Complex Networks Everywhere
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Complex Networks Everywhere
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Global Optimization of Nonlinear Network Design : SIAM Journal on Optimization: Vol. 23, No. 1 (Society for Industrial and Applied Mathematics)

Global Optimization of Nonlinear Network Design : SIAM Journal on Optimization: Vol. 23, No. 1 (Society for Industrial and Applied Mathematics) | Complex Networks Everywhere | Scoop.it
A. J. Alvarez-Socorro's insight:
A novel approach for obtaining globally optimal solutions to design of networks with nonlinear resistances and potential driven flows is proposed. The approach is applicable to networks where the potential loss on an edge in the network is governed by a convex and strictly monotonically increasing function of flow rate. We introduce a relaxation of the potential loss constraint and formulate the design problem as a mixed-integer nonlinear program. A linearization-based approach with tailored cuts is proposed that improves the computational efficiency over a standard implementation. We have also implemented a simple heuristic approach for finding feasible solutions at the root node and during the search process. The algorithm has been implemented with IBM-ILOG CPLEX and is shown to be computationally effective on a number of examples from the literature.


Read More: http://epubs.siam.org/doi/abs/10.1137/110827387
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Music and the Origins of Language | International Summer School on Agent-based Computational Models of Creativity

The school is intended for postdocs, lecturers and predocs with a background in computer science (artificial intelligence) or computational linguistics (corpus linguistics or natural language processing) and a strong interest in music and the origins of language. There will be background lectures that introduce concepts from biology, anthropology, psychology, music theory and linguistics that are helpful to understand the nature of creativity, the role and intimate relations between language and music, and the mechanisms underlying cultural evolution. It contains technical lectures on the fundamental computational components required for language processing and technical ateliers to learn how to set up evolutionary linguistics experiments. Participants have the opportunity to present their latest research in a poster session. The school also features artistic ateliers in which participants create new creative works and engage in performance.

 

Music and the Origins of Language
International Summer School on Agent-based Computational Models of Creativity, 15 – 20 September 2013 in Cortona (Italy)

http://ai.vub.ac.be/events/cortona-2013


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Cesar Hidalgo: The Structure and Dynamics of Cultural Exports

At MIT 13/14 February 2013

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Catalyzing the Connection Economy - Triple Pundit

Catalyzing the Connection Economy - Triple Pundit | Complex Networks Everywhere | Scoop.it
Triple Pundit Catalyzing the Connection Economy Triple Pundit In order to meet our own generation's needs, without compromising the needs of future generations, it is incumbent on us evolve a new enterprise model based on this very straightforward...
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Network Science Postdoctoral Appointee - Defense Daily Network (subscription)

Network Science Postdoctoral Appointee
Defense Daily Network (subscription)
Sandia National Laboratories is searching for a Network Science Postdoctoral Appointee for the Informatics and Systems Assessments Department located in Livermore, CA.
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I, Quantum Robot - Scientific American (blog)

I, Quantum Robot - Scientific American (blog) | Complex Networks Everywhere | Scoop.it
Scientific American (blog)
I, Quantum Robot
Scientific American (blog)
Artificial Intelligence is the ability of a computer system to operate in a manner similar to human intelligence.
A. J. Alvarez-Socorro's insight:

Very interesting, I enjoyed reading it.

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luiy's curator insight, March 19, 2013 10:13 AM

The quantum robot is the idea of combining quantum theory with robot technology. In other words, it is a practical use of the combination of quantum computing and robot technology. Quantum computing involves using quantum systems and quantum states to do computations.

 

A robot is an automated machine that is capable of doing a set of complex tasks. In some applications of robots, the programming used to run the robots may be based on artificial intelligence. Artificial Intelligence is the ability of a computer system to operate in a manner similar to human intelligence. Think of artificial intelligence as if you were training a machine to act like a human. Essentially, quantum robots are complex quantum systems.They are mobile systems with on board quantum computers that interact with their environments. Several programs would be involved in the operation of the robot. These programs would be quantum searching algorithms and quantum reinforcement learning algorithms.

 

Quantum reinforcement learning is based on superposition of the quantum state and quantum parallelism. A quantum state is a system that is a set of quantum numbers. The four basic quantum numbers represent the energy level, angular momentum, spin, and magnetization. In the superposition of quantum states, the idea is to get one state to look like another.

