Complexity & Systems
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Complexity & Systems
Complex systems present problems both in mathematical modelling and philosophical foundations. The study of complex systems represents a new approach to science that investigates how relationships between parts give rise to the collective behaviors of a system and how the system interacts and forms relationships with its environment. The equations from which models of complex systems are developed generally derive from statistical physics, information theory and non-linear dynamics, and represent organized but unpredictable behaviors of natural systems that are considered fundamentally complex.  wikipedia (en)
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Homophily and the Speed of Social Mobilization: The Effect of Acquired and Ascribed Traits

Large-scale mobilization of individuals across social networks is becoming increasingly prevalent in society. However, little is known about what affects the speed of social mobilization. Here we use a framed field experiment to identify and measure properties of individuals and their relationships that predict mobilization speed. We ran a global social mobilization contest and recorded personal traits of the participants and those they recruited. We studied the effects of ascribed traits (gender, age) and acquired traits (geography, and information source) on the speed of mobilization. We found that homophily, a preference for interacting with other individuals with similar traits, had a mixed role in social mobilization. Homophily was present for acquired traits, in which mobilization speed was faster when the recuiter and recruit had the same trait compared to different traits. In contrast, we did not find support for homophily for the ascribed traits. Instead, those traits had other, non-homophily effects: Females mobilized other females faster than males mobilized other males. Younger recruiters mobilized others faster, and older recruits mobilized slower. Recruits also mobilized faster when they first heard about the contest directly from the contest organization, and decreased in speed when hearing from less personal source types (e.g. family vs. media). These findings show that social mobilization includes dynamics that are unlike other, more passive forms of social activity propagation. These findings suggest relevant factors for engineering social mobilization tasks for increased speed.

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Social Evolution: New Horizons

Cooperation is a widespread natural phenomenon yet current evolutionary thinking is dominated by the paradigm of selfish competition. Recent advanced in many fronts of Biology and Non-linear Physics are helping to bring cooperation to its proper place. In this contribution, the most important controversies and open research avenues in the field of social evolution are reviewed. It is argued that a novel theory of social evolution must integrate the concepts of the science of Complex Systems with those of the Darwinian tradition. Current gene-centric approaches should be reviewed and com- plemented with evidence from multilevel phenomena (group selection), the constrains given by the non-linear nature of biological dynamical systems and the emergent nature of dissipative phenomena.

 

Chapter in forthcoming open access book "Frontiers in Ecology, Evolution and Complexity"

by Octavio Miramontes, Og DeSouza

arXiv:1404.6267 [q-bio.PE]


Via NESS
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Eli Levine's curator insight, April 28, 2014 8:14 PM

Indeed, one example of this cooperative method in evolution that springs to mind is the coevolution of dogs and humans.  By being domesticated, dogs earned themselves protection from the elements and a reliable source of food, water and even medical care in case of injury.  Humans gained more sleep, due to the watchfulness of dogs at night, and thus, gained a greater degree of cognitive functionality that otherwise wouldn't have existed had dogs not been kept with us.

 

Sometimes, the cooperative option is the selfish option, and vice versa.

 

Imagine if political leaders, rather than competing with each other for relative power and pride within the society, worked together to solve actual common problems in our society?  What if nations worked together to solve common problems in humanity, amongst humanity, sucht that we're focused on survival and well being, rather than wealth or relative power?

 

What is so difficult and onerous about these changes?

 

I don't understand.

 

Think about it.

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Allometric Relations and Scaling Laws for the Cardiovascular System of Mammals

Allometric Relations and Scaling Laws for the Cardiovascular System of Mammals | Complexity & Systems | Scoop.it
The modeling of the cardiovascular system of mammals is discussed within the framework of governing allometric relations and related scaling laws for mammals.
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Measuring the Complexity of Self-Organizing Traffic Lights

We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.

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John Niles's curator insight, April 28, 2014 4:04 AM

USDOT works to educate traffic engineers on adaptive traffic signals.  http://www.nc-ite.org/images/files/Adaptive%20Signal%20Control%20Technology%20Overview%20Presentation.pdf

 

This paper provides insight into difficulty. Adaptive traffic signal timing is not commonly implemented in U.S. urban areas.


