Social Foraging
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# The Language of Game Theory : Putting Epistemics into the Mathematics of Games (by Adam Brandenburger)

### The Language of Game Theory : Putting Epistemics into the Mathematics of Games (World Scientific Series in Economic Theory)

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This volume contains eight papers written by Adam Brandenburger and his co-authors over a period of 25 years. These papers are part of a program to reconstruct game theory in order to make how players reason about a game a central feature of the theory. The program now called epistemic game theory extends the classical definition of a game model to include not only the game matrix or game tree, but also a description of how the players reason about one another (including their reasoning about other players' reasoning). With this richer mathematical framework, it becomes possible to determine the implications of how players reason for how a game is played. Epistemic game theory includes traditional equilibrium-based theory as a special case, but allows for a wide range of non-equilibrium behavior.

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# Social Foraging

Dynamics of Social Interaction
Curated by Ashish Umre
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## Eagle's Wings Inspire More Fuel Efficient Planes

"[...] The wing tips of steppe eagles are an ideal shape to maximize lift with a minimal wingspan. The curvature at the end of the wing reduces drag. Engineers designing the A380 copied that design, resulting in fuel savings of up to 3%, depending on if it is a long or short distance flight."

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## Not too fast, but not too slow: searching strategies to beat a majority group of interacting walkers

We introduce a model of interacting random walkers on a finite one-dimensional chain with absorbing boundaries or targets at the ends. Walkers are of two types: informed particles that move ballistically towards a given target, and diffusing uniformed particles that are biased towards close informed particles. This model mimics the dynamics of animals searching for food, where an informed individual knows the location of a food target and tries to persuade close-by uninformed conspecifics to go to that target. We characterize the success of this persuasion by the first-passage probability of the uniformed particle to the target, and we interpret the speed of the informed particle as a strategic parameter that the particle tunes to maximize its success. We find that the success probability is non-monotonic, reaching its maximum at an intermediate speed that increases with the diffusing rate of the uniformed particle. When two different groups of informed particles traveling in opposite directions compete, usually the largest group is the most successful. However, the minority can reverse this situation and become the most probable winner by following two different strategies: increasing its attraction strength and adjusting its speed to an optimal value relative to the majority's speed.

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## Exact solution for a metapopulation version of Schelling’s model

In 1971, Schelling introduced a model in which families move if they have too many neighbors of the opposite type. In this paper, we will consider a metapopulation version of the model in which a city is divided into Nneighborhoods, each of which has L houses. There are ρNL red families and ρNL blue families for some ρ < 1/2. Families are happy if there are ≤ρcL families of the opposite type in their neighborhood and unhappy otherwise. Each family moves to each vacant house at rates that depend on their happiness at their current location and that of their destination. Our main result is that if neighborhoods are large, then there are critical values ρb < ρd < ρc, so that for ρ < ρb, the two types are distributed randomly in equilibrium. When ρ > ρb, a new segregated equilibrium appears; for ρb < ρ < ρd, there is bistability, but when ρ increases past ρd the random state is no longer stable. When ρc is small enough, the random state will again be the stationary distribution when ρ is close to 1/2. If so, this is preceded by a region of bistability.

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 Rescooped by Ashish Umre from Papers

## How structurally stable are global socioeconomic systems?

The stability analysis of socioeconomic systems has been centred on answering whether small perturbations when a system is in a given quantitative state will push the system permanently to a different quantitative state. However, typically the quantitative state of socioeconomic systems is subject to constant change. Therefore, a key stability question that has been under-investigated is how strongly the conditions of a system itself can change before the system moves to a qualitatively different behaviour, i.e. how structurally stable the systems is. Here, we introduce a framework to investigate the structural stability of socioeconomic systems formed by a network of interactions among agents competing for resources. We measure the structural stability of the system as the range of conditions in the distribution and availability of resources compatible with the qualitative behaviour in which all the constituent agents can be self-sustained across time. To illustrate our framework, we study an empirical representation of the global socioeconomic system formed by countries sharing and competing for multinational companies used as proxy for resources. We demonstrate that the structural stability of the system is inversely associated with the level of competition and the level of heterogeneity in the distribution of resources. Importantly, we show that the qualitative behaviour of the observed global socioeconomic system is highly sensitive to changes in the distribution of resources. We believe that this work provides a methodological basis to develop sustainable strategies for socioeconomic systems subject to constantly changing conditions.

