Resources Research Papers 2018-04-30T17:17:58+00:00

Complexity Theory Research (20)

  • Power Laws and Rich-Get-Richer Phenomena

    Power Laws and Rich-Get-Richer Phenomena

    Ideas from the analysis of information cascades and network effects provide the basis for a very natural mechanism to generate power laws. Just as normal distributions arise from many independent random decisions averaging out, we will find that power laws arise from the feedback introduced by correlated decisions across a population.

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  • Causality Principle & Non-Equilibrium Thermodynamics

    Causality Principle & Non-Equilibrium Thermodynamics

    In real life situations, open systems in non-equilibrium are sometimes in steady state and sometimes in non-steady states. Steady state is obtained when forces and counter forces interact. However, when multiple forces are operative involving autocatalysis (positive feedback) and inhibitory step (negative feedback), exotic non-equilibrium phenomena are observed.

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  • Organizational Path Dependence

    Organizational Path Dependence
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    To enable a better understanding of the underlying logic of path dependence, we set forth a theoretical framework explaining how organizations become path dependent. At its core are the dynamics of self-reinforcing mechanisms, which are likely to lead an organization into a lock-in. By drawing on studies of technological paths, we conceptualize the emergent process of path dependence along three distinct stages.

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  • Power law Distribution in Empirical Data

    Power law Distribution in Empirical Data

    Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the detection and characterization of power laws is complicated by the large fluctuations that occur in the tail of the distribution—the part of the distribution representing large but rare events— and by the difficulty of identifying the range over which power-law behavior holds.

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  • Self-Organised Criticality Primer

    Self-Organised Criticality Primer

    The last decade and a half has seen an ardent development of self-organised criticality (SOC), a new approach to complex systems, which has become important in many domains of natural as well as social science, such as geology, biology, astronomy, and economics, to mention just a few. This has led many to adopt a generalist stance towards SOC, which is now repeatedly claimed to be a universal theory of complex behaviour.

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  • Self-Organised Criticality

    Self-Organised Criticality
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    The concept of self-organized criticality was introduced to explain the behaviour of the sandpile model. In this model, particles are randomly dropped onto a square grid of boxes. When a box accumulates four particles they are redistributed to the four adjacent boxes or lost off the edge of the grid. Redistributions can lead to further instabilities with the possibility of more particles being lost from the grid, contributing to the size of each ‘avalanche’.

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  • What is a Complex System?

    What is a Complex System?

    Complex systems research is becoming ever more important in both the natural and social sciences. It is commonly implied that there is such a thing as a complex system, different examples of which are studied across many disciplines. However, there is no concise definition of a complex system, let alone a definition on which all scientists agree. We review various attempts to characterize a complex system, and consider a core set of features that are widely associated with complex systems in the literature and by those in the field

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  • Complex Systems: Why Do They Need to Evolve

    Complex Systems: Why Do They Need to Evolve

    We live in a world characterized by evolution—that is, by ongoing processes of development, formation, and growth in both natural and human-created systems. Biology tells us that complex, natural systems are not created all at once but must instead evolve over time. We are becoming increasingly aware that evolutionary processes are ubiquitous and critical for social, educational, and technological innovations as well.

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  • Complex Adaptive Systems

    Complex Adaptive Systems

    The various at the Santa Fe Institute studying complex adaptive systems(CAS) have somewhat different points of view and have adopted different vocabularies. Some of us speak of “artificial life” or “artificial social life” or “artificial worlds,” while others, of whom I am one, prefer to consider natural CAS and computer-based systems together.

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  • On Network Theory

    On Network Theory

    The theory of self-organization and adaptivity has grown out of a variety of disciplines, including thermodynamics, cybernetics and computer modelling. The present article reviews its most important concepts and principles. It starts with an intuitive overview, illustrated by the examples of magnetization and Bénard convection, and concludes with the basics of mathematical modelling.

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  • The Science of Self Organization & Adaptivity

    The Science of Self Organization & Adaptivity

    The theory of self-organization and adaptivity has grown out of a variety of disciplines, including thermodynamics, cybernetics and computer modelling. The present article reviews its most important concepts and principles. It starts with an intuitive overview, illustrated by the examples of magnetization and Bénard convection, and concludes with the basics of mathematical modelling.

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  • Complex Systems: A Survey

    Complex Systems: A Survey

    A complex system is a system composed of many interacting parts, often called agents, which displays collective behavior that does not follow trivially from the behaviors of the individual parts. Examples include condensed matter systems, ecosystems, stock markets and economies, biological evolution, and indeed the whole of human society.

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  • The Architecture of Complexity

    The Architecture of Complexity

    We are surrounded by complex systems, from cells made of thousands of molecules to society, a collection of billions of interacting individuals. These systems display signatures of order and self-organization. Understanding and quantifying this complexity is a grand challenge for science.

