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Sciences - The Dequan Li Attractor

Sciences - The Dequan Li Attractor | Complexity - Complex Systems Theory | Scoop.it
Math:Rules - Strange Attractors by Chaotic Atmospheres , via Behance - The Dequan Li Attractor
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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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Defining chaos

Defining chaos | Complexity - Complex Systems Theory | Scoop.it
In this paper, we propose, discuss, and illustrate a computationally feasible definition of chaos which can be applied very generally to situations that are commonly encountered, including attractors, repellers, and non-periodically forced systems. This definition is based on an entropy-like quantity, which we call “expansion entropy,” and we define chaos as occurring when this quantity is positive. We relate and compare expansion entropy to the well-known concept of topological entropy to which it is equivalent under appropriate conditions. We also present example illustrations, discuss computational implementations, and point out issues arising from attempts at giving definitions of chaos that are not entropy-based.
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Complex Adaptive Systems

Complex Adaptive Systems | Complexity - Complex Systems Theory | Scoop.it
This article explores the concept of the Complex Adaptive Systems and see how this model might apply in various walks of life.
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David Poveda's curator insight, August 27, 1:20 PM

Supply chains are Complex Adaptive Systems. In order to manage them well, this basic fact must be recognized. And they are certainly not well managed with forecasts and ERP´s.

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Introduction to the Modeling and Analysis of Complex Systems | Open SUNY Textbooks

Introduction to the Modeling and Analysis of Complex Systems | Open SUNY Textbooks | Complexity - Complex Systems Theory | Scoop.it

Introduction to the Modeling and Analysis of Complex Systems introduces students to mathematical/computational modeling and analysis developed in the emerging interdisciplinary field of Complex Systems Science. Complex systems are systems made of a large number of microscopic components interacting with each other in nontrivial ways. Many real-world systems can be understood as complex systems, where critically important information resides in the relationships between the parts and not necessarily within the parts themselves. This textbook offers an accessible yet technically-oriented introduction to the modeling and analysis of complex systems. The topics covered include: fundamentals of modeling, basics of dynamical systems, discrete-time models, continuous-time models, bifurcations, chaos, cellular automata, continuous field models, static networks, dynamic networks, and agent-based models. Most of these topics are discussed in two chapters, one focusing on computational modeling and the other on mathematical analysis. This unique approach provides a comprehensive view of related concepts and techniques, and allows readers and instructors to flexibly choose relevant materials based on their objectives and needs. Python sample codes are provided for each modeling example.


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Why Systems Thinking is Not a Natural Act

Competence in systems thinking is implicitly assumed among the population of engineers and managers — in fact, most technical people claim to be systems ...


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FOCUS: Complexity and the failure of quantitative social science

FOCUS: Complexity and the failure of quantitative social science | Complexity - Complex Systems Theory | Scoop.it
Photo: Walter Baxter - licensed for reuse CC BY-SA 2.0 Brian Castellani (Kent State University)   When I attended university in 1984 as a psychology undergraduate in the States, the pathway to...

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Christophe Bredillet's curator insight, July 26, 11:21 AM

I love this map (this one and previous versions) and use(d) it quite often

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COMPLEXITY, PROBLEM SOLVING, AND SUSTAINABLE SOCIETIES, by Joseph A. Tainter, 1996

COMPLEXITY, PROBLEM SOLVING, AND SUSTAINABLE SOCIETIES, by Joseph A. Tainter, 1996 | Complexity - Complex Systems Theory | Scoop.it

Historical knowledge is essential to practical applications of ecological economics. Systems of problem solving develop greater complexity and higher costs over long periods. In time such systems either require increasing energy subsidies or they collapse. Diminishing returns to complexity in problem solving limited the abilities of earlier societies to respond sustainably to challenges, and will shape contemporary responses to global change. To confront this dilemma we must understand both the role of energy in sustaining problem solving, and our historical position in systems of increasing complexity.

