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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Abrupt rise of new machine ecology beyond human response time : Scientific Reports : Nature Publishing Group

Abrupt rise of new machine ecology beyond human response time : Scientific Reports : Nature Publishing Group | Complexity & Systems | Scoop.it

Society's techno-social systems are becoming ever faster and more computer-orientated. However, far from simply generating faster versions of existing behaviour, we show that this speed-up can generate a new behavioural regime as humans lose the ability to intervene in real time. Analyzing millisecond-scale data for the world's largest and most powerful techno-social system, the global financial market, we uncover an abrupt transition to a new all-machine phase characterized by large numbers of subsecond extreme events. The proliferation of these subsecond events shows an intriguing correlation with the onset of the system-wide financial collapse in 2008. Our findings are consistent with an emerging ecology of competitive machines featuring ‘crowds’ of predatory algorithms, and highlight the need for a new scientific theory of subsecond financial phenomena.

 

 

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Sciences - The Four-Wing Attractor

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The Learning Environment as a Chaotic and Complex Adaptive System

Thrivability is a novel concept describing the intention to go beyond sustainability, allowing a system to flourish. For a society or organization to be thrivable, educated, responsible acting agents are needed. Traditional education focuses on (efficient) reproduction of existing organised bodies of information. We argue that complex adaptive systems theory and chaos theory provide concepts well suited to inform the design of learning environments, in order to facilitate a thrivable organization. This learning is not linear and externally controlled, but happens in a chaotic, yet guided manner. After discussing the suitability of the theoretical body of these general approaches, we show how a concrete progressive education approach, called the Dalton-Plan pedagogy, implements and supports these elements. By doing so, we show that the Dalton-Plan pedagogy is well suited for education of agents working in and for thrivable organizations. Support for teachers as part of this evolving learning system is provided by an e-learning environment.

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from http://gfbertini.wordpress.com/2013/09/03/the-learning-environment-as-a-chaotic-and-complex-adaptive-system/

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Sciences - The Dequan Li Attractor

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How to Tackle Complexity Using Systems Thinking

How to Tackle Complexity Using Systems Thinking | Complexity & Systems | Scoop.it
Systems thinking: what it is and why it’s important for fed leaders
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Julie Hankin's curator insight, September 7, 2013 3:54 AM

Fundamental systems thinking and applicability to public service reform

Julie Hankin's curator insight, September 7, 2013 3:56 AM

The basics of system thinking and how it applies to public service reform.  This is essential for mental health, not only a complex system in its own right but interlinking with so many others, police, employment, housing, education etc

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Sciences - The Coullet Attractor

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Nietzsche's Butterfly: An Introduction to Chaos Theory | Student Voices | Learn Science at Scitable

Nietzsche's Butterfly: An Introduction to Chaos Theory | Student Voices | Learn Science at Scitable | Complexity & Systems | Scoop.it
Have you ever thought about your life as a fractal? Have you embraced the infinite? PhD student Robin Andrews explains the chaotic theory you will find everywhere...even within yourself.
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Using a complex system approach to address world challenges in Food and Agriculture

Using a complex system approach to address world challenges in Food and Agriculture | Complexity & Systems | Scoop.it

World food supply is crucial to the well-being of every human on the planet in the basic sense that we need food to live. It also has a profound impact on the world economy, international trade and global political stability.Furthermore, consumption of certain types and amounts foods can affect health,and the choice of livestock and plants for food production can impact sustainable use of global resources. There are communities where insufficient food causes nutritional deficiencies, and at the same time other communities eating too much food leading to obesity and accompanying diseases. These aspects reflect the utmost importance of agricultural production and conversion of commodities to food products. Moreover, all factors contributing to the food supply are interdependent, and they are an integrative part of the continuously changing, adaptive and interdependent systems in the world around us. The properties of such interdependent systems usually cannot be inferred from the properties of its parts. In addressing current challenges, like the apparent incongruences of obesity and hunger, we have to account for the complex interdependencies among areas such as physics and sociology. This is possible using the complex system approach. It encompasses an integrative multi-scale and inter-disciplinary approach. Using a complex system approach that accounts for the needs of stakeholders in the agriculture and food domain, and determines which research programs will enable these stakeholders to better anticipate emerging developments in the world around them, will enable them to determine effective intervention strategies to simultaneously optimise and safeguard their interests and the interests of the environment.

 

 

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Sciences - The Chen-Lee Attractor

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Sciences - The Arneodo Attractor

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Attractor - Wikipedia, the free encyclopedia

An attractor is a set towards which a variable, moving according to the dictates of a dynamical system, evolves over time. That is, points that get close enough to the attractor remain close even if slightly disturbed. The evolving variable may be represented algebraically as an n-dimensional vector. The attractor is a region in n-dimensional space. In physical systems, the n dimensions may be, for example, two or three positional coordinates for each of one or more physical entities; in economic systems, they may be separate variables such as the inflation rate and the unemployment rate.

If the evolving variable is two- or three-dimensional, the attractor of the dynamic process can be represented geometrically in two or three dimensions, (as for example in the three-dimensional case depicted to the right). An attractor can be a point, a finite set of points, a curve, a manifold, or even a complicated set with a fractal structure known as a strange attractor. If the variable is a scalar, the attractor is a subset of the real number line. Describing the attractors of chaotic dynamical systems has been one of the achievements of chaos theory.

A trajectory of the dynamical system in the attractor does not have to satisfy any special constraints except for remaining on the attractor. The trajectory may be periodic or chaotic. If a set of points is periodic or chaotic, but the flow in the neighbourhood is away from the set, the set is not an attractor, but instead is called a repeller (or repellor).

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Why is combinatorial communication rare in the natural world, and why is language an exception to this trend?