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  • Primer on Complexity, Self-organization & Emergence

    Primer on Complexity, Self-organization & Emergence
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    Complex Systems Science aims to understand concepts like complexity, self-organization, emergence and adaptation, among others. The inherent fuzziness in complex systems definitions is complicated by the unclear relation among these central processes: does self-organisation emerge or does it set the preconditions for emergence? Does complexity arise by adaptation or is complexity necessary for adaptation to arise?

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  • A Simple Guide to Chaos and Complexity

    A Simple Guide to Chaos and Complexity

    The concepts of complexity and chaos are being invoked with increasing frequency in the health sciences literature. However, the concepts underpinning these concepts are foreign to many health scientists and there is some looseness in how they have been translated from their origins in mathematics and physics, which is leading to confusion and error in their application.

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  • Complex Adaptive Systems: Exploring The Known

    Complex Adaptive Systems: Exploring The Known

    The study of complex adaptive systems, from cells to societies, is a study of the interplay among processes operating at diverse scales of space, time and organizational complexity. The key to such a study is an understanding of the interrelationships between microscopic processes and macroscopic patterns, and the evolutionary forces that shape systems.

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  • The Dynamics of Complex Systems

    The Dynamics of Complex Systems

    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. It is strongly rooted in the advances that have been made in diverse fields ranging from physics to anthropology, from which it draws inspiration and to which it is relevant.

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  • Complex Systems Primer

    Complex Systems Primer

    Systems are entities composed of well‐defined components. When integrated the components act together as to form a functioning whole with dynamical behaviors and responses to the environment. Systems can be embedded into other functional entities as components. Identifying a system or a hierarchy of systems requires a certain level of abstraction and simplification.

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  • Complex Adaptive Systems

    Complex Adaptive Systems

    Complexity theory is a relatively new field that began in the mid-1980s at the Santa Fe Institute in New Mexico. Work at the Santa Fe Institute is usually presented as the study of Complex Adaptive Systems (CAS). The CAS movement is predominantly American, as opposed to the European “natural science” tradition in the area of cybernetics and systems.

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  • Modeling Complex Systems

    Modeling Complex Systems

    This paper offers a brief description and summary of the characteristics of complex adaptive systems. The use of computer software such as StarLogo and NetLogo is presented as a powerful way to explore the dynamics of such systems.

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Systems Design Research (20)

  • A primer on the design and science of complex systems

    A primer on the design and science of complex systems
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    Electrical networks, flocking birds, transportation hubs, weather patterns, commercial organisations, swarming robots... Increasingly, many of the systems that we want to engineer or understand are said to be ‘complex’. These systems are often considered to be intractable because of their unpredictability, non-linearity, interconnectivity, heterarchy and ‘emergence’.

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  • Complex Engineered Systems

    Complex Engineered Systems

    Future scientific and technological developments in many fields will necessarily depend upon coming to grips with complex systems. Such systems are complex in both their composition (typically many different kinds of components interacting with each other and their environments on multiple levels) and in the rich diversity of behavior of which they are capable.

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  • Co-Creation & the New Landscapes of Design

    Co-Creation & the New Landscapes of Design

    Designers have been moving increasingly closer to the future users of what they design and the next new thing in the changing landscape of design research has become co-designing with your users. But co-designing is actually not new at all, having taken distinctly different paths in the US and in Europe.

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  • Self-Assembly, Self-Organization

    Self-Assembly, Self-Organization

    Put the different parts of a car in a big box, and shake the whole, will you get a car? This image is often used to express what self-assembly can achieve. Spontaneous arrangements of small building blocks in ordered patterns or structures are ubiquitous in living systems, and they are crucial for designing at the nanoscale, where human hands and tools are helpless.

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  • The Social Internet of Things

    The Social Internet of Things

    Recently there has been quite a number of independent research activities that investigate the potentialities of integrating social networking concepts into Internet of Things (IoT) solutions. The resulting paradigm, named Social Internet of Things (SIoT), has the potential to support novel applications and networking services for the IoT in more e

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  • Innovation in Networked Infrastructures

    Innovation in Networked Infrastructures

    Infrastructures are the systems that provide energy and water, that remove waste water and wastes, that facilitate the movement of people and goods, and that enable us to communicate and exchange information without being troubled by distance. Infrastructure systems are designed to satisfy specific social needs, but they shape social change at a much broader and more complex level.

