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Complexity - Complex Systems Theory
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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Flow, Conflux | Smart Cities

Flow, Conflux | Smart Cities | Complexity - Complex Systems Theory | 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, 9:00 AM

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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Common scaling laws for city highway systems and the mammalian neocortex - Changizi - 2009 - Complexity - Wiley Online Library

Common scaling laws for city highway systems and the mammalian neocortex - Changizi - 2009 - Complexity - Wiley Online Library | Complexity - Complex Systems Theory | Scoop.it

Changizi, M. A. and Destefano, M. (2010), Common scaling laws for city highway systems and the mammalian neocortex. Complexity, 15: 11–18. doi: 10.1002/cplx.20288

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Eli Levine's curator insight, February 19, 1:01 PM

Could you imagine if we're able to mimic our social/constructed systems upon our natural/organic systems?  Imagine if we could discover the natural laws that shape our world and then make our world be in conformity with these natural, discovered laws (as opposed to our abstracted, imaginatively created laws.

 

Think about it!

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We need to talk about TED

We need to talk about TED | Complexity - Complex Systems Theory | Scoop.it

Benjamin Bratton: Science, philosophy and technology run on the model of American Idol – as embodied by TED talks – is a recipe for civilisational disaster

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Chaos Theory and the Sciences of Complexity: Foundations for Transforming Education - Charles M. Reigeluth

This is from 2004 but still work reading, as it is well in advance of what most people today are still saying about learning. But it is relevant to the theories of learning networks and connectivism. Among other things, it discusses:

network health - "For a system to be healthy, it must co-evolve with its environment: it changes in response to changes in its environment, and its environment changes in response to its changes"learning theories - "Co-evolution is fostered by disequilibrium and positive feedback" (ie., Boltzmann mechanisms and back propagation)openness - "open systems maintain a state of non-equilibrium… They participate in an open exchange with their world"content - "Transformation is strongly influenced by 'strange attractors'... In educational systems, they can be considered 'core ideas' and values or beliefs"self-organization - "require two major characteristics: openness and self-reference [and] Because it partners with its environment, the system develops increasing autonomy from the environment [and] the more freedom in self-organization, the more order"from Stephen Downes blog
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Networked for complexity

Networked for complexity | Complexity - Complex Systems Theory | Scoop.it

In the 21st century, then, the industrial era has given way to the social era, and it is time to rethink both how we work and how we organise ourselves to do so. 


Via Kenneth Mikkelsen, Christophe Bredillet
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Kenneth Mikkelsen's curator insight, November 25, 2013 2:39 PM

Terrific blog post by Richard Martin. You should follow Richard on Scoop.it [url=/u/2565370 x-already-notified=1]Richard Martin[/url] and on Twitter here

Stephen Dale's curator insight, November 27, 2013 2:01 AM

I picked out this abstract which resonated with me..." a company is like ‘a social network of productive relationships in which stakeholders are deployed where they are of greatest use. It is designed as a flow of input that can come from anywhere in the network. The work is asynchronous in time and place, and people contribute whatever expertise they have, irrespective of rank or experience." 


Great post.

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Wicked Problems

Wicked Problems | Complexity - Complex Systems Theory | Scoop.it

A wicked problem is one for which each attempt to create a solution changes the understanding of the problem. Wicked problems cannot be solved in a traditional linear fashion, because the problem definition evolves as new possible solutions are considered and/or implemented. The term was originally coined by Horst Rittel.

 

Wicked problems always occur in a social context -- the wickedness of the problem reflects the diversity among the stakeholders in the problem.


Most projects in organizations -- and virtually all technology-related projects these days -- are about wicked problems. Indeed, it is the social complexity of these problems, not their technical complexity, that overwhelms most current problem solving and project management approaches

 

 

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Chaos Forgets and Remembers: Measuring Information Creation, Destruction, and Storage

The hallmark of deterministic chaos is that it creates information---the rate being given by the Kolmogorov-Sinai metric entropy. Since its introduction half a century ago, the metric entropy has been used as a unitary quantity to measure a system's intrinsic unpredictability. Here, we show that it naturally decomposes into two structurally meaningful components: A portion of the created information---the ephemeral information---is forgotten and a portion---the bound information---is remembered. The bound information is a new kind of intrinsic computation that differs fundamentally from information creation: it measures the rate of active information storage. We show that it can be directly and accurately calculated via symbolic dynamics, revealing a hitherto unknown richness in how dynamical systems compute.