If vehicles were to communicate with traffic signals, another layer of complexity would be added.

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Resilience of modular complex networks

Complex networks often have a modular structure, where a number of tightly- connected groups of nodes (modules) have relatively few interconnections. Modularity had been shown to have an important effect on the evolution and stability of biological networks, on the scalability and efficiency of large-scale infrastructure, and the development of economic and social systems. An analytical framework for understanding modularity and its effects on network vulnerability is still missing. Through recent advances in the understanding of multilayer networks, however, it is now possible to develop a theoretical framework to systematically study this critical issue. Here we study, analytically and numerically, the resilience of modular networks under attacks on interconnected nodes, which exhibit high betweenness values and are often more exposed to failure. Our model provides new understandings into the feedback between structure and function in real world systems, and consequently has important implications as diverse as developing efficient immunization strategies, designing robust large-scale infrastructure, and understanding brain function.

 

Resilience of modular complex networks
Saray Shai, Dror Y. Kenett, Yoed N. Kenett, Miriam Faust, Simon Dobson, Shlomo Havlin

http://arxiv.org/abs/1404.4748


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Dynamics of Information Spreading in Online Social Networks

 Online social networks (OSNs) are changing the way information spreads throughout the Internet. A deep understanding of information spreading in OSNs leads to both social and commercial benefits. In this paper, dynamics of information spreading (e.g., how fast and widely the information spreads against time) in OSNs are characterized, and a general and accurate model based on Interactive Markov Chains (IMCs) and mean-field theory is established. This model shows tight relations between network topology and information spreading in OSNs, e.g., the information spreading ability is positively related to the heterogeneity of degree distributions whereas negatively related to the degree-degree correlations in general. Further, the model is extended to feature the time-varying user behavior and the ever-changing information popularity. By leveraging the mean-field theory, the model is able to characterize the complicated information spreading process (e.g., the dynamic patterns of information spreading) with six parameters. Extensive evaluations based on Renren's data set illustrate the accuracy of the model, e.g., it can characterize dynamic patterns of video sharing in Renren precisely and predict future spreading dynamics successfully.

Bernard Ryefield's insight:

updated Apr 24 : http://arxiv.org/abs/1404.5562v2

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Air traffic complexity based on non linear dynamical systems

Air traffic complexity based on non linear dynamical systems | Complexity & Systems | Scoop.it
This paper presents a new air traffic complexity metric based on non-linear dynamical systems. The goal of this metric is to identify any trajectory organisation in the traffic pattern in order to quantify the associated control difficulty.
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Institute for Complex System Simulations (Home page)


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Topics in social network analysis and network science

This chapter introduces statistical methods used in the analysis of social networks and in the rapidly evolving parallel-field of network science. Although several instances of social network analysis in health services research have appeared recently, the majority involve only the most basic methods and thus scratch the surface of what might be accomplished. Cutting-edge methods using relevant examples and illustrations in health services research are provided.

by A. James O'Malley, Jukka-Pekka Onnela

arXiv:1404.0067 [physics.soc-ph]


Via NESS, Complejidady Economía
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Eli Levine's curator insight, April 16, 2014 11:08 PM

A very cool and comprehensive look at how networks can be analyzed, studied and examined.

 

Way cool science!

 

Think about it.

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Pattern and Process | Spatial Simulation: Exploring Pattern and Process

Pattern and Process | Spatial Simulation: Exploring Pattern and Process | Complexity & Systems | Scoop.it

Across broad areas of the environmental and social sciences, simulation models are an important way to study systems inaccessible to scientific experimental and observational methods, and also an essential complement of those more conventional approaches.  The contemporary research literature is teeming with abstract simulation models whose presentation is mathematically demanding and requires a high level of knowledge of quantitative and computational methods and approaches.  Furthermore, simulation models designed to represent specific systems and phenomena are often complicated, and, as a result, difficult to reconstruct from their descriptions in the literature.  Spatial Simulation: Exploring Pattern and Process aims to provide a practical and accessible account of dynamic spatial modelling, while also equipping readers with a sound conceptual foundation in the subject, and a useful introduction to the wide-ranging literature.