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  • Introducing Inverse Infrastructures

    Introducing Inverse Infrastructures

    The current dominant paradigm of contemporary infrastructure1 design is that of Hughesian large-scale technical systems (LTSs) (Hughes 1983). However, we see unprecedented infrastructures emerging that are not owned by governments or large businesses. They are not governed centrally or controlled top-down by government or industry as telecommunications, energy networks, and railways, for example, have been for decades. Instead

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  • Path Dependence in Technologies & Organizations

    Path Dependence in Technologies & Organizations

    The note on which an entry for the Palgrave Encyclopedia of Strategic Management will draw offers a beginner’s guide to path dependency in technologies and organizations. We address the very meaning of the concept and its centrality in various aspects of economic analysis. We outline the various levels of the economic system where it is observable, its sources, consequences and different formal representations of path dependent processes.

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  • Emergence Versus Self-Organisation

    Emergence Versus Self-Organisation

    A clear terminology is essential in every research discipline. In the context of ESOA, a lot of confusion exists about the meaning of the terms emergence and self-organisation. One of the sources of the confusion comes from the fact that a combination of both phenomena often occurs in dynamical systems.

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  • Understanding Complex Systems: Infrastructure Impacts

    Understanding Complex Systems: Infrastructure Impacts

    Prior to the 1990s, little attention was given to infrastructure interdependencies. However, recent events such as the Baltimore Howard Street Tunnel train derailment, the Northeast electric power blackout and hurricane Katrina, have brought the importance of infrastructure interdependencies to the forefront.

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  • Complex Systems & Systems Engineering

    Complex Systems & Systems Engineering

    One may define a complex system as a system in which phenomena emerge as a consequence of multiscale interaction among the system’s components and their environments. The field of Complex Systems is the study of such systems—usually naturally occurring, either biological or social.

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  • Complex Engineered Systems: A New Paradigm

    Complex Engineered Systems: A New Paradigm

    Human history is often seen as an inexorable march towards greater complexity — in ideas, artifacts, social, political and economic systems, technology, and in the structure of life itself. While we do not have detailed knowledge of ancient times, it is reasonable to conclude that the average resident of New York City today faces a world of much greater complexity than the average denizen of Carthage or Tikal.

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  • How to Design Self-Organizing Systems

    How to Design Self-Organizing Systems

    The behavior of a self-organizing system (SOS) is typically defined by the local interaction rules of the components. While this emergent behavior typically is very flexible, i.e., working at different scales being robust against disturbances and failures, there exists no straight-forward way for the design of these rules so that the overall system shows the desired properties.

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  • When Systems Engineering Fails

    When Systems Engineering Fails

    We review the lessons learned from problems with systems engineering over the past couple of decades and suggest that there are two effective strategies for overcoming them: (1) restricting the conventional systems engineering process to not-too-complex projects, and (2) adopting an evolutionary paradigm for complex systems engineering that involves rapid parallel exploration and a context designed to promote change through competition between design/implementation groups with field testing of multiple variants. The second approach is an extension of many of the increasingly popular variants of systems engineering today

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  • Understanding Complex Service Systems

    Understanding Complex Service Systems
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    The 2011 Grand Challenge in Service conference aimed to explore, analyse and evaluate complex service systems, utilising a case scenario of delivering on improved perception of safety in the London Borough of Sutton, which provided a common context to link the contributions. The key themes that emerged included value co-creation, systems and networks, ICT and complexity, for which we summarise the contributions. Contributions on value co-creation are based mainly on empirical research and provide a variety of insights including the importance of better understanding collaboration within value co-creation. Contributions on the systems perspective, considered to arise from networks of value co-creation, include efforts to understand the implications of the interactions within service systems, as well as their interactions with social systems, to co-create value. Contributions within the technological sphere, providing ever greater connectivity between entities, focus on the creation of new value constellations and new demand being fulfilled through hybrid offerings of physical assets, information and people. Contributions on complexity, arising from the value cocreation networks of technology enabled services systems, focus on the challenges in understanding, managing and analysing these complex service systems. The theory and applications all show the importance of understanding service for the future

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  • Designing Complex Systems

    Designing Complex Systems

    Networked infrastructures are complex socio-technical systems. The complexity shows in the physical networks, in the actor networks, and in their combination. This paper addresses the question how these systems should be designed. For the physical networks as well as the actor networks, design processes exist that could be applied separately. However, for these integrated networks an integrated approach is proposed. Three cases studies of designs are discussed concerning a district heating system, a gas network and a seaport development. The studies lead to the conclusion that an integrated socio-technical complex system design process must be applied

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  • Complex Engineered Systems: A New Paradigm

    Complex Engineered Systems: A New Paradigm

    Human history is often seen as an inexorable march towards greater complexity — in ideas, artifacts, social, political and economic systems, technology, and in the structure of life itself. While we do not have detailed knowledge of ancient times, it is reasonable to conclude that the average resident of New York City today faces a world of much greater complexity than the average denizen of Carthage or Tikal. A careful consideration of this change, however, suggests that most of it has occurred recently, and has been driven primarily by the emergence of technology as a force in human life. In the 4000 years separating the Indus Valley Civilization from 18th century Europe, human transportation evolved from the bullock cart to the hansom, and the methods of communication used by George Washington did not differ significantly from those used by Alexander or Rameses. The world has moved radically towards greater complexity in the last two centuries.