How structurally stable are global socioeconomic systems?
Serguei Saavedra, Rudolf P. Rohr, Luis J. Gilarranz, Jordi Bascompte

http://dx.doi.org/10.1098/ rsif.2014.0693
J. R. Soc. Interface 6 November 2014 vol. 11 no. 100 20140693

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Eli Levine's curator insight,

There are most likely a plurality of stable socio-economic systems with different dynamics and levels of short term system stability.  It's likely that, even if there are periods of short term instability, that long term stability will hold, even if instability is a stable feature.

Very interesting points here.

Enjoy!

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## Modeling the evolution of programming languages

Darwin’s notion of natural selection is undoubtedly one of the most important ideas in the history of science. Powerful as it is, explaining a great deal of the complexities intrinsic to biology, many wonder if the same or some similarly elegant idea could be used to explain cultural change as well. Darwin himself was interested in the relation between natural and human-driven change. Although many ideas from evolutionary biology have been applied in studying cultural change, there’s still a lot of debate as to whether natural and cultural phenomena evolve similarly. One of the reasons why the debate persists is that it is not easy to compare and tell definitely where and how the two differ, because cultural evolution and technological innovation have not been modelled as extensively as biological change. This is mainly because cultural phenomena lack a “genome” that would serve as a change measure, with the exception of natural language for which researchers in formal linguistics have devised more than several metrics accounting for grammatical, pragmatic, phonetic, orthographic and semantic changes. Other cultural phenomena, such as technological innovation, are much more difficult to quantify and measure adequately. That is why Sergi Valverde and Ricard Solé of Santa
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 Rescooped by Ashish Umre from Papers

## The dilemma of statistics: Rigorous mathematical methods cannot compensate messy interpretations and lousy data

Statistics, although being indispensable in present day science and society has a bad reputation, in particular, in public. This can hardly be expressed in a better way than in the famous well-known quotation:
There are three kinds of lies: Lies, damned lies, and statistics. 1
It would be unfair not to make an attempt to restore the image of statistics and I try to do this in part by means of another citation.
While it is easy to lie with statistics, it is even easier to lie without them.
This quote is attributed to Frederick Mosteller [1]. Both citations are built undoubtedly on the association of statistics with telling lies and it is worth asking why statisticians have such a bad image. I feel there are two main reasons for it: (...)

The dilemma of statistics: Rigorous mathematical methods cannot compensate messy interpretations and lousy data
Peter Schuster
http://dx.doi.org/10.1002/cplx.21553

Complexity
Volume 20, Issue 1, pages 11–15, September/October 2014

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## Symbolic regression of generative network models

Networks are a powerful abstraction with applicability to a variety of scientific fields. Models explaining their morphology and growth processes permit a wide range of phenomena to be more systematically analysed and understood. At the same time, creating such models is often challenging and requires insights that may be counter-intuitive. Yet there currently exists no general method to arrive at better models. We have developed an approach to automatically detect realistic decentralised network growth models from empirical data, employing a machine learning technique inspired by natural selection and defining a unified formalism to describe such models as computer programs. As the proposed method is completely general and does not assume any pre-existing models, it can be applied “out of the box” to any given network. To validate our approach empirically, we systematically rediscover pre-defined growth laws underlying several canonical network generation models and credible laws for diverse real-world networks. We were able to find programs that are simple enough to lead to an actual understanding of the mechanisms proposed, namely for a simple brain and a social network.

Symbolic regression of generative network models
• Telmo Menezes & Camille Roth

Scientific Reports 4, Article number: 6284 http://dx.doi.org/10.1038/srep06284

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Flora Moon's curator insight,

Big data meets systems and can potentially shines a light on system dynamics....

 Rescooped by Ashish Umre from Talks

## Self-organizing Intelligent Network of UAVs

This video explains our research on autonomous unmanned aerial vehicles (UAVs). The research team at the Alpen-Adria University and Lakeside Labs developing a multi-UAV system by four key components: - the multiple UAV platforms,

http://youtu.be/QX2UPkd6yIc

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## A/B Testing the Untestable in Checkout

92% of merchants participating in the e-tailing group’s 16th Annual Merchant Survey ranked A/B, multi-variate or other usability testing as most or somewhat important merchandising tactic for customer retention (second only to web analytics).