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A signature of power law network dynamics

Can one hear the 'sound' of a growing network? We address the problem of recognizing the topology of evolving biological or social networks. Starting from percolation theory, we analytically prove a linear inverse relationship between two simple graph parameters--the logarithm of the average cluster size and logarithm of the ratio of the edges of the graph to the theoretically maximum number of edges for that graph--that holds for all growing power law graphs. The result establishes a novel property of evolving power-law networks in the asymptotic limit of network size. Numerical simulations as well as fitting to real-world citation co-authorship networks demonstrate that the result holds for networks of finite sizes, and provides a convenient measure of the extent to which an evolving family of networks belongs to the same power-law class.

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Center for Complex Networks and Systems Research

Center for Complex Networks and Systems Research | Complexity & Systems | Scoop.it

Via Bryan A. Knowles
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Swarm Intelligence Based Algorithms: A Critical Analysis

Many optimization algorithms have been developed by drawing inspiration from swarm intelligence (SI). These SI-based algorithms can have some advantages over traditional algorithms. In this paper, we carry out a critical analysis of these SI-based algorithms by analyzing their ways to mimic evolutionary operators. We also analyze the ways of achieving exploration and exploitation in algorithms by using mutation, crossover and selection. In addition, we also look at algorithms using dynamic systems, self-organization and Markov chain framework. Finally, we provide some discussions and topics for further research.

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Stochastic modeling of a serial killer

We analyze the time pattern of the activity of a serial killer, who during twelve years had murdered 53 people. The plot of the cumulative number of murders as a function of time is of "Devil's staircase" type. The distribution of the intervals between murders (step length) follows a power law with the exponent of 1.4. We propose a model according to which the serial killer commits murders when neuronal excitation in his brain exceeds certain threshold. We model this neural activity as a branching process, which in turn is approximated by a random walk. As the distribution of the random walk return times is a power law with the exponent 1.5, the distribution of the inter-murder intervals is thus explained. We illustrate analytical results by numerical simulation. Time pattern activity data from two other serial killers further substantiate our analysis.

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The Difference Between Complex and Complicated, And Why It Matters | Sam McNerney

The Difference Between Complex and Complicated, And Why It Matters | Sam McNerney | Complexity & Systems | Scoop.it
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A combined nelder-mead simplex and genetic algorithm

A combined nelder-mead simplex and genetic algorithm | Complexity & Systems | Scoop.it
It is usually said that genetic algorithm should be used when nothing else works. In practice, genetic algorithm are very often used for large sized global optimization problems, but are not very efficient for local optimization problems.
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Adaptive Cluster Synchronization of Directed Complex Networks with Time Delays

Adaptive Cluster Synchronization of Directed Complex Networks with Time Delays | Complexity & Systems | Scoop.it

This paper studied the cluster synchronization of directed complex networks with time delays. It is different from undirected networks, the coupling configuration matrix of directed networks cannot be assumed as symmetric or irreducible. In order to achieve cluster synchronization, this paper uses an adaptive controller on each node and an adaptive feedback strategy on the nodes which in-degree is zero. Numerical example is provided to show the effectiveness of main theory. This method is also effective when the number of clusters is unknown. Thus, it can be used in the community recognizing of directed complex networks.

 

 

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Chaotic and non-chaotic phases in experimental responses of a single neuron

Consistency and predictability of brain functionalities depend on reproducible activity of a single neuron. We identify a reproducible non-chaotic neuronal phase where deviations between concave response latency profiles of a single neuron do not increase with the number of stimulations. A chaotic neuronal phase emerges at a transition to convex latency profiles which diverge exponentially, indicating irreproducible response timings. Our findings are supported by a quantitative mathematical framework and found robust to periodic and random stimulation patterns. In addition, these results put a bound on the neuronal temporal resolution which can be enhanced below a millisecond using neuronal chains.