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  • Modularity in the Design of Complex Engineering Systems

    Modularity in the Design of Complex Engineering Systems
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    In the last decade, the concept of modularity has caught the attention of engineers, management researchers and corporate strategists in a number of industries. When a product or process is “modularized,” the elements of its design are split up and assigned to modules according to a formal architecture or plan. From an engineering perspective, a modularization generally has three purposes: To make complexity manageable; To enable parallel work; and To accommodate future uncertainty

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  • Foundations for Complex Systems Research in the Physical Sciences and Engineering

    Foundations for Complex Systems Research in the Physical Sciences and Engineering

    Science and engineering have long sought principles for the organization and understanding of complex systems. The impetus to study complex systems is driven both by  curiosity as exemplified in the aphorism “the whole is more than the sum of its parts” and  the need to deal with important problems of national interest such as critical infrastructure, sustainability and epidemics . Many complex systems like the power grid, transportation networks and the web demand immediate attention. They have high levels of uncertainty, lack master plans and are susceptible to breakdowns that could have catastrophic consequences. Stronger foundations for the science of complex systems are needed to mitigate these risks and manage these continually evolving systems. A deeper understanding of complex systems will also facilitate the development of controls and strategies to make systems more efficient.

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  • Complexity Management for Projects, Programmes, and Portfolios: An Engineering Systems Perspective

    Complexity Management for Projects, Programmes, and Portfolios: An Engineering Systems Perspective

    Complexity has received wide attention from practitioners and academics alike. We have made significant progress in understanding the different aspects of complexity in projects, programmes, and portfolios. Yet there is still significant work to be done in bridging complexity concepts and managerial reality. In this whitepaper, we discuss the aspects of complexity, how it impacts projects, programmes, and portfolios and what we can do about it. Drawing upon the emerging field of engineering systems, the paper helps us to understand the intricate nature of complexity, uncertainty, and human behaviour, covering both structural and dynamic dimensions. It further outlines the potential challenges in practices by connecting the abstract concepts and management approaches to concrete practical examples. Finally, it introduces cutting-edge tools and strategies for dealing with project complexity covering network analysis, systems dynamics, modularisation, antifragility, and mindfulness.

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Systems Thinking Research (5)

  • Complexity and Systems Thinking

    Complexity and Systems Thinking

    Systems thinking has evolved over the millennia as people have looked for ways to articulate the features of the world around them in a coherent manner.1 Starting from the definition of a system as an integrated whole made up of interconnected parts, various formalizations of systems thinking in a way that would be of interest to managers have emerged over time as people have looked for ways of rationalizing their interactions with the world. These formalizations give us a set of ontological and epistemological devices that have been used to define what the world is, to explain how it works, and to define and justify interventions that are intended to change, control or constrain the future behaviour of that world.

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  • SYSTEMS ARCHETYPES

    SYSTEMS ARCHETYPES
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    Systems Archetypes I helps you understand the structure and story line of the archetypes–those “common stories” in systems thinking. Each two-page description leads you through an archetype and outlines ways to use the archetype to address your own business issues.

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  • Introduction To Systems Thinking

    Introduction To Systems Thinking
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    System. We hear and use the word all the time. “There’s no sense in trying to buck the system,” we might say. Or, “This job’s getting out of control, I’ve got to establish a system.” Whether you are aware of it or not, you are a member of many systems – a family, a community, a church, a company.

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  • A Definition of Systems Thinking: A Systems Approach

    A Definition of Systems Thinking: A Systems Approach
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    This paper proposes a definition of systems thinking for use in a wide variety of disciplines, with particular emphasis on the development and assessment of systems thinking educational efforts. The definition was derived from a review of the systems thinking literature combined with the application of systems thinking to itself. Many different definitions of systems thinking can be found throughout the systems community, but key components of a singular definition can be distilled from the literature. This researcher considered these components both individually and holistically, then proposed a new definition of systems thinking that integrates these components as a system

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  • What is Systemic Thinking?

    What is Systemic Thinking?

    Systemic Thinking (ST) offers you a powerful new perspective, a specialized language, and a set of tools that you can use to better understand and address stubborn recurring problems in your everyday work and life. ST is a way of understanding reality that emphasizes the relationships between a system’s parts, rather than the parts themselves. Based on a field of study known as systems dynamics, ST has practical every day application that rests on a solid theoretical foundation

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Social Complexity Research (12)

  • What is Social Resilience?

    What is Social Resilience?