While testing the small stuff like button color, headline copy, can get reasonable lift, often the most impressive gains come from bigger changes – new approaches to layout, radical redesigns that fix multiple conversion speed bumps and, of more recent popularity, responsive design.

And it’s often recommended to start A/B testing your checkout process before tackling other areas of your site, as visitors that get as far as

your checkout are closest to conversion.

The trouble is, many marketers face limitations in fully testing the

checkout process.

Both IT requirements and technology can be roadblocks. Even if you enjoy the luxury of dedicated IT, the time it takes to make such changes is costly.

Your testing tool and ecommerce platforms may only support simple changes like button colors, headlines, images, and relatively simple layout adjustments. Test that typically yield bigger results require more effort.

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## 3 strategies for developing the data-driven retail store

Tracking customers through today’s data-driven shopping journey provides retailers a fresh take on doing business and the chance to deliver the best customer experience and build loyalty.

The retail store has traditionally been a destination inviting footfalls and converting them to transactions. Today, however, consumers do not engage with stores in this type of linear fashion, as they are always connected to the store. Many see the constantly distracted consumer and the abundance of choice across channels as threats to traditional retail. However, tracking customers on their journey provides new opportunities to retailers to engage with customers and achieve their business goals.

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## Miller experiments in atomistic computer simulations

In 1953, Stanley Miller reported on the spontaneous formation of glycine when applying an electric discharge on a mixture of simple molecules, giving birth to modern research on the origins of life. The effect of electric fields on mixtures of simple molecules is presently studied in computer simulations at the quantum level, and Miller results are reproduced for the first time, to our knowledge, in atomistic simulations, as glycine forms spontaneously only in the presence of electric fields. However, this occurs through reaction pathways more complex than believed, identifying formamide as a key compound in prebiotic chemistry. Moreover, electric fields are naturally present at mineral surfaces, suggesting a potentially crucial role in the biogeochemistry of both the primordial and the modern Earth.

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## Complex network theory and the brain

We have known for at least 100 years that a brain is organized as a network of connections between nerve cells. But in the last 10 years there has been a rapid growth in our capacity to quantify the complex topological pattern of brain connectivity, using mathematical tools drawn from graph theory.
Here we bring together articles and reviews from some of the world’s leading experts in contemporary brain network analysis by graph theory. The contributions are focused on three big questions that seem important at this stage in the scientific evolution of the field: How does the topology of a brain network relate to its physical embedding in anatomical space and its biological costs? How does brain network topology constrain brain dynamics and function? And what seem likely to be important future methodological developments in the application of graph theory to analysis of brain networks?
Clearer understanding of the principles of brain network organization is fundamental to understanding many aspects of cognitive function, brain development and clinical brain disorders. We hope this issue provides a forward-looking window on this fast moving field and captures some of the excitement of recent progress in applying the concepts of graph theory to measuring and modeling the complexity of brain networks.

Complex network theory and the brain
Issue compiled and edited by David Papo, Javier M. Buldú, Stefano Boccaletti and Edward T. Bullmore

http://rstb.royalsocietypublishing.org/site/2014/network.xhtml

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## The Merits of Unconscious Thought in Rule Detection - Unconscious Decision Making

According to unconscious thought theory (UTT), unconscious thought is more adept at complex decision-making than is conscious thought. Related research has mainly focused on the complexity of decision-making tasks as determined by the amount of information provided. However, the complexity of the rules generating this information also influences decision making. Therefore, we examined whether unconscious thought facilitates the detection of rules during a complex decision-making task. Participants were presented with two types of letter strings. One type matched a grammatical rule, while the other did not. Participants were then divided into three groups according to whether they made decisions using conscious thought, unconscious thought, or immediate decision. The results demonstrated that the unconscious thought group was more accurate in identifying letter strings that conformed to the grammatical rule than were the conscious thought and immediate decision groups. Moreover, performance of the conscious thought and immediate decision groups was similar. We conclude that unconscious thought facilitates the detection of complex rules, which is consistent with UTT.