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Q&A with Melanie Mitchell on SFI’s massive open online course in complexity

Q&A with Melanie Mitchell on SFI’s massive open online course in complexity | Complexity - Complex Systems Theory | Scoop.it

In early 2013, SFI External Professor Melanie Mitchell taught the Institute’s first Massive Open Online Course (MOOC).

The 16-week course, “Introduction to Complexity,” drew nearly 7,100 students. It marked the debut of a series of free courses and resources for complexity science SFI is providing through the online Complexity Explorer.

Approximately 1,200 participants finished the course successfully, a 17 percent completion rate (much higher than the MOOC average).

SFI is re-offering "Introduction to Complexity" beginning September 30, 2013. See the announcement for more information.

As Mitchell prepares to begin the course again, she offers her thoughts to SFI science writer Jenna Marshall about the first SFI MOOC and what the future holds for future online courses in complexity.

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The reductionism stops here - Steve Keen

The reductionism stops here - Steve Keen | Complexity - Complex Systems Theory | Scoop.it

One of the defining features of neoclassical economics is the belief that macroeconomic analysis has to be not merely compatible with, but derivable from, microeconomic analysis. The development of economic theory has been driven far more by this belief than by the desire to make the theory compatible with the observed behaviour of the economy.

This ‘reductionist’ aspect of economics – the attempt to reduce the higher level topic of macroeconomics to an applied version of the lower level topic of microeconomics – is at odds with the last 50 years of genuine sciences, where complexity has ruled the roost, for reasons that were eloquently put by Physics Nobel Laureate Philip Anderson in a highly readable paper entitled “More Is Different”.

In that paper, Anderson asserted that reductionism did not work, because though it is possible to rank sciences in a hierarchy in which “The elementary entities of science X obey the laws of science Y, … this hierarchy does not imply that ‘science X is just applied Y’… At each stage entirely new laws, concepts, and generalisations are necessary, requiring inspiration and creativity to just as great a degree as in the previous one. Psychology is not applied biology, nor is biology applied chemistry.”

Economics violates this by its belief that “macroeconomics is just applied microeconomics”, but recent blogosphere debates have confirmed that there is a limit to how far neoclassical economists will take reductionism: it stops at microeconomics.

 

 

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Urban Emergencies : Emergent Urbanism

Urban Emergencies : Emergent Urbanism | Complexity - Complex Systems Theory | Scoop.it

Urban Emergencies : Emergent Urbanism (UE:EU) is an independent research group exploring international and interdisciplinary perspectives on the implications of emergent risks on the built environment and its inhabitants.

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SIMSOC: Recommendations for ABM videos | MASS

SIMSOC: Recommendations for ABM videos | MASS | Complexity - Complex Systems Theory | Scoop.it

I asked participants of the SIMSOC email list for recommendations of videos to show in agent-based modelling and complexity lectures. Thank you to everyone who replied. Here is a list of some useful resources:

Bernard Ryefield's insight:

lots of good links to videos on agent-based modelling

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Complexity analysis of experimental cardiac arrhythmia

To study the cardiac arrhythmia, an in vitro experimental model and technology Multielectrodes Array (MEA) are used. This platform serves as an intermediary of the electrical activities of cardiac cells and the signal processing / dynamics analysis. Through which the extracellular potential of cardiac cells is acquired, allowing a real-time monitoring / analyzing. Since MEA has 60 electrodes / channels dispatched in a rectangular region, it allows real-time monitoring and signal acquisition on multiple sites. The in vitro experimental model (cardiomyocytes cultures from new-born rats' heart) is directly prepared on the MEA. This carefully prepared culture has similar parameters as cell of human's heart. In order to discriminate the cardiac arrhythmia, complexity analysis methods (Approximate Entropy, ApEn and Sample Entropy, SampEn) are used especially taking into account noises. The results showed that, in case of arrhythmia, the ApEn and SampEn are reduced to about 50\% of the original entropies. Both parameters could be served as factors to discriminate arrhythmia. Moreover, from a point of view of biophysics this decrease 50% of Entropy coincides with the bifurcation (periods, attractors etc.) in case of arrhythmia which have been reported previously. It supports once more the hypothesis that in case of cardiac arrhythmia, the heart entered into chaos which helps better understand the mechanism of atrial fibrillation.