    Over the last decade, a growing body of literature has emerged which is concerned with the question of what form a promising concept of social resilience might take. In this article we argue that social resilience has the potential to be crafted into a coherent analytic framework that can build on scientific knowledge from the established concept of social vulnerability, and offer a fresh perspective on today’s challenges of global change.

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  • Estimatin of Social Entropy

    Estimatin of Social Entropy

    The history of Extension Education in India is inevitably flamboyant with a proadoption approach in transfer of technology mode. The much acclaimed Green Revolution in India had been instrumental so far and so on, as some might demand, with transfer of exotic technology, external supply of input and a supply driven knowledge concept. A plethora of extension programs may be bracketed with this so called ‘Transfer of Technology’ mode.

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  • Computational Social Science

    Computational Social Science

    We live life in the network. We check our e-mails regularly, make mobile phone calls from almost any location, swipe transit cards to use public transportation, and make purchases with credit cards.

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  • The Self-Organization of Social Movements

    The Self-Organization of Social Movements
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    The New Social Movement Approach and the Resource Mobilization Approach are the dominant approaches in social movement research. They focus either on macro-aspects and externalism or on micro-aspects and internalism.

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  • Complex Adaptive Systems in the Behavioral and Social Sciences

    Complex Adaptive Systems in the Behavioral and Social Sciences

    This article examines applications of complexity theory within the behavioral and social sciences. Specific attention is given to the fundamental characteristics of complex adaptive systems (CAS)–such as individuals, groups, and societies– including the underlying structure of CAS, the internal dynamics of evolving CAS, and how CAS respond to their environment.

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  • Sociology, Chaos Theory & Complexity Science

    Sociology, Chaos Theory & Complexity Science
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    The ‘new science’ of complexity and chaos theory has grown rapidly in the last three decades aided enormously by the quantum expansion of computers and computing applications. Responding to the energy and enthusiasm of complexity scientists and publicists, social theorists have assimilated concepts of complexity and its potential impacts on sociological theory and social research.

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  • Modelling Culture with Complex, Multi-dimensional, Multi-agent Systems

    Modelling Culture with Complex, Multi-dimensional, Multi-agent Systems

    Culture plays a significant role in human civilizations as a key determinant of relationships and organization formation, however, its role, key properties, and mechanisms are not yet fully understood. This work explores culture and cultural modelling from a complex systems, multi-dimensional, and multi-agency standpoint.

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  • A Network Theory of Social Capital

    A Network Theory of Social Capital

    The concept of “social capital “has captured the imagination and attention of a wide range of scholars and professionals in diverse disciplines and practical arenas. Since the notion of social capital has generated multiple definitions, conceptualizations and empirical measurements…

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  • Governance: Prospects of Complexity Theory in Revisiting System Theory

    Governance: Prospects of Complexity Theory in Revisiting System Theory
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    The broadest meaning of governance is the regulation of social activities utilizing a variety of modes and mechanism of societal regulation. These range from collectively binding decisions to uncoordinated individual action guided by social norms and rationality principles. In the political science literature of the 1950s and 1960s this theoretical problem was treated in terms of “control” and “regulation” by variants of system theory.

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  • On Network Theory

    On Network Theory

    Research on social networks has grown considerably in the last decade. However, there is a certain amount of confusion about network theory—for example, what it is, what is distinctive about it, and how to generate new theory. This paper attempts to remedy the situation by clarifying the fundamental concepts of the field (such as the network) and characterizing how network reasoning works.

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  • Networks and Institutions

    Networks and Institutions

    Research on institutions and networks has proceeded on largely separate trajectories over the past few decades. The former is more associated with work in organizational and political sociology, and the latter serves as the wellspring of research in economic sociology. To be sure, a number of loose linkages exist between the subfields.

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  • A Complex Systems Approach to the Study of Ideology

    A Complex Systems Approach to the Study of Ideology
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    We propose a complex systems approach to the study of political belief systems, to overcome some of the fragmentation in the current scholarship on ideology. We review relevant work in psychology, sociology, and political science and identify major cleavages in the literature: the spatial vs. non-spatial divide…

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Complexity Economics Research (12)

  • What Should Policymakers Know About Economic Complexity?

    What Should Policymakers Know About Economic Complexity?

    This essay is written with two goals. The first is to outline the main ideas underlying the growing study of complex economic environments. The second is to suggest areas of public policy where those ideas might be important. Both goals are necessarily speculative. The study of complex systems, whether natural or social, is still in its infancy.

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  • Path Dependence: ‘Historical Economics’

    Path Dependence: ‘Historical Economics’
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    The concept of path dependence refers to a property of contingent, non-reversible dynamical processes, including a wide array of biological and social processes that can properly be described as ‘evolutionary’. To dispel existing confusions in the literature, and clarify the meaning and significance of path dependence for economists…

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  • Economic Networks: What Do We Know?