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Creating an Artificial World with a New Kind of Cellular Automata

Creating an Artificial World with a New Kind of Cellular Automata | Complexity - Complex Systems Theory | Scoop.it

This paper describes a new concept of cellular automata (CA). XCA consists of a set of arcs (edges). These arcs correspond to cells in CA. At a definite time, the arcs are connected to a directed graph. With each next time step, the arcs are exchanging their neighbors (adjacent arcs) according to rules that are dependent on the status of the adjacent arcs. With the extended cellular automaton (XCA) an artificial world may be simulated starting with a Big Bang. XCA does not require a grid like CA do. However, it can create one, just as the real universe after the big bang generated its own space, which previously did not exist. Examples with different rules show how manifold the concept of XCA is. Like the game of life simulates birth, survival, and death, this game should simulate a system that starts from a singularity, and evolves to a complex space.

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Decoding the Remarkable Algorithms of Ants | Quanta Magazine

Decoding the Remarkable Algorithms of Ants |  Quanta Magazine | Complexity - Complex Systems Theory | Scoop.it
The biologist Deborah Gordon has uncovered how ant colonies search efficiently without central organization, an insight that might improve computer networks.
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Lévy walks

Random walk is a fundamental concept with applications ranging from quantum physics to econometrics. Remarkably, one specific model of random walks appears to be ubiquitous across many fields as a tool to analyze transport phenomena in which the dispersal process is faster than dictated by Brownian diffusion. The Lévy-walk model combines two key features, the ability to generate anomalously fast diffusion and a finite velocity of a random walker. Recent results in optics, Hamiltonian chaos, cold atom dynamics, biophysics, and behavioral science demonstrate that this particular type of random walk provides significant insight into complex transport phenomena. This review gives a self-consistent introduction to Lévy walks, surveys their existing applications, including latest advances, and outlines further perspectives.

 

Lévy walks
V. Zaburdaev, S. Denisov, and J. Klafter
Rev. Mod. Phys. 87, 483

http://dx.doi.org/10.1103/RevModPhys.87.483


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Can’t sort complex from complicated? Check out SFI’s MaxEnt tutorial

Can’t sort complex from complicated? Check out SFI’s MaxEnt tutorial | Complexity - Complex Systems Theory | Scoop.it

A new offering from SFI’s online education resource,Complexity Explorer, gives complexity enthusiasts quantitative tools for distinguishing the "complex" aspects of a system from the merely "complicated."

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[1505.00890] Analysis of food pairing in regional cuisines of India

[1505.00890] Analysis of food pairing in regional cuisines of India | Complexity - Complex Systems Theory | Scoop.it

Any national cuisine is a sum total of its variety of regional cuisines, which are the cultural and historical identifiers of their respective regions. India is home to a number of regional cuisines that showcase its culinary diversity. Here, we study recipes from eight different regional cuisines of India spanning various geographies and climates. We investigate the phenomenon of food pairing which examines compatibility of two ingredients in a recipe in terms of their shared flavor compounds. Food pairing was enumerated at the level of cuisine, recipes as well as ingredient pairs by quantifying flavor sharing between pairs of ingredients. Our results indicate that each regional cuisine follows negative food pairing pattern; more the extent of flavor sharing between two ingredients, lesser their co-occurrence in that cuisine. We find that frequency of ingredient usage is central in rendering the characteristic food pairing in each of these cuisines. Spice and dairy emerged as the most significant ingredient classes responsible for the biased pattern of food pairing. Interestingly while individual spices contribute to negative food pairing, dairy products on the other hand tend to deviate food pairing towards positive side. Our data analytical study highlighting statistical properties of the regional cuisines, brings out their culinary fingerprints that could be used to design algorithms for generating novel recipes and recipe recommender systems. It forms a basis for exploring possible causal connection between diet and health as well as prospection of therapeutic molecules from food ingredients. Our study also provides insights as to how big data can change the way we look at food.

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The Slime Mould Collective - An international network of/for intelligent organisms

The Slime Mould Collective - An international network of/for intelligent organisms | Complexity - Complex Systems Theory | Scoop.it

The Slime Mould Collective is a portal for interesting, progressive and ground breaking research and creative practice working with the simple yet intelligent organisms. If you are involved with or interested in slime moulds as a scientist, artist (or somewhere in between or other) please join and share what you do...