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## Culturomics: Quantitative Analysis of Culture Using Millions of Digitized Books

Construct a corpus of digitized texts containing about 4% of all books ever printed, and then analyze that corpus using advanced software and the investigato...
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## Mathematics Online: Wolfram Brings Mathematica Technical Computing to the Web

If you’re a fan of Wolfram’s Mathematica app, you’ll be pleased to hear its comprehensive tools for technical computing are now more accessible. For the first time, Mathematica is available on the Web.

While the desktop applications (Windows, Mac and Linux) remain unaltered, Wolfram is introducing a browser-based version called Mathematica Online that can be accessed from any internet-enabled device.

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Over 500 million people interact daily with Facebook. Yet, whether Facebook use influences subjective well-being over time is unknown. We addressed this issue using experience-sampling, the most reliable method for measuring in-vivo behavior and psychological experience. We text-messaged people five times per day for two-weeks to examine how Facebook use influences the two components of subjective well-being: how people feel moment-to-moment and how satisfied they are with their lives. Our results indicate that Facebook use predicts negative shifts on both of these variables over time. The more people used Facebook at one time point, the worse they felt the next time we text-messaged them; the more they used Facebook over two-weeks, the more their life satisfaction levels declined over time. Interacting with other people “directly” did not predict these negative outcomes. They were also not moderated by the size of people's Facebook networks, their perceived supportiveness, motivation for using Facebook, gender, loneliness, self-esteem, or depression. On the surface, Facebook provides an invaluable resource for fulfilling the basic human need for social connection. Rather than enhancing well-being, however, these findings suggest that Facebook may undermine it.

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Our identities are prismatic. We’re not the same person to everyone. Yet when you follow someone on Twitter, your feed overflows with a combination of their personal, professional, and social tweets. But thanks to TechCrunch Disrupt Hackathon project Persona, you can choose which dimensions of someone’s identity you want to see. Persona uses machine learning to classify people’s tweets into separate themed timelines around different topics they tweet about, like their work, personal life, and interests.

If you ever wished you could just get someone’s smart professional insights without knowing what they had for lunch, or love their taste in art but yawn when they nerd out on tech or current events, Persona could banish boring tweets from your feed.

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 Rescooped by Ashish Umre from Influence et contagion

## Knowledge Sharing #Tools and #Methods Toolkit - #SNA

"Social network analysis is the mapping and measuring of relationships and flows between people, groups, organisations, computers or other information/knowledge processing entities." (Valdis Krebs, 2002). Social Network Analysis (SNA) is a method for visualizing our people and connection power, leading us to identify how we can best interact to share knowledge.

Via jean lievens, Nevermore Sithole, João Greno Brogueira, luiy
luiy's curator insight,

When to use:Visualize relationships within and outside of the organization.Facilitate identification of who knows who and who might know what - teams and individuals playing central roles - thought leaders, key knowledge brokers, experts, etc.Identify isolated teams or individuals and knowledge bottlenecks.Strategically work to improve knowledge flows.Accelerate the flow of knowledge and information across functional and organisational boundaries.Improve the effectiveness of formal and informal communication channels.Raise awareness of the importance of informal networks.

Karen du Toit's curator insight,

A great wiki to check out about social network analysis

 Rescooped by Ashish Umre from Papers

## Dynamic Homeostasis in Packet Switching Networks

In this study, we investigate the adaptation and robustness of a packet switching network (PSN), the fundamental architecture of the Internet. We claim that the adaptation introduced by a transmission control protocol (TCP) congestion control mechanism is interpretable as the self-organization of multiple attractors and stability to switch from one attractor to another. To discuss this argument quantitatively, we study the adaptation of the Internet by simulating a PSN using ns-2. Our hypothesis is that the robustness and fragility of the Internet can be attributed to the inherent dynamics of the PSN feedback mechanism called the congestion window size, or \textit{cwnd}. By varying the data input into the PSN system, we investigate the possible self-organization of attractors in cwnd temporal dynamics and discuss the adaptability and robustness of PSNs. The present study provides an example of Ashby's Law of Requisite Variety in action.

Dynamic Homeostasis in Packet Switching Networks
Mizuki Oka, Hirotake Abe, Takashi Ikegami

http://arxiv.org/abs/1409.1533

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Business mergers and acquisitions bring about significant imbalances in the functioning of economic systems, and the threat of monopoly looms large, according to a new analysis of economic data published in Proceedings of the Royal Society A.