 

Let’s say I have two dogs. One dog knows how to fetch a bone (energy level), sit up (angular momentum), give a high five (spin), and shake hands (magnetization). Now, let’s apply the superposition of quantum states. Since one dog has been trained and given the commands, the other dog must learn to mimic or copy what the first dog did. Each time a command is achieved, reinforcement is given. The reinforcement for the dog would be a bone (or no bone if the command is not achieved).

 

In quantum reinforcement learning, it is slightly different. The idea would be similar to an “If-Then” statement. An example would be if the quantum state has a certain energy level, then the angular momentum is certain value. This idea of “If-Then” statements in the quantum world leads to an idea which can be a topic of its own; Quantum Logic.

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Defining and Modeling Complex Adaptive Systems

Defining and Modeling Complex Adaptive Systems | Complex Networks Everywhere | Scoop.it
Almost all the critical problems of our time are problems of control and almost all of them concern complex adaptive systems. If we want to know more about our bodies, it is not just to increase knowledge but so that we can control our health.

 

CAS are  “systems that don’t yield compact forms of representation”1. In other words a complex system cannot be described by a simple set of equations. Why would this be the case? It is the “adaptive” nature of these systems that leads to this intractability. Agents within the system respond to each set of environmental conditions within a complex adaptive system with a different set of responses and the number of such environments and their corresponding agent responses that need to be accounted for to construct an accurate model of the system is simply too large. But is this simply a problem of impracticality? Could we, at least in theory, construct a model that takes into account all possible environmental conditions and all possible agent behaviours? Although some scientists may argue that such an approach is theoretically possible, there is ample evidence that the critical “adaptive” component of some complex adaptive systems may in fact be unmodelable


Via Anne Caspari
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luiy's curator insight, March 18, 2013 5:12 PM
What Is A Complex Adaptive System?

The first question that then needs to be answered is: What is a complex adaptive system? David Krakauer defines complex systems as “systems that don’t yield compact forms of representation”1. In other words a complex system cannot be described by a simple set of equations. Why would this be the case? As Krakauer notes, it is the “adaptive” nature of these systems that leads to this intractability. Agents within the system respond to each set of environmental conditions within a complex adaptive system with a different set of responses and the number of such environments and their corresponding agent responses that need to be accounted for to construct an accurate model of the system is simply too large. But is this simply a problem of impracticality? Could we, at least in theory, construct a model that takes into account all possible environmental conditions and all possible agent behaviours? Although some scientists may argue that such an approach is theoretically possible, there is ample evidence that the critical “adaptive” component of some complex adaptive systems may in fact be unmodelable. There is no better example of this than the problems faced by the economist Hyman Minsky in formalising many of his most important ideas.

Luciano Lampi's curator insight, March 19, 2013 1:02 PM

Interesting to read!

Léonne Willems's curator insight, March 25, 2013 8:27 PM

Another way to think about environmental influences at the source of tensions at work (as opposed to individual lack of employee performance or motivational problems). Are these 'tensions' actually symptoms of a system out of balance? Are these tensions the real gems for organisational steering? Check out how Holacracy capitalises just on that! 

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Complex Adaptive Systems Modeling: A multidisciplinary Roadmap

I would like to start by extending a very warm welcome from the editorial board of Complex Adaptive Systems Modeling (CASM) journal, a new and exciting SpringerOpen/BioMed Central project. This article is the opening editorial and a call for papers for CASM. It also provides a gentle introduction to CASM as well as serves as a concise multidisciplinary roadmap and survey for CASM readership. The primary goal is to assist multidisciplinary researchers with an interest in modeling complex systems in finding more about relevant helpful resources and the numerous exciting ways in which other colleague researchers use modeling approaches in their respective disciplines. Finally I also provide advice for prospective authors regarding the preparation of manuscripts in a style appropriate to the highly multidisciplinary CASM readership. It is hoped that this will help seed fruitful cross‐fertilization of ideas transgressing disciplinary boundaries.