    Economic Networks: What Do We Know?

    We examine the emergent field of economic networks and explore its ability to shed light on the global and volatile economy where credit, ownership, innovation, investment, and virtually every other economic activity is carried at a scale and scope that respects no geographical, organizational, or political boundaries.

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  • From Simplistic to Complex Systems in Economics

    From Simplistic to Complex Systems in Economics

    The applicability of complex systems theory in economics is evaluated and compared with standard approaches to economic theorizing based upon constrained optimization. A complex system is defined in the economic context and differentiated from complex systems in physiochemical and biological settings.

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  • Complexity Economics: A Different Framework for Economic Thought

    Complexity Economics: A Different Framework for Economic Thought

    This paper provides a logical framework for complexity economics. Complexity economics builds from the proposition that the economy is not necessarily in equilibrium: economic agents (firms, consumers, investors) constantly change their actions and strategies in response to the outcome they mutually create.

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  • Fundamentals of Complex Evolving Systems

    Fundamentals of Complex Evolving Systems

    Complex Evolving Systems (CES) are definitely not everyone´s bag – they are certainly not on the menu list of the favourite subjects of so-called “Mainstream Economics”. There are reasons for that, but they are not good enough. Therefore, this Primer is intended to help economists cover a deficit in understanding which is not only glaring but – given the current state of the world – has become patently unacceptable.

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  • Why is Economics not a Complex Systems Science?

    Why is Economics not a Complex Systems Science?

    Economics is viewed as a discipline that is mainly concerned with ‘simplistic’ theorizing, centered upon constrained optimization. As such, it is ahistorical and outcome focused, ie, it does not deal with economic processes. It is argued that all parts of the economy are inhabited by complex adaptive systems operating in complicated historical contexts and that this should be acknowledged at the core of economic analysis.

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  • The Stock Market as a Complex Adaptive System

    The Stock Market as a Complex Adaptive System

    It is time to shift the emphasis of the debate about market efficiency. Most academics and practitioners agree that markets are efficient by a reasonable operational criterion: there is no systematic way to exploit opportunities for superior gains.

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  • Rethinking Economics Using Complexity Theory

    Rethinking Economics Using Complexity Theory

    In this paper we argue that if we want to find a more satisfactory approach to tackling the major socio-economic problems we are facing, we need to thoroughly rethink the basic assumptions of macroeconomics and financial theory. Making minor modifications to the standard models to remove “imperfections” is not enough, the whole framework needs to be revisited.

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  • The Building Blocks of Economic Complexity

    The Building Blocks of Economic Complexity

    For Adam Smith, wealth was related to the division of labor. As people and firms specialize in different activities, economic efficiency increases, suggesting that development is associated with an increase in the number of individual activities and with the complexity that emerges from the interactions between them.

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  • Economic Complexity and Human Development

    Economic Complexity and Human Development

    This book combines the human development approach and innovation economics in order to explore the effects that structural economic change has on human development. While economic diversification can provide valuable new social choices and capabilities, it also tends to lead to more complex decision processes and changes to the set of capabilities required by people to self-determine their future.

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  • The Nature of Heterodox Economics

    The Nature of Heterodox Economics
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    Recent years have seen the emergence of numerous activities in economics identified first and foremost as heterodox. For example 1999 witnessed the formation of the Association for Heterodox Economics (AHE), an organisation that now sponsors an annual conference, postgraduate training workshops and more

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Systems Ecology Research (12)

  • Far-From-Equilibrium Physics: An Overview

    Far-From-Equilibrium Physics: An Overview
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    Isolated systems tend to evolve towards equilibrium, a special state that has been the focus of many-body research for a century. Yet much of the richness of the world around us arises from conditions far from equilibrium. Phenomena such as turbulence, earthquakes, fracture, and life itself occur only far from equilibrium.

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  • Social complexity and sustainability

    Social complexity and sustainability

    Social complexity and sustainability emerge from successful problem solving, rather than directly from environmental conditions. Social complexity develops from problem solvingat all scales from local to national and international. Complexity in problem solving is an economic function, and can both support and hinder sustainability. Sustainability outcomes may take decades or centuries to develop.

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  • Ecological Networks & Their Fragility

    Ecological Networks & Their Fragility

    Darwin used the metaphor of a ‘tangled bank’ to describe the complex interactions between species. Those interactions are varied: they can be antagonistic ones involving predation, herbivoryand parasitism, or mutualistic ones, such as those involving the pollination of flowers by insects.

