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Pardee Distinguished Lecture With Geoffrey West » Pardee Center for the Study of the Longer-Range Future | Boston University

Prof. West, Distinguished Professor and former president of the Santa Fe Institute,  gave the annual Pardee Distinguished Lecture at the Trustee Ballroom. His talk was titled“Growth, Innovation, and the Accelerating Pace of Life from Cells to Cities: Are They Sustainable?” He was invited to deliver this year’s Distinguished Lecture in association with a Pardee Center initiative focusing on The Urban Century.

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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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Reaction-Diffusion Processes on Interconnected Scale-Free Networks

We study the two particle annihilation reaction A+B->Ø A+B→∅ on interconnected scale free networks. We show that the mixing of particles and the evolution of the process are influenced by the number of interconnecting links and by their functional properties, while surprisingly when the interconnecting links have the same function as the links within the networks, they are not affected by the interconnectivity strategies in use. Due to the better mixing, which suppresses the segregation effect, we show that the reaction rates are faster than what was observed in other topologies, in-line with previous studies performed on single scale free networks.

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Interview: Prof Geoffrey West on complexity science

CLC interviewed Prof. Geoffrey West, Distinguished Professor and Past President of Sante Fe Institute, at the World Cities Summit 2014 on the study of cities in relation to complexity science....

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Enlarging the scope: grasping brain complexity

To further advance our understanding of the brain, new concepts and theories are needed. In particular, the ability of the brain to create information flows must be reconciled with its propensity for synchronization and mass action. The theoretical and empirical framework of Coordination Dynamics, a key aspect of which is metastability, are presented as a starting point to study the interplay of integrative and segregative tendencies that are expressed in space and time during the normal course of brain and behavioral function. Some recent shifts in perspective are emphasized, that may ultimately lead to a better understanding of brain complexity.

 

Front. Syst. Neurosci., 25 June 2014 | http://dx.doi.org/10.3389/fnsys.2014.00122

Enlarging the scope: grasping brain complexity
Emmanuelle Tognoli and J. A. Scott Kelso


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[1407.2425] Spatial maximum entropy modeling from presence/absence tropical forest data

Understanding the assembly of ecosystems to estimate the number of species at different spatial scales is a challenging problem. Until now, maximum entropy approaches have lacked the important feature of considering space in an explicit manner. We propose a spatially explicit maximum entropy model suitable to describe spatial patterns such as the species area relationship and the endemic area relationship. Starting from the minimal information extracted from presence/absence data, we compare the behavior of two models considering the occurrence or lack thereof of each species and information on spatial correlations. Our approach uses the information at shorter spatial scales to infer the spatial organization at larger ones. We also hypothesize a possible ecological interpretation of the effective interaction we use to characterize spatial clustering.

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The scaling of human interactions with city size

The size of cities is known to play a fundamental role in social and economic life. Yet, its relation to the structure of the underlying network of human interactions has not been investigated empirically in detail. In this paper, we map society-wide communication networks to the urban areas of two European countries. We show that both the total number of contacts and the total communication activity grow superlinearly with city population size, according to well-defined scaling relations and resulting from a multiplicative increase that affects most citizens. Perhaps surprisingly, however, the probability that an individual's contacts are also connected with each other remains largely unaffected. These empirical results predict a systematic and scale-invariant acceleration of interaction-based spreading phenomena as cities get bigger, which is numerically confirmed by applying epidemiological models to the studied networks. Our findings should provide a microscopic basis towards understanding the superlinear increase of different socioeconomic quantities with city size, that applies to almost all urban systems and includes, for instance, the creation of new inventions or the prevalence of certain contagious diseases.

 

Markus Schläpfer, Luís M. A. Bettencourt, Sébastian Grauwin, Mathias Raschke, Rob Claxton, Zbigniew Smoreda, Geoffrey B. West, and Carlo Ratti
The scaling of human interactions with city size
J. R. Soc. Interface. 2014 11 20130789; http://dx.doi.org/10.1098/rsif.2013.0789

 

on ArXiv: http://arxiv.org/abs/1210.5215


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on ArXiv: http://arxiv.org/abs/1210.5215

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Large-scale Fluctuations of Lyapunov Exponents in Diffusive Systems

We present a general formalism for computing Lyapunov exponents and their fluctuations in spatially extended systems described by diffusive fluctuating hydrodynamics, thus extending the concepts of dynamical system theory to a broad range of non-equilibrium systems. Our analytical results compare favorably with simulations of a lattice model of heat conduction. We further show how the computation of Lyapunov exponents for the Symmetric Simple Exclusion Process relates to damage spreading and to a two-species pair annihilation process, for which our formalism yields new finite size results.