 

Complex Adaptive Systems Modeling: A multidisciplinary Roadmap
Muaz A Niazi

Complex Adaptive Systems Modeling 2013, 1:1 http://dx.doi.org/10.1186/2194-3206-1-1


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YOUNG SCIENTIST AWARD for SOCIO and ECONOPHYSICS 2013 - Dr Vittoria COLIZZA | ISI Foundation

YOUNG SCIENTIST AWARD for SOCIO and ECONOPHYSICS 2013 - Dr Vittoria COLIZZA | ISI Foundation | Complex Networks Everywhere | Scoop.it

Vittoria Colizza receives the Young Scientist Award for Socio and Econophysics 2013 
 
Torino, March 11, 2013. Vittoria Colizza, senior researcher at ISI Foundation (Turin, Italy) and at Inserm (Paris, France) is this year’s recipient of the Young Scientist Award for Socio and Econophysics. This is the third time that an Italian scientist receives the award of the German Physical Society (after Fabrizio Lillo in 2008 and Santo Fortunato, ISI researcher as well, in 2011), among the most prestigious prizes in the world in the field of the physics of social and economic systems, assigned to researchers under 40. Colizza receives today the prize in Regensburg, Germany, during the annual meeting of the German Physical Society.
 
“With vision and courage, Dr. Colizza has made major contributions to and has, indeed, significantly shaped the new field of computational epidemiology”,it is written in the motivation for the award assignment, “leading to remarkable advances in the surveillance, modeling, and prediction of epidemic spreading on a global scale”.


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The nature of collective intelligence

Digital data stem from our own personal and social cognitive processes and thus express them in one way or another. But we still don’t have any scientific tools to make sense of the data flows produced by online creative conversations at the scale of the digital medium as a whole.

 

Presentation by Pierre Levy


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Viktor Markowski's curator insight, March 2, 2013 4:57 PM

45 minute video presentation supported by slides on the nature of collective intelligence and the philosophical and technical construct behind the next level of the internet as a global mind.

Luciano Lampi's curator insight, March 22, 2013 6:15 PM

Pierre Levy, c´est toujours très intéressant!

Bernard Ryefield's curator insight, June 18, 2013 7:32 PM

Pierre Lévy invented IEML; think semantic web

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El Deterioro Cognitivo Leve bajo una nueva perspectiva

El Deterioro Cognitivo Leve bajo una nueva perspectiva | Complex Networks Everywhere | Scoop.it
Las Redes Complejas sin complejos - Divulgación y aplicaciones de las redes complejas
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A.L. Barabási, el “hub” de las Redes Complejas

A.L. Barabási, el “hub” de las Redes Complejas | Complex Networks Everywhere | Scoop.it
Las Redes Complejas sin complejos - Divulgación y aplicaciones de las redes complejas
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El congreso Dynamics Days Europe 2013 tendrá lugar en Madrid

El congreso Dynamics Days Europe 2013 tendrá lugar en Madrid | Complex Networks Everywhere | Scoop.it
Las Redes Complejas sin complejos - Divulgación y aplicaciones de las redes complejas
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Fixed Point Optimization Algorithms for Distributed Optimization in Networked Systems : SIAM Journal on Optimization: Vol. 23, No. 1 (Society for Industrial and Applied Mathematics)

Fixed Point Optimization Algorithms for Distributed Optimization in Networked Systems : SIAM Journal on Optimization: Vol. 23, No. 1 (Society for Industrial and Applied Mathematics) | Complex Networks Everywhere | Scoop.it
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Interactions between species and environments from incomplete information

There are two contradictory aspects of the adaptive process in evolution. The first is that species must optimally increase their own fitness in a given environment. The second is that species must maintain their variation to be ready to respond to changing environments. In a strict sense, these two aspects might consider to be mutually exclusive. If species are optimally adapted, then the variation in the species that is suboptimal decreases and vice versa. To resolve this dilemma, species must find a balance between optimal adaptation and robust adaptation. Finding the balance between these processes requires both the local and global complete, static information. However, the balance between the processes must be dynamic. In this study, we propose a model that illustrates dynamic negotiation between the global and local information using lattice theory. The dynamic negotiation between these two levels results in an overestimate of fitness for each species. The overestimation of fitness in our model represents the multiplicity of fitness which is sometimes discussed as the exaptation. We show that species in our model demonstrate the power law of the lifespan distribution and 1/f fluctuation for the adaptive process. Our model allows for a balance between optimal adaptation and robust adaptation without any arbitrary parameters.