In a combinatorial communication system, some signals consist of the combinations of other signals. Such systems are more efficient than equivalent, non-combinatorial systems, yet despite this they are rare in nature. Why? Previous explanations have focused on the adaptive limits of combinatorial communication, or on its purported cognitive difficulties, but neither of these explains the full distribution of combinatorial communication in the natural world. Here we present a nonlinear dynamical model of the emergence of combinatorial communication that, unlike previous models, considers how initially non-communicative behaviour evolves to take on a communicative function. We derive three basic principles about the emergence of combinatorial communication. We hence show that the interdependence of signals and responses places significant constraints on the historical pathways by which combinatorial signals might emerge, to the extent that anything other than the most simple form of combinatorial communication is extremely unlikely. We also argue that these constraints can be bypassed if individuals have the socio-cognitive capacity to engage in ostensive communication. Humans, but probably no other species, have this ability. This may explain why language, which is massively combinatorial, is such an extreme exception to nature's general trend for non-combinatorial communication.

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Nouvelle Alliance (Folio Essais) (French Edition): Prigogine/Stengers

"L'ancienne alliance est rompue. L'homme sait enfin qu'il est seul dans l'immensité indifférente de l'univers d'où il a émergé par hasard. " C'est de ces mots du biologiste et Prix Nobel Jacques Monod qu'Ilya Prigogine, chimiste et autre Prix Nobel, et la philosophe Isabelle Stengers, ont tiré le titre de cette réflexion, devenue classique, sur l'évolution de la science. À partir de la théorie du chaos, qui met à mal le déterminisme de la science classique, de la thermodynamique et de ses implications en biologie moléculaire, ils montrent que le visage de la science a résolument changé. On croyait possible, il y a un siècle, de mettre l'univers en équation ; on sait aujourd'hui que cet espoir est à jamais chimérique. La certitude a fait place à la probabilité, et l'homme lui-même est désormais une partie intégrante du savoir qu'il édifie. Le temps est venu de nouvelles alliances, depuis toujours nouées, longtemps méconnues, entre l'histoire des hommes, de leurs sociétés, de leurs savoirs et l'aventure exploratrice de la nature. -Arthur Hennessy

Bernard Ryefield's insight:

indispensable pour comprendre l'évolution de la science moderne et ses implications

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Sciences - The Genesio-Tesi Attractor

Sciences - The Genesio-Tesi Attractor | Complexity & Systems | Scoop.it
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Sciences - The Finance Attractor

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Sciences - The Coupled Lorenz Attractor

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Sciences - The Dadras Attractor

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Exactly scale-free scale-free networks

Exactly scale-free scale-free networks | Complexity & Systems | Scoop.it

There is mounting evidence of the apparent ubiquity of scale-free networks among complex systems. Many natural and physical systems exhibit patterns of interconnection that conform, approximately, to the structure expected of a scale-free network. We propose an efficient algorithm to generate representative samples from the space of all networks defined by a particular(scale-free) degree distribution. Using this algorithm we are able to systematically explore that space with some surprising results: in particular,we find that preferential attachment growth models do not yield typical realizations and that there is a certain latent structure among such networks--- which we loosely term "hub-centric". We provide a method to generate or remove this latent hub-centric bias --- thereby demonstrating exactly which features of preferential attachment networks are atypical of the broader class of scale free networks. Based on these results we are also able to statistically determine whether experimentally observed networks are really typical realizations of a given degree distribution (scale-free degree beingthe example which we explore). In so doing we propose a surrogate generation method for complex networks, exactly analogous the the widely used surrogate tests of nonlinear time series analysis.

 

 

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‘Superorganisations’ – Learning from Nature’s Networks

‘Superorganisations’ – Learning from Nature’s Networks | Complexity & Systems | Scoop.it

Fritjof Capra, in his book ‘The Hidden Connections’ applies aspects of complexity theory, particularly the analysis of networks, to global capitalism and the state of the world; and eloquently argues the case that social systems such as organisations and networks are not just like living systems – they are living systems. The concept and theory of living systems (technically known as autopoiesis) was introduced in 1972 by Chilean biologists Humberto Maturana and Francisco Varela.

 

This is a complete version of a ‘long-blog’ written by Al Kennedy on behalf of ‘The Nature of Business’ blog and BCI: Biomimicry for Creative Innovation www.businessinspired...


Via Peter Vander Auwera, ddrrnt, Spaceweaver, David Hodgson, pdjmoo, Sakis Koukouvis, Dr. Stefan Gruenwald, Ben van Lier
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Monica S Mcfeeters's curator insight, January 18, 2014 8:57 PM

A look at how to go organic with business models in a tech age...

Nevermore Sithole's curator insight, March 14, 2014 9:01 AM

Learning from Nature’s Networks

pdjmoo's curator insight, December 6, 2014 11:04 PM

YOU ARE INVITED TO FOLLOW MY NEWS AGGREGATES @pdjmoo

 

▶  CLIMATE CHANGE http://www.scoop.it/t/changingplanet

▶  BIODIVERSITY http://www.scoop.it/t/biodiversity-is-life

▶  OUR OCEANS http://www.scoop.it/t/our-oceans-need-us

▶   OUR FOOD http://www.scoop.it/t/agriculture-gmos-pesticides

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Sciences - The Chua Attractor

Sciences - The Chua Attractor | Complexity & Systems | Scoop.it
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Benoit Mandelbrot: Fractals and the art of roughness | Video on TED.com

At TED2010, mathematics legend Benoit Mandelbrot develops a theme he first discussed at TED in 1984 -- the extreme complexity of roughness, and the way that fractal math can find order within patterns that seem unknowably complicated.
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Sciences - The Burke-Shaw Attractor

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Sciences - The Chen-Celkovsky Attractor

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The Anishchenko-Astakhov Attractor

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