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Center for Complex Networks and Systems Research - Indiana University

Center for Complex Networks and Systems Research - Indiana University | Complexity - Complex Systems Theory | Scoop.it

The Center for Complex Networks and Systems Research (CNetS) is part of the Pervasive Technology Institute of Indiana University and the School of Informatics and Computing. The center was established in 2009 to consolidate and enhance the research efforts of the complex systems group, which has been active within the School since 2004. CNetS is meant to foster interdisciplinary research in all areas related to complex systems.

The types of problems that we work on include mining usage and traffic patterns in technological networks such as the Web and the Internet; studying the interaction between social dynamics and online behaviors; modeling the evolution of complex social and technological networks; developing adaptive, distributed, collaborative, agent-based applications for Web search and recommendation; understanding complex biological networks and complex reaction in biochemistry; developing models for the spread of diseases; understanding how coordinated behavior arises from the dynamical interaction of nervous system, body, and environment; studying social human behavior; exploring reasons underlying species diversity; studying the interplay between self-organization and natural selection; understanding how information arises and is used in biological systems; and so on. All these examples are characterized by complex nonlinear feedback mechanisms and it is now being increasingly recognized that the outcome of such interactions can only be understood through mathematical and computational models.

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Complexity Theory Basic Concepts

A summary of key complexity theory concepts. (Complexity theory background http://t.co/lsYiQGJZv1)

Via Christophe Bredillet, Philippe Vallat
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Economics 2.0: The Natural Step towards a Self-Regulating, Participatory Market Society

source : https://www.jstage.jst.go.jp/article/eier/10/1/10_3/_article

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War, space, and the evolution of Old World complex societies

How did human societies evolve from small groups, integrated by face-to-face cooperation, to huge anonymous societies of today, typically organized as states? Why is there so much variation in the ability of different human populations to construct viable states? Existing theories are usually formulated as verbal models and, as a result, do not yield sharply defined, quantitative predictions that could be unambiguously tested with data. Here we develop a cultural evolutionary model that predicts where and when the largest-scale complex societies arose in human history. The central premise of the model, which we test, is that costly institutions that enabled large human groups to function without splitting up evolved as a result of intense competition between societies—primarily warfare. Warfare intensity, in turn, depended on the spread of historically attested military technologies (e.g., chariots and cavalry) and on geographic factors (e.g., rugged landscape). The model was simulated within a realistic landscape of the Afroeurasian landmass and its predictions were tested against a large dataset documenting the spatiotemporal distribution of historical large-scale societies in Afroeurasia between 1,500 BCE and 1,500 CE. The model-predicted pattern of spread of large-scale societies was very similar to the observed one. Overall, the model explained 65% of variance in the data. An alternative model, omitting the effect of diffusing military technologies, explained only 16% of variance. Our results support theories that emphasize the role of institutions in state-building and suggest a possible explanation why a long history of statehood is positively correlated with political stability, institutional quality, and income per capita.

Bernard Ryefield's insight:

Cliodynamics (historical dynamics)

original link : http://www.pnas.org/content/early/2013/09/20/1308825110

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Announcing SFI's new free online course in complex systems

To receive e-mail updates about how to register for this course, please visit the course website http://www.complexityexplorer.org/. SFI will offer a series ...
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Case Based Method and Complexity Science, Part II (The SACS Toolkit)

Case Based Method and Complexity Science, Part II (The SACS Toolkit) | Complexity - Complex Systems Theory | Scoop.it

My goal here is to introduce the case-based complexity science method my colleagues and I have developed for modeling complex systems. Our case-based modeling technique is called the SACS Toolkit--which stands for the Sociology and Complexity Science Toolkit.


Via Susan Bainbridge
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