multi-level social structures of the kind found in many primates (including humans) depends on a capacity for high investment in social time, preferential social interaction strategies, high mortality risk and/or differential reproduction. These conditions are characteristic of only a few mammalian taxa.
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Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates

Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates | Social Foraging | Scoop.it
Functional MRI (fMRI) is 25 years old, yet surprisingly its most common statistical methods have not been validated using real data. Here, we used resting-state fMRI data from 499 healthy controls to conduct 3 million task group analyses. Using this null data with different experimental designs, we estimate the incidence of significant results. In theory, we should find 5% false positives (for a significance threshold of 5%), but instead we found that the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%. These results question the validity of some 40,000 fMRI studies and may have a large impact on the interpretation of neuroimaging results.

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The Power of Expectation Can Restrain Hyper-Emotional Memories in the Brain

The Power of Expectation Can Restrain Hyper-Emotional Memories in the Brain | Social Foraging | Scoop.it
The creaking of an opening gate followed by a dog attack can disturb otherwise pleasant evening walks. The sound of that gate opening on subsequent walks will elicit an emotional response, and the power of this response will be different if the dog was a German shepherd or a poodle. Through repeated experiences, the neighborhood, the gate and the dog all become part of the brain’s emotional memory system. The core of this system–the amygdala–forges indelible links of experience when we are attacked or threatened but, thanks to the power of expectation, the strength of these emotional memories is proportional to the unpleasantness of the experience.

“Forming an emotional memory is all about learning and calibrating our internal expectations with repeated external stimuli from the environment,” says Joshua Johansen, a team leader at the RIKEN Brain Science Institute. An instructive signal like a dog attack should startle you–and your amygdala–the first time it happens, but over time, both your brain activity and your behavior will temper the reaction to the dog attack once you learn to expect when and how it happens, for example on a particular street, outside of a particular house. In a study published in Nature Neuroscience, Johansen and colleagues discovered a neural circuit that can temper the strength of emotional memories by restraining the amygdala’s over-responsiveness to expected but unpleasant stimuli.
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How do Asian honey bees make decisions using dance?

How do Asian honey bees make decisions using dance? | Social Foraging | Scoop.it
Decision making is hard. Decision making in a group is even harder. The vultures from Disney’s The Jungle Book come to mind. What we gonna do? I don’t know, whatcha wanna do? And so it goes.

Honey bees are an example of a superorganism. Not only do they work together to run their large and complex societies, they also work together to decide on a new home.

When honey bees decide it’s getting too cozy in their hive, half of the bees will leave with the old queen and swarm to an intermediate location. The remaining bees will stay home with a newly raised queen.
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This AI software dreams up new drug molecules

This AI software dreams up new drug molecules | Social Foraging | Scoop.it
Ingesting a heap of drug data allows a machine-learning system to suggest alternatives humans hadn’t tried yet.
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Visualising the languages of New York

Visualising the languages of New York | Social Foraging | Scoop.it
Web developer Jill Hubley has created a data visualization mapping the most common languages in New York City, broken down by census tract. Users can select individual languages to see where they are the most common, as well as filter out English and Spanish—the most common languages—to see the widely varied demographic makeup of the city’s population. The visualization uses data from the U.S. Census Bureau’s 2014 American Community Survey
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Historic Achievement: Microsoft researchers reach human parity in conversational speech recognition

Historic Achievement: Microsoft researchers reach human parity in conversational speech recognition | Social Foraging | Scoop.it
Microsoft has made a major breakthrough in speech recognition, creating a technology that understands a conversation as well as a person does.

In a paper published Monday, a team of researchers and engineers in Microsoft Artificial Intelligence and Research reported a speech recognition system that makes the same or fewer errors than professional transcriptionists.  The researchers reported a word  error rate (WER) of 5.9 percent, down from the 6.3 percent WER the team reported just last month.

The 5.9 percent error rate is about equal to that of people who were asked to transcribe the same conversation, and it’s the lowest ever recorded against the industry standard Switchboard speech recognition task.
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Spatial-Temporal Congestion Identification Based on Time Series Similarity Considering Missing Data

Spatial-Temporal Congestion Identification Based on Time Series Similarity Considering Missing Data | Social Foraging | Scoop.it
Traffic congestion varies spatially and temporally. The observation of the formation, propagation and dispersion of network traffic congestion can lead to insights about the network performance, the bottleneck dynamics etc. While many researchers use the traffic flow data to reconstruct the congestion profile, the data missing problem is bypassed. Current methods either omit the missing data or supplement the missing part by average etc. Great error may be introduced during these processes. Rather than simply discarding the missing data, this research regards the data missing event as a result of either the severe congestion which prevent the floating vehicle from entering the congested area, or a type of feature of the resulting traffic flow time series. Hence a new traffic flow operational index time series similarity measurement is expected to be established as a basis of identifying the dynamic network bottleneck. The method first measures the traffic flow operational similarity between pairs of neighboring links, and then the similarity results are used to cluster the spatial-temporal congestion. In order to get the similarity under missing data condition, the measurement is implemented in a two-stage manner: firstly the so called first order similarity is calculated given that the traffic flow variables are bounded both upside and downside; then the first order similarity is aggregated to generate the second order similarity as the output. We implement the method on part of the real-world road network; the results generated are not only consistent with empirical observation, but also provide useful insights.

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The Businesses That Platforms Are Actually Disrupting

Platforms are all the rage these days. Powered by online technologies, they are sweeping across the economic landscape, striking down companies large and small. Uber’s global assault on the taxi industry is well known. Many platforms, some household names and others laboring in obscurity, are doing the same in other sectors.

Surveying these changes, you might conclude that if your business isn’t a platform, you had better worry that one is coming your way. Everyone from automakers to plumbers should count their days as traditional businesses. And maybe you should jump on the platform bandwagon too. If it worked for Airbnb, why not you?

Based on our research into the wave of online platforms that have started in the last two decades, we don’t necessarily disagree. Traditional businesses should worry, and maybe they should think about platform strategies. But we think these conclusions are overwrought — and miss what’s really going on.
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The Computational Properties of a Simplified Cortical Column Model

The Computational Properties of a Simplified Cortical Column Model | Social Foraging | Scoop.it
The mammalian neocortex has a repetitious, laminar structure and performs functions integral to higher cognitive processes, including sensory perception, memory, and coordinated motor output. What computations does this circuitry subserve that link these unique structural elements to their function? Potjans and Diesmann (2014) parameterized a four-layer, two cell type (i.e. excitatory and inhibitory) model of a cortical column with homogeneous populations and cell type dependent connection probabilities. We implement a version of their model using a displacement integro-partial differential equation (DiPDE) population density model. This approach, exact in the limit of large homogeneous populations, provides a fast numerical method to solve equations describing the full probability density distribution of neuronal membrane potentials. It lends itself to quickly analyzing the mean response properties of population-scale firing rate dynamics. We use this strategy to examine the input-output relationship of the Potjans and Diesmann cortical column model to understand its computational properties. When inputs are constrained to jointly and equally target excitatory and inhibitory neurons, we find a large linear regime where the effect of a multi-layer input signal can be reduced to a linear combination of component signals. One of these, a simple subtractive operation, can act as an error signal passed between hierarchical processing stages.

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SantaFe Institute: Networks, AI, and social psychology for social change

SantaFe Institute: Networks, AI, and social psychology for social change | Social Foraging | Scoop.it
Influencing social change on a broad scale is a chronically difficult problem. But what if you could identify – and then target and train at exactly the right time – those members of a population most likely to have the greatest influence on their peers?
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Google AdWords New Machine Learning Based Smart Bidding

Google AdWords New Machine Learning Based Smart Bidding | Social Foraging | Scoop.it


Everything at Google is going the way of machine learning, not just the searc
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Advanced Algorithms for Local Routing Strategy on Complex Networks

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets R c increases by over ten-fold and the average transmission time ⟨ T ⟩ decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks.
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The Store Of The Future: 72 Startups Transforming Bricks-And-Mortar Retail In One Infographic

The Store Of The Future: 72 Startups Transforming Bricks-And-Mortar Retail In One Infographic | Social Foraging | Scoop.it
Transforming bricks-and-mortar shopping is a high-stakes endeavor for retailers given Americans still do over 90% of our shopping in physical stores. In fact, one of the latest trends in retail is the launch of physical stores by online e-commerce companies, including Amazon, Warby Parker, and Birchbox.

Dozens of startups have taken on the challenge of helping retailers bridge the gap between digital and physical commerce through features ranging from shelf-stocking robots, to augmented reality displays, to Wi-Fi based beacons that collect data on shopper behavior.

Using CB Insights data, we identified startups enhancing the in-store experience with digital tools. The startups in our list have racked up partnerships with many big name brands — including Maybelline, Lancome, Kiehl’s, Cabela’s, Foot Locker, Home Depot, Express — and department stores, from Lord & Taylor to Target.
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