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  • Understanding the Complexity of Economic, Ecological, and Social Systems

    Understanding the Complexity of Economic, Ecological, and Social Systems

    Hierarchies and adaptive cycles comprise the basis of ecosystems and social-ecological systems across scales. Together they form a panarchy. The panarchy describes how a healthy system can invent and experiment, benefiting from inventions that create opportunity while being kept safe from those that destabilize because of their nature or excessive exuberance.

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  • Complexity, Modeling, and Natural Resource Management

    Complexity, Modeling, and Natural Resource Management

    This paper contends that natural resource management (NRM) issues are, by their very nature, complex and that both scientists and managers in this broad field will benefit from a theoretical understanding of complex systems.

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  • Regime Shifts Resilience & Biodiversity

    Regime Shifts Resilience & Biodiversity

    We review the evidence of regime shifts in terrestrial and aquatic environments in relation to resilience of complex adaptive ecosystems and the functional roles of biological diversity in this context. The evidence reveals that the likelihood of regime shifts may increase when humans reduce resilience by such actions as removing response diversity, removing whole functional…

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  • Continuity and Change in Social-ecological Systems: the Role of Institutional Resilience

    Continuity and Change in Social-ecological Systems: the Role of Institutional Resilience

    In recent years recurring political, economic, and environmental crises require questioning and re-evaluating dominant pathways of human development. However, political and economic frameworks seem to encompass deeply rooted resistance to fundamental changes (e.g., global financial crisis, climate change negotiations). In an effort to repair the system as fast as possible, those paradigms, mechanisms, and structures that led into the crisis are perpetuated. Instead of preserving conventional patterns and focusing on continuity, crises could be used as an opportunity for learning, adapting, and entering onto more sustainable pathways.

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  • Resilience: Perspective for Social–Ecological Systems Analyses

    Resilience: Perspective for Social–Ecological Systems Analyses

    The resilience perspective is increasingly used as an approach for understanding the dynamics of social–ecological systems. This article presents the origin of the resilience perspective and provides an overview of its development to date. With roots in one branch of ecology and the discovery of multiple basins of attraction in ecosystems in the 1960–1970s, it inspired social and environmental scientists to challenge the dominant stable equilibrium view. The resilience approach emphasizes non-linear dynamics, thresholds, uncertainty and surprise, how periods of gradual change interplay with periods of rapid change and how such dynamics interact across temporal and spatial scales.

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  • Complex Systems Theory and Biodynamics

    Complex Systems Theory and Biodynamics

    Systems biology is a biology-based inter-disciplinary study field that focuses on the systematic study of complex interactions in biological systems, thus using a new perspective (holism instead of reduction) to study them. Particularly from year 2000 onwards, the term is used widely in the biosciences, and in a variety of contexts.

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  • Complex Systems & Valuation

    Complex Systems & Valuation

    Ecological and economic systems are undeniably complex. Whereas a goal of delineating ‘ecosystem services’ is to make readily apparent some of the important ways in which ecosystems underpin human welfare, insights are also gained by appreciating the nonlinear dynamic properties of ecosystems. In this paper, we review some of the relevant characteristics of complex systems.

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  • Ecosystems and the Biosphere as Complex Adaptive Systems

    Ecosystems and the Biosphere as Complex Adaptive Systems

    Ecosystems are prototypical examples of complex adaptive systems, in which patterns at higher levels emerge from localized interactions and selection processes acting at lower levels. An essential aspect of such systems is nonlinearity, leading to historical dependency and multiple possible outcomes of dynamics.

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  • Complexity in Ecological Systems

    Complexity in Ecological Systems

    Ecology has been eminently a descriptive science despite some pioneering work by theoreticians such as Lotka, Volterra, Nicholson, and others. Description is a first step toward understanding a system. However, such a first step needs to be accompanied by the development of a theoretical framework in order to achieve real insight and, whenever possible, predictive power.

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Complexity Management Research (13)

  • Developing Leaders in a VUCA Environment

    Developing Leaders in a VUCA Environment
    1

    In The World Is Flat, Thomas Friedman notes that the rate of change today is much different than in the past. “Whenever civilization has gone through one of these disruptive, dislocating technical revolutions—like Gutenberg’s introduction of the printing press—the whole world has changed in profound ways…

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  • Complex Social Systems: Rising Complexity in Business Environments

    Complex Social Systems: Rising Complexity in Business Environments
    1

    Attempts to simulate the effects of environmental complexity changes in business yielded the realization that much exploratory work needs to be done to (a) demonstrate that complexity has increased universally, and (b) to elucidate what contributory factors are at work in this environment.

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  • Leading In a Complex World

    Leading In a Complex World

    The world is changing at an increasingly rapid pace and these changes are not just radical they are transformative; transforming every aspect of our lives and transforming boundaries between and within markets. Whilst we can’t explore everything in this article here are some of the big ones that we think have major implications for leaders. Technologies are disrupting sectors and even whole industries faster than ever.