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Combining segregation and integration: Schelling model dynamics for heterogeneous population

The Schelling model is a simple agent based model that demonstrates how individuals' relocation decisions generate residential segregation in cities. Agents belong to one of two groups and occupy cells of rectangular space. Agents react to the fraction of agents of their own group within the neighborhood around their cell. Agents stay put when this fraction is above a given tolerance threshold but seek a new location if the fraction is below the threshold. The model is well known for its tipping point behavior: an initial random (integrated) pattern remains integrated when the tolerance threshold is below 1/3 but becomes segregated when the tolerance threshold is above 1/3.
In this paper, we demonstrate that the variety of the Schelling model steady patterns is richer than the segregation-integration dichotomy and contains patterns that consist of segregated patches for each of the two groups alongside patches where both groups are spatially integrated. We obtain such patterns by considering a general version of the model in which the mechanisms of agents' interactions remain the same but the tolerance threshold varies between agents of both groups.
We show that the model produces patterns of mixed integration and segregation when the tolerance threshold of most agents is either below the tipping point or above 2/3. In these cases, the mixed patterns are relatively insensitive to the model's parameters.

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Game Theory Makes New Predictions for Evolution | Simons Foundation

Game Theory Makes New Predictions for Evolution | Simons Foundation | Complexity - Complex Systems Theory | Scoop.it
An insight borrowed from computer science suggests that evolution values both fitness and diversity.

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The direction of evolution: The rise of cooperative organization

The direction of evolution: The rise of cooperative organization | Complexity - Complex Systems Theory | Scoop.it

Two great trends are evident in the evolution of life on Earth: towards increasing diversification and towards increasing integration. Diversification has spread living processes across the planet, progressively increasing the range of environments and free energy sources exploited by life. Integration has proceeded through a stepwise process in which living entities at one level are integrated into cooperative groups that become larger-scale entities at the next level, and so on, producing cooperative organizations of increasing scale (for example, cooperative groups of simple cells gave rise to the more complex eukaryote cells, groups of these gave rise to multi-cellular organisms, and cooperative groups of these organisms produced animal societies). The trend towards increasing integration has continued during human evolution with the progressive increase in the scale of human groups and societies. The trends towards increasing diversification and integration are both driven by selection. An understanding of the trajectory and causal drivers of the trends suggests that they are likely to culminate in the emergence of a global entity. This entity would emerge from the integration of the living processes, matter, energy and technology of the planet into a global cooperative organization. Such an integration of the results of previous diversifications would enable the global entity to exploit the widest possible range of resources across the varied circumstances of the planet. This paper demonstrates that it's case for directionality meets the tests and criticisms that have proven fatal to previous claims for directionality in evolution.


The direction of evolution: The rise of cooperative organization
John E. Stewart

Biosystems
Available online 1 June 2014

http://dx.doi.org/10.1016/j.biosystems.2014.05.006


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Eli Levine's curator insight, June 15, 10:06 PM

Cooperation is the best way to improve, sustain, maintain, and repair.  Competition is what drives everyone and everything towards something different, be it competition for resources or competition against the elements around us.

 

I don't get what the point of competition amongst the species is for.  Part of cooperation, after all, is knowing what works, learning about what could work better or doesn't work, and then letting the negative or sub-optimal slip back beneath the waves of ignorance, such that the new ways can rise to prominence.

 

Change is the only constant in this universe of universes.

 

Yet cooperation, I think, yields the higher and stronger of the universal structures that are out there, even if it means that there are still losers and winners.  The only difference is the level of consent and consensus that's reached within the social, ecological, economical, and/or political landscape.  One way works towards what is best.  The other way simply yields what is best at competing, which is not the same as being the actual best solution to a given problem or condition.

 

Think about it.

Luciano Lampi's curator insight, June 16, 9:51 AM

is this the end of stove pipes?

Ra's curator insight, June 22, 6:02 AM

Have I been reading too much science fiction?

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NSF Research Helps UNESCO Preserve Subaks in Bali

NSF Research Helps UNESCO Preserve Subaks in Bali | Complexity - Complex Systems Theory | Scoop.it
Immersed in the world of Balinese water temples and cooperative farms, Anthropologist J. Stephen Lansing’s NSF funded research helped win UNESCO World Heritage Site status for Bali’s subaks.
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Designing Complex Dynamics in Cellular Automata with Memory

Since their inception at Macy conferences in later 1940s complex systems remain the most controversial topic of inter-disciplinary sciences. The term `complex system' is the most vague and liberally used scientific term. Using elementary cellular automata (ECA), and exploiting the CA classification, we demonstrate elusiveness of `complexity' by shifting space-time dynamics of the automata from simple to complex by enriching cells with {\it memory}. This way, we can transform any ECA class to another ECA class --- without changing skeleton of cell-state transition function --- and vice versa by just selecting a right kind of memory. A systematic analysis display that memory helps `discover' hidden information and behaviour on trivial --- uniform, periodic, and non-trivial --- chaotic, complex --- dynamical systems.