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Complexity Digest joins Complex Systems Society

It is my pleasure to announce that Complexity Digest has become the official news channel of the the Complex Systems Society (CSS). We trust that this merger will service the growing number of people interested in the scientific study of complex systems.

 

We will continue offering our services for free. The scope of the content should be more varied, as more people become involved editing material for ComDig. This will be a gradual process which should benefit both members and non-members of the CSS.

 

The first change has been the logo of ComDig, which is in line with the new CSS logo. Further changes will continue in coming months.

 

Complex wishes,

Carlos Gershenson

Editor-in-Chief


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What’s the use of “econo-physics”? — The Physics of Finance — Medium

What’s the use of “econo-physics”? — The Physics of Finance — Medium | Complexity & Systems | Scoop.it

About 20 years ago, a few physicists got interested in applying some ideas and concepts from physics to problems in finance and economics. The area is sometimes called "econophysics" – I actually don't like the name – and it tends to be controversial. Some economists find it annoying, although a few others either work in the area or do work that is closely associated conceptually. On occasion, you'll find people suggesting that research in econophysics has never achieved anything worthwhile (this was seven years ago, and that writer may possibly have changed his mind by now).

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Flow, Conflux | Smart Cities

Flow, Conflux | Smart Cities | Complexity & Systems | Scoop.it

“The city is not only a community, it is a conflux. ….The real city, as a center of industry, is a conflux of streams of traffic; as a center of culture, it is conflux of streams of thought.” So wrote Benton MacKaye in 1928 in his book The New Exploration: A Philosophy of Regional Planning. When I sent a copy of my own recent book The New Science of Cities to my erstwhile colleague and old friend Lionel March, he quickly scowered it and said: “I see in your Preamble that you cite Castells’ ‘space of flows’ and that your approach makes much of flows and networks. I immediately turned to your bibliography to search for the name Benton MacKaye. It is not there! The author of The New Exploration (1928) is my hero of metropolitan/regional development. I’m sure you know of him”.

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Eli Levine's curator insight, April 17, 2014 5:00 PM

Location, location, location.

 

The natural geography has to fit with the demands of the population and the society.  It's not something that someone on high chooses, but rather one where things grow up naturally according to the relative advantages and disadvantages of the area.  Then you build and with building in these geographically advantageous (or, sometimes, just convenient) areas you reinforce their advantages as centers of commerce, trade and "flows" as Batty would put it.

 

It makes sense to have it be on the regional, national and/or international scale, such that we, as humans, take advantage of the most strategic places and the most strategic resources that are available.  With this comes the flourishing of new life, happiness and possible/hopefully sustainable prosperity for the present and for the future well being of our civilizations.

 

The climate is changing and that's going to force a lot of changes on our part.  If we can survive the environmental tumult, and the economic and social tumult that it is going to cause, we could potentially, get off on a better footing than before, in spite of the losses which we incur as a result of the present silliness of our political, social and economic "leadership".

 

Good stuff!

 

Think about it.

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Complex Thinking for a Complex World – About Reductionism, Disjunction and Systemism | Morin | Systema: connecting matter, life, culture and technology

Complex Thinking for a Complex World – About Reductionism, Disjunction and Systemism | Morin | Systema: connecting matter, life, culture and technology | Complexity & Systems | Scoop.it

This article is based on the keynote address presented to the European Meetings on Cybernetics and Systems Research (EMCSR) in 2012, on the occasion of Edgar Morin receiving the Bertalanffy Prize in Complexity Thinking, awarded by the Bertalanffy Centre for the Study of Systems Science(BCSSS).

The following theses will be elaborated on: (a) The whole is at the same time more and less than its parts; (b) We must abandon the term "object" for systems because all the objects are systems and parts of systems; (c) System and organization are the two faces of the same reality; (d) Eco-systems illustrate self-organization.

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Arrogant physicists — do they think economics is easy?