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[1505.05738] Predictability of Critical Transitions

[1505.05738] Predictability of Critical Transitions | Complexity - Complex Systems Theory | Scoop.it

Critical transitions in multistable systems have been discussed as models for a variety of phenomena ranging from the extinctions of species to socio-economic changes and climate transitions between ice-ages and warm-ages. From bifurcation theory we can expect certain critical transitions to be preceded by a decreased recovery from external perturbations. The consequences of this critical slowing down have been observed as an increase in variance and autocorrelation prior to the transition. However especially in the presence of noise it is not clear, whether these changes in observation variables are statistically relevant such that they could be used as indicators for critical transitions. In this contribution we investigate the predictability of critical transitions in conceptual models. We study the the quadratic integrate-and-fire model and the van der Pol model, under the influence of external noise. We focus especially on the statistical analysis of the success of predictions and the overall predictability of the system. The performance of different indicator variables turns out to be dependent on the specific model under study and the conditions of accessing it. Furthermore, we study the influence of the magnitude of transitions on the predictive performance.

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Civilization Far From Equilibrium - Energy, Complexity, and Human Survival

Human societies use complexity -- within their institutions and technologies -- to address their various problems, and they need high-quality energy to create and sustain this complexity. But now greater complexity is producing diminishing returns in wellbeing, while the energetic cost of key sources of energy is rising fast. Simultaneously, humankind's problems are becoming vastly harder, which requires societies to deliver yet more complexity and thus consume yet more energy. Resolving this paradox is the central challenge of the 21st century. Thomas Homer-Dixon holds the CIGI Chair of Global Systems at the Balsillie School of International Affairs in Waterloo, Canada, and is a Professor at the University of Waterloo.

 

https://www.youtube.com/watch?v=4Vf-y3mv57U


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Making Decisions in a Complex Adaptive System

Making Decisions in a Complex Adaptive System | Complexity - Complex Systems Theory | Scoop.it
This article explains how to make effective decisions when operating in a complex adaptive system.
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Using Chaos Theory to Predict and Prevent Catastrophic 'Dragon King' Events

Using Chaos Theory to Predict and Prevent Catastrophic 'Dragon King' Events | Complexity - Complex Systems Theory | Scoop.it

Stop a stock trade and avoid a catastrophic global financial crash. Seal a microscopic crack and prevent a rocket explosion. Push a button to avert a citywide blackout.

Though such situations are mostly fantasies, a new analysis suggests that certain types of extreme events occurring in complex systems – known as dragon king events – can be predicted and prevented.


Via Claudia Mihai, Complexity Digest, Bill Aukett, Jürgen Kanz
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Ali Anani's curator insight, November 9, 2013 3:54 AM

Can we control  the uncontrollable? 

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'Leaders and lifters' help ants move massive meals - BBC News

'Leaders and lifters' help ants move massive meals - BBC News | Complexity - Complex Systems Theory | Scoop.it
In a new study, physicists reveal how ants co-operate to carry huge chunks of food back to their nests.
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complexity map by Brian Castellani - map of complexity science

complexity map by Brian Castellani - map of complexity science | Complexity - Complex Systems Theory | Scoop.it

Feb 09 2015

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Human and nature dynamics (HANDY): Modeling inequality and use of resources in the collapse or sustainability of societies

Human and nature dynamics (HANDY): Modeling inequality and use of resources in the collapse or sustainability of societies | Complexity - Complex Systems Theory | Scoop.it

Highlights

 

HANDY is a 4-variable thought-experiment model for interaction of humans and nature.

The focus is on predicting long-term behavior rather than short-term forecasting.

Carrying Capacity is developed as a practical measure for forecasting collapses.

A sustainable steady state is shown to be possible in different types of societies.

But over-exploitation of either Labor or Nature results in a societal collapse.