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ECCS 2014 Satellite

ECCS 2014 Satellite | Complexity - Complex Systems Theory | Scoop.it

Workshop on Robustness, Adaptability and Critical Transitions in Living Systems. Submit your Abstract at http://seis.bristol.ac.uk/~fs13378/eccs_2014_livingsys.html

Follow updates @SamirSuweis

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Networks as a Privileged Way to Develop Mesoscopic Level Approaches in Systems Biology

The methodologies advocated in computational biology are in many cases proper system-level approaches. These methodologies are variously connected to the notion of “mesosystem” and thus on the focus on relational structures that are at the basis of biological regulation. Here, I describe how the formalization of biological systems by means of graph theory constitutes an extremely fruitful approach to biology. I suggest the epistemological relevance of the notion of graph resides in its multilevel character allowing for a natural “middle-out” causation making largely obsolete the traditional opposition between “top-down” and “bottom-up” styles of reasoning, so fulfilling the foundation dream of systems science of a direct link between systems analysis and the underlying physical reality.

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Crowdsourcing for Participatory Democracies: Efficient Elicitation of Social Choice Functions

We present theoretical and empirical results demonstrating the usefulness of voting rules for participatory democracies. We first give algorithms which efficiently elicit \epsilon-approximations to two prominent voting rules: the Borda rule and the Condorcet winner. This result circumvents previous prohibitive lower bounds and is surprisingly strong: even if the number of ideas is as large as the number of participants, each participant will only have to make a logarithmic number of comparisons, an exponential improvement over the linear number of comparisons previously needed. We demonstrate the approach in an experiment in Finland's recent off-road traffic law reform, observing that the total number of comparisons needed to achieve a fixed \epsilon approximation is linear in the number of ideas and that the constant is not large.
Finally, we note a few other experimental observations which support the use of voting rules for aggregation. First, we observe that rating, one of the common alternatives to ranking, manifested effects of bias in our data. Second, we show that very few of the topics lacked a Condorcet winner, one of the prominent negative results in voting. Finally, we show data hinting at a potential future direction: the use of partial rankings as opposed to pairwise comparisons to further decrease the elicitation time.

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A universal law for capillary rise in corners

We study the capillary rise of wetting liquids in the corners of different geometries and show that the meniscus rises without limit following the universal law: h(t)/a ≈ (ɣt/na)⅓, where ɣ and n stand for the surface tension and viscosity of the liquid while a =√γ /ρɣ g is the capillary length, based on the liquid density p and gravity g. This law is universal in the sense that it does not depend on the geometry of the corner. © 2011 Cambridge University Press.

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Bourdieu Dynamics of Fields from a Modified Axelrod Model

Pierre Bourdieu discussed how an individual's taste relates o his or her social environment, and how the classification of distinct and vulgar among others, arises from at the same time as shapes this taste in his work called La Distinction. Robert Axelrod created a computational model with local convergence and global polarization properties to describe the dissemination of culture by simple selective interactions. In this letter, Axelrod model is modified, while holding to the same original principles, to describe Bourdieu theory. This allows to analyze how the dynamics of society's tastes and trends may vary with a simple approach, considering social structures and to understand which social forces are crucial to change dynamics. Despite the relative simplicity, the present approach clarifies symbolic power relations, a relevant issue for understanding power relation both on large as well as on small and localized scale, with impact on activities ranging from daily life matters to business, politics, and research. This model sheds light on social issues, showing that a small amount of conflict within a class plays a central role in the culture dynamics, being the major responsible for continuous changes in distinction paradigms.

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The Fascinating World of Complex Systems

Part 1:             http://www.multimedia.ethz.ch/campus/zurichmeetsny/?doi=10.3930/ETHZ/AV-80b92958-97b0-4ad7-b07f-b15192931efc&autostart=false
 
Part 2:             http://www.multimedia.ethz.ch/campus/zurichmeetsny/?doi=10.3930/ETHZ/AV-1db36e67-b2d7-4229-8973-ef1bb54dde27&autostart=false
  
http://www.complexsys.org/publicprograms.html


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june holley's curator insight, July 9, 8:40 AM

Videos on complex systems.