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  • New Tools For Resolving Wicked Problems

    New Tools For Resolving Wicked Problems

    Wicked Problems (equivalently, Social Messes) are seemingly intractable problems. They are composed of inter-related dilemmas, issues, and other problems at multiple levels society, economy, and governance. These interconnections—systems of systems—make Wicked Problems so resilient to analysis and to resolution.

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  • Sense-making in a complex and complicated world

    Sense-making in a complex and complicated world

    In this paper, we challenge the universality of three basic assumptions prevalent in organizational decision support and strategy: assumptions of order, of rational choice, and of intent. We describe the Cynefin framework, a sense-making device we have developed to help people make sense of the complexities made visible by the relaxation of these assumptions.

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  • Complexity and Limits to Knowledge

    Complexity and Limits to Knowledge

    This paper examines how complexity science faces up to the material fact of uncertainty and the very real limits to knowledge. Indeed it shows how ignorance, the impossibility of having full knowledge and the inevitability of uncertainty, are both the result of, and the driving force behind, evolution and change.

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  • The Sage Handbook of Complexity and Management

    The Sage Handbook of Complexity and Management

    The first substantive scholarly work to provide a map of the state-of-the-art research in the growing field emerging at the intersection of complexity science and management studies. Edited and written by internationally respected scholars from management and related disciplines, the Handbook is a reference source for understanding the implications of complexity science for management research and practice.

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  • Decision Theory in Complex Systems

    Decision Theory in Complex Systems

    Human beings are continuously making conscious decisions. Life is a stream of decisions made on a continuum from the subconscious to the fully involved conscious state. Many decisions are made “without thinking” as when we have driven our car to a destination and realize that we were not aware of the actions we were taking to maneuver the automobile.

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  • Managing in an Age of Complexity

    Managing in an Age of Complexity

    From a psychological perspective, it seems that most people prefer certainty to ambiguity and, it seems, would even choose certainty over freedom. In business, certainty suggests we can predict what is going on in our market place and with this information we believe we can then develop the optimal strategy for making money.

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  • A Brief Review of Systems Theories and Their Managerial Applications

    A Brief Review of Systems Theories and Their Managerial Applications

    Systems theory is an interdisciplinary theory about every system in nature, in society and in many scientific domains as well as a framework with which we can investigate phenomena from a holistic approach. Systems thinking comes from the shift in attention from the part to the whole, considering the observed reality as an integrated and interacting unicum of phenomena where the individual properties of the single parts become indistinct.

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  • Applications of Complexity Science for Public Policy

    Applications of Complexity Science for Public Policy

    Government officials and other decision makers increasingly encounter a daunting class of problems that involve systems composed of very large numbers of diverse interacting parts. These systems are prone to surprising, large-scale, seemingly uncontrollable, behaviors. These traits are the hallmarks of what scientists call complex systems.

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  • Managing Complexity: A Discussion of Current Strategies and Approaches

    Managing Complexity: A Discussion of Current Strategies and Approaches

    The “Complex” view of reality is important in understanding the activities of an organization. The inclusion of complexity in management discourse is therefore a natural consequence. Despite this increasing importance, most companies have not introduced or implemented yet a complexity management system/approach or they do not know, if the used complexity management strategy and methods, are efficient and adequate. The aim of this paper is to point out which the strategies and models can be useful method to management complexity. In practice, proposed models are often maturity models. The various levels of maturity within such models can be used to describe the different achievable skill levels. The features of the areas of maturity models have been indicated as elements one of selected complexity management approach. We conclude how this approach may help in management and complexity decision-making support.

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  • Making Sense of the Collaborative Economy

    Making Sense of the Collaborative Economy

    The collaborative economy is becoming difficult to ignore; it is undeniably a global movement that dominates news with tales of startup glory and threats of government responses to industry disruption. Whether people associate their activities with this specific term or not, this report shows that a quarter of the UK population…

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Complexity Science Research (3)

  • Complexity Science

    Complexity Science
    1

    We need to start thinking about the world in a new way, because in some fundamental and essential respects our world has changed its character. We need to shift from seeing the world as composed largely of simple machines to seeing it as composed mainly of complex systems. Seeing the world as composed mainly of simple machines might have been appropriate several decades ago: we commonly thought of our economy, the natural resource systems we were exploiting, and our societies in general as machines that were analogous, essentially, to a windup clock.

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  • A Complexity Science Primer

    A Complexity Science Primer
    2

    This paper is called a 'primer' because it is intended to be a first step in understanding complexity science. In house painting, the primer or prime coat is not the finished surface. A room with a primer on the walls often looks worse than before the painting began.

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  • Nonlinearity in Complexity Science

    Nonlinearity in Complexity Science

    Complexity Science is experiencing a new vogue. The