Arrogant physicists — do they think economics is easy? | Complexity & Systems | Scoop.it
Arrogant physicists — do they think economics is easy?No. But their ideas can help improve economics, and here’s why

 

 

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Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World

Almost universally, wealth is not distributed uniformly within societies or economies. Even though wealth data have been collected in various forms for centuries, the origins for the observed wealth-disparity and social inequality are not yet fully understood. Especially the impact and connections of human behavior on wealth could so far not be inferred from data. Here we study wealth data from the virtual economy of the massive multiplayer online game (MMOG) Pardus. This data not only contains every player's wealth at every point in time, but also all actions of every player over a timespan of almost a decade. We find that wealth distributions in the virtual world are very similar to those in western countries. In particular we find an approximate exponential for low wealth and a power-law tail. The Gini index is found to be 0.65, which is close to the indices of many Western countries. We find that wealth-increase rates depend on the time when players entered the game. Players that entered the game early on tend to have remarkably higher wealth-increase rates than those who joined later. Studying the players' positions within their social networks, we find that the local position in the trade network is most relevant for wealth. Wealthy people have high in- and out-degree in the trade network, relatively low nearest-neighbor degree and a low clustering coefficient. Wealthy players have many mutual friendships and are socially well respected by others, but spend more time on business than on socializing. We find that players that are not organized within social groups with at least three members are significantly poorer on average. We observe that high `political' status and high wealth go hand in hand. Wealthy players have few personal enemies, but show animosity towards players that behave as public enemies.

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Eli Levine's curator insight, April 5, 2014 3:53 PM

When you let laissez-faire take its course, only a few individuals really end up on top.  That's not to say that markets shouldn't be allowed and enabled to exist, for the sake of the free exchange of goods, services, knowledge, wealth, etc.  It is saying that we need non-intrusive mechanisms to help make sure that the wealth that is produced is enjoyed by everyone who produced it.

 

Some people will always have more than others, for behavioral reasons and for circumstantial reasons.  That is not a problem, in my own view.  The problem comes, for me, when their focus on wealth becomes so great that they lose sight of their human needs on the individual as well as social and environmental levels, such that they choose wealth that they will not use over that which they need for survival and physical/psychological well being.

 

It's a form of being disconnected with the real world, kind of like schizophrenia.  The brain isn't functioning properly when  greed is and has taken over, for one reason or another.  It should be considered a mental illness that we could, potentially in time, treat, such that these individuals who are not aware and do not care to be aware of their actual place in the universe can lead normal, happy, healthy and appropriately placed lives in our societies.

 

So, we're left with the present situation in which work is undervalued, relative to what it produces, while executive management is way overvalued relative to its healthy role in the economy and society.  I'm not saying that pure equality is desirable, because sometimes people do work harder than others and deserve a greater share of wealth than someone who didn't work when they honestly could have.  What I'm saying, is that indulging the elite's fantasy of the ego is detrimental to themselves and to others, and that I don't think it should be accepted or tolerated within our social world.

 

If you want equality of opportunities, you must have more equality of outcomes.  That is yet another fact about our world that conservatives fail to accept and appreciate, if they're attempting to realize a world in which we are all together as one, rather than a world where we are heavily stratified according to an artificial hierarchy.  That is the difference between a conservative and a progressive.  One wants us all to be living together in peace, harmony, stability and, for want of a better word, love, while the other just wants everyone in a specific place according to birth.  One promotes democracy and inclusivity, the other, discourages it.  One works better for humanity on the tangible level, the other, does not.

 

And it's just a difference in brain type/values that makes them be something so antithetical to what Western civilization has stood for.

 

Think about it.

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Dynamical Systems on Networks: A Tutorial

We give a tutorial for the study of dynamical systems on networks, and we focus in particular on ``simple" situations that are tractable analytically. We briefly motivate why examining dynamical systems on networks is interesting and important. We then give several fascinating examples and discuss some theoretical results. We also discuss dynamical systems on dynamical (i.e., time-dependent) networks, overview software implementations, and give our outlook on the field.

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