Tom Cockburn's curator insight, July 17, 4:07 AM

Interesting

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Evolution’s Contrarian Capacity for Creativity - Facts So Romantic - Nautilus

Evolution’s Contrarian Capacity for Creativity - Facts So Romantic - Nautilus | Complexity - Complex Systems Theory | Scoop.it

One can imagine life evolving again and again, crashing on the rocks of time and circumstance, until finally it hit upon just the right mutation rate—one that eons later would produce organisms and species and ecosystems.

 

 

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Studying Collective Human Decision Making and Creativity with Evolutionary Computation

We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of ideas, each conducted by participating humans. Based on this evolutionary perspective, we generated hypotheses about collective human decision making using agent-based computer simulations. The hypotheses were then tested through several experiments with real human subjects. Throughout this project, we utilized evolutionary computation (EC) in non-traditional ways---(1) as a theoretical framework for reinterpreting the dynamics of idea generation and selection, (2) as a computational simulation model of collective human decision making processes, and (3) as a research tool for collecting high-resolution experimental data of actual collaborative design and decision making from human subjects. We believe our work demonstrates untapped potential of EC for interdisciplinary research involving human and social dynamics.

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Are Big, Rich Cities Greener Than Poor Ones?

Are Big, Rich Cities Greener Than Poor Ones? | Complexity - Complex Systems Theory | Scoop.it
When it comes to cities, being big and rich is better for the planet than being big and poor, according to a new study of carbon dioxide emissions from cities around the world. But is this correct?

Via Claudia Mihai, Roger D. Jones, PhD
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Global Civil Unrest: Contagion, Self-Organization, and Prediction

Global Civil Unrest: Contagion, Self-Organization, and Prediction | Complexity - Complex Systems Theory | Scoop.it

Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, records of civil unrest of 170 countries during the period 1919–2008 are analyzed. It is demonstrated that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.

 

 

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The Science of Inequality

The Science of Inequality | Complexity - Complex Systems Theory | Scoop.it

In 2011, the wrath of the 99% kindled Occupy movements around the world. The protests petered out, but in their wake an international conversation about inequality has arisen, with tens of thousands of speeches, articles, and blogs engaging everyone from President Barack Obama on down. Ideology and emotion drive much of the debate. But increasingly, the discussion is sustained by a tide of new data on the gulf between rich and poor.

This special issue uses these fresh waves of data to explore the origins, impact, and future of inequality around the world. Archaeological and ethnographic data are revealing how inequality got its start in our ancestors (see pp. 822 and 824). New surveys of emerging economies offer more reliable estimates of people's incomes and how they change as countries develop (see p. 832). And in the past decade in developed capitalist nations, intensive effort and interdisciplinary collaborations have produced large data sets, including the compilation of a century of income data and two centuries of wealth data into the World Top Incomes Database (WTID) (see p. 826 and Piketty and Saez, p. 838).

Science 23 May 2014: 
Vol. 344 no. 6186 pp. 818-821 
DOI: 10.1126/science.344.6186.818


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Nigel Goldenfeld: We Need a Theory of Life

Nigel Goldenfeld: We Need a Theory of Life | Complexity - Complex Systems Theory | Scoop.it
I was intrigued when Carl Woese told me his collaboration with University of Illinois physicist Nigel Goldenfeld was the most productive one of his entire career, and was pleased to finally run into Goldenfeld last September at lunch in the courtyard...
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▶ Large-Scale Structure in Networks - YouTube

▶ Large-Scale Structure in Networks - YouTube | Complexity - Complex Systems Theory | Scoop.it
Mark Newman May 2, 2014 Annual Science Board Symposium and Meeting Complexity: Theory and Practice
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Eli Levine's curator insight, June 9, 2:40 AM

To know the structure is to know a HUMONGOUS part of the function and, thus, the ability to predict.  It seems to me to be a large fractal pattern of clusters, nodes and connections (but, that is just in my relatively uneducated eye). 

 

Never forget, though, that there are important qualitative aspects to networks (think of defacto qualities of the nodes, groups of nodes and the connections amongst them).  Very important for social and/or ecological/causal relation networks (essentially, a network that outlines and maps accurately the function of a system and all of the flows of information and material resources).

 

Really cool stuff here.

 

Think about it..

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Dynamics of Complex Systems - Y. Bar-Yam

Dynamics of Complex Systems - Y. Bar-Yam | Complexity - Complex Systems Theory | Scoop.it

Textbook for seminar/course on complex systems.
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The study of complex systems in a unified framework has become recognized in recent years as a new scientific discipline, the ultimate of interdisciplinary fields. Breaking down the barriers between physics, chemistry and biology and the so-called soft sciences of psychology, sociology, economics, and anthropology, this text explores the universal physical and mathematical principles that govern the emergence of complex systems from simple components.

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