 

Interactions between species and environments from incomplete information
Takayuki Niizato, Yukio-Pegio Gunji

Biosystems
Volume 111, Issue 3, March 2013, Pages 145–155

http://dx.doi.org/10.1016/j.biosystems.2012.12.003


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A Strange Computer Promises Great Speed

A Strange Computer Promises Great Speed | Complex Networks Everywhere | Scoop.it
New York Times
A Strange Computer Promises Great Speed
New York Times
Ray Johnson, Lockheed's chief technical officer, said his company would use the quantum computer to create and test complex radar, space and aircraft systems.
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Humans Use Memory Tricks To Track Complex Social Networks - RedOrbit

Humans Use Memory Tricks To Track Complex Social Networks - RedOrbit | Complex Networks Everywhere | Scoop.it
RedOrbit Humans Use Memory Tricks To Track Complex Social Networks RedOrbit Humans keep track of our vast social networks by using special memory tricks that cheat complexity, rather than using routine memorization, according to a new Cornell...
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The nature of collective intelligence

The nature of collective intelligence | Complex Networks Everywhere | Scoop.it

Presentation by Pierre Levy


Via Viktor Markowski
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Viktor Markowski's curator insight, March 2, 2013 4:57 PM

45 minute video presentation supported by slides on the nature of collective intelligence and the philosophical and technical construct behind the next level of the internet as a global mind.

Luciano Lampi's curator insight, March 22, 2013 6:15 PM

Pierre Levy, c´est toujours très intéressant!

Bernard Ryefield's curator insight, June 18, 2013 7:32 PM

Pierre Lévy invented IEML; think semantic web

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The Insupportable Equilibrium of Economic Thought - Bloomberg

The Insupportable Equilibrium of Economic Thought - Bloomberg | Complex Networks Everywhere | Scoop.it
Bloomberg The Insupportable Equilibrium of Economic Thought Bloomberg We'll never understand economies and markets until we get over the nutty idea that they alone -- unlike almost every other complex system in the world -- are inherently stable...
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Complexity, patterns and links

Complexity, patterns and links | Complex Networks Everywhere | Scoop.it
The mainstream ways of thinking about management are based on the sciences of certainty. The whole system of strategic choice, goal setting and choosing actions to reach the given goals in a contro...

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Ides De Vos's curator insight, March 13, 2013 4:52 PM

In our lineair thinking , we think that everything has a solution .We are certain of that ...but we know that in real life , there is no one solution because the results of interaction between human beings is unpredictable .

So the only certainty we have is uncertainty

luiy's curator insight, March 14, 2013 2:27 PM

The mainstream ways of thinking about management are based on the sciences of certainty. The whole system of strategic choice, goal setting and choosing actions to reach the given goals in a controlled way depends on predictability. The problem is that this familiar causal foundation cannot explain the reality we face. Almost daily, we experience the inability of people to choose what happens in their organizations – or in their countries. We live in a complex world. Things may appear orderly over time, but are inherently unpredictable.

 

Complexity refers to a pattern, a movement in time that is at the same time predictable and unpredictable, knowable and unknowable. Healthy, ordinary, everyday life is always complex, no matter what the situation is. There is absolutely no linearity in the world of human beings.

Human patterns that lose this complexity become repetitive and rapidly inappropriate for dealing with life. Unlike mechanical systems, human systems thrive on variety and diversity. An exact replication of behavior in nature would be disastrous and seen as neurotic in social life. For example, a failing heart is typically characterized by increasing loss of complexity.


A pattern is something that emerges through the complex interactions between elements in a system. Although there is apparent order, there is never exact repetition if the system is viable. This is why human interaction cannot be understood as processes in the way they were used in manufacturing, but as patterns.

 

Patterns that are more repetitive are normally called routines or habits. This conclusion is important for us. Novelty emerges in a radically unpredictable way. Creativity is seldom the end result of a repetitive process.

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Open Access Copit ArXives UNAM

Open Access Copit ArXives UNAM | Complex Networks Everywhere | Scoop.it
e-books, libros electronicos, mexico, unam, contenido libre, open access, libros gratis
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First documented case of child cured of HIV

First documented case of child cured of HIV | Complex Networks Everywhere | Scoop.it
Researchers have described the first documented case of a child being cured of HIV. The case involves a two-year-old child in Mississippi diagnosed with HIV at birth and immediately put on antiretroviral therapy.
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La Estructura de las Redes Sociales

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Las Redes Complejas sin complejos - Divulgación y aplicaciones de las redes complejas
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Mark Newman, el hub en la sombra…

Mark Newman, el hub en la sombra… | Complex Networks Everywhere | Scoop.it
Las Redes Complejas sin complejos - Divulgación y aplicaciones de las redes complejas
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