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Dealing with Multi-Level Governance and Wicked Problems in Urban Transportation Systems: The Case of Palermo Municipality

Dealing with Multi-Level Governance and Wicked  Problems in Urban Transportation Systems: The Case of Palermo Municipality | Complexity - Complex Systems Theory | Scoop.it
Italian New Public Management (NPM) has been mainly characterized by a political orientation toward power decentralization to local governments and privatization of public companies. Nowadays, local utilities in Italy are often run by joint stock companies controlled by public agencies such as Regional and Municipal Administrations. Due to this transformation, these companies must comply with a set of diverse expectations coming from a wide range of stakeholders, related to their financial, competitive and social performance. Such fragmented governance increases the presence of “wicked” problems in the decision-making sphere of these entities. Given this multi-level governance structure, how do these agents influence public services performance? In recent years, coordination and inter-institutional joint action have been identified as possible approaches for dealing with governance fragmentation and wicked problems deriving from it. How can we adapt a performance management perspective in order to help us reform the system and so have a better collaboration between the stakeholders involved? In order to address and discuss these research questions, a case study will be developed. The case concerns AMAT, the local utility providing the public transportation service in the Municipality of Palermo (Italy). The result of this study is a dynamic model including a set of performance indicators that help us in understanding the impact of the governing structure on the system’s performance.
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Exploiting chaos for applications

Exploiting chaos for applications | Complexity - Complex Systems Theory | Scoop.it
We discuss how understanding the nature of chaotic dynamics allows us to control these systems. A controlled chaotic system can then serve as a versatile pattern generator that can be used for a range of application. Specifically, we will discuss the application of controlled chaos to the design of novel computational paradigms. Thus, we present an illustrative research arc, starting with ideas of control, based on the general understanding of chaos, moving over to applications that influence the course of building better devices.
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Life’s Quantum Crystal Ball

Life’s Quantum Crystal Ball | Complexity - Complex Systems Theory | Scoop.it

Does the ability to predict the future—perhaps with quantum help—define the fundamental difference between living and inanimate matter?

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Some new surprises in chaos

Some new surprises in chaos | Complexity - Complex Systems Theory | Scoop.it
“Chaos is found in greatest abundance wherever order is being sought.
It always defeats order, because it is better organized”
Terry Pratchett
A brief review is presented of some recent findings in the theory of chaotic dynamics. We also prove a statement that could be naturally considered as a dual one to the Poincaré theorem on recurrences. Numerical results demonstrate that some parts of the phase space of chaotic systems are more likely to be visited earlier than other parts. A new class of chaotic focusing billiards is discussed that clearly violates the main condition considered to be necessary for chaos in focusing billiards.
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How random are complex networks

Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks---the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain---and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations, and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness.

 

How random are complex networks
Chiara Orsini, Marija Mitrović Dankulov, Almerima Jamakovic, Priya Mahadevan, Pol Colomer-de-Simón, Amin Vahdat, Kevin E. Bassler, Zoltán Toroczkai, Marián Boguñá, Guido Caldarelli, Santo Fortunato, Dmitri Krioukov

http://arxiv.org/abs/1505.07503


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Complexity in Industrial Ecology: Models, Analysis, and Actions

This special issue brings together articles that illustrate the recent advances of studying complex adaptive systems in industrial ecology (IE). The authors explore the emergent behavior of sociotechnical systems, including product systems, industrial symbiosis (IS) networks, cities, resource consumption, and co-authorship networks, and offer application of complex systems models and analyses. The articles demonstrate the links, relevance, and implications of many (often emerging) fields of study to IE, including network analysis, participatory modeling, nonequilibrium thermodynamics, and agent-based modeling. Together, these articles show that IE itself is a complex adaptive system, where knowledge, frameworks, methods, and tools evolve with and by their applications and use in small and large case studies—multidisciplinary knowledge ecology.

 

Complexity in Industrial Ecology: Models, Analysis, and Actions
Gerard P.J. Dijkema, Ming Xu, Sybil Derrible and Reid Lifset

Journal of Industrial Ecology
Special Issue: Advances in Complex Adaptive Systems and Industrial Ecology
Volume 19, Issue 2, pages 189–194, April 2015

http://dx.doi.org/10.1111/jiec.12280


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