Drawing approaches from complexity and evolutionary biology -- and analyzing historical business data from a variety of industries and geographies and from the 1830s to the present -- SFI Distinguished Professor Geoffrey West and colleagues from Imperial College London and PricewaterhouseCoopers show that the cumulative history of mergers and acquisitions of companies (i.e. ancestry) is a key characteristic underpinning the dynamics of business ecosystems.

They conclude that a universal mechanism leads to imbalanced business ecosystems in which a few very large but sluggish “too big to fail” entities, and very small niche entities prevail.

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## The Leverage Effect on Wealth Distribution in a Controllable Laboratory Stock Market

Wealth distribution has always been an important issue in our economic and social life, since it affects the harmony and stabilization of the society. Under the background of widely used financial tools to raise leverage these years, we studied the leverage effect on wealth distribution of a population in a controllable laboratory market in which we have conducted several human experiments, and drawn the conclusion that higher leverage leads to a higher Gini coefficient in the market. A higher Gini coefficient means the wealth distribution among a population becomes more unequal. This is a result of the ascending risk with growing leverage level in the market plus the diversified trading abilities and risk preference of the participants. This work sheds light on the effects of leverage and its related regulations, especially its impact on wealth distribution. It also shows the capability of the method of controllable laboratory markets which could be helpful in several fields of study such as economics, econophysics and sociology.

The Leverage Effect on Wealth Distribution in a Controllable Laboratory Stock Market

Zhu C, Yang G, An K, Huang J

PLoS ONE 9(6): e100681. (2014)

http://dx.doi.org/10.1371/journal.pone.0100681

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## Consumers Spent 75% Of The Time On Top 4 Apps [bigMobility]

There was a time when desktop was considered to be the most used medium for the world to connect online. But with increasing adoption of smartphones in recent times, this trend has changed and now mobile phones and tablets dominate the digital connectivity. Last year US became a multi-platform majority with user digital consumption being mainly through mobile phones and tablets every month. The same year, mobile usage crossed desktop usage in terms of total digital media engagement. This year saw a new development – APP MAJORITY – where now the majority of all digital media time spent occurs on mobile apps.

This was an expected phenomenon as apps have allowed users to attain a great deal of real life fulfillment such as hailing a cab, checking weather, purchase of commodities etc or for digital fulfillment to post an update on Facebook, stream videos or watch movies.. These apps drive the mobile digital consumption and is where most of the device’s utility comes from.

Although engagement is higher on mobile, advertising on this platform has not made it big yet. But as seen in every previous development, money follows eyeballs and hence mobile app economy  will have a bright future.

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## Synchronization in human musical rhythms and mutually interacting complex systems

Though the statistical properties of musical compositions have been widely studied, little is known about the statistical nature of musical interaction—a foundation of musical communication. The goal of this study was to uncover the general statistical properties underlying musical interaction by observing two individuals synchronizing rhythms. We found that the interbeat intervals between individuals exhibit scale-free cross-correlations, i.e., the next beat played by an individual is dependent on the entire history (up to several minutes) of their partner’s interbeat intervals. To explain this surprising observation, we introduce a general stochastic model that can also be used to study synchronization phenomena in econophysics and physiology. The scaling laws found in musical interaction are directly applicable to audio production.

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## Using Cellular Automata for Parking Recommendations in Smart Environments

In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space.

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## Evaluating sentiment in financial news articles

Can the choice of words and tone used by the authors of financial news articles correlate to measurable stock price movements? If so, can the magnitude of price movement be predicted using these same variables? We investigate these questions using the Arizona Financial Text (AZFinText) system, a financial news article prediction system, and pair it with a sentiment analysis tool. Through our analysis, we found that subjective news articles were easier to predict in price direction (59.0% versus 50.0% of chance alone) and using a simple trading engine, subjective articles garnered a 3.30% return. Looking further into the role of author tone in financial news articles, we found that articles with a negative sentiment were easiest to predict in price direction (50.9% versus 50.0% of chance alone) and a 3.04% trading return. Investigating negative sentiment further, we found that our system was able to predict price decreases in articles of a positive sentiment 53.5% of the time, and price increases in articles of a negative sentiment 52.4% of the time. We believe that perhaps this result can be attributable to market traders behaving in a contrarian manner, e.g., see good news, sell; see bad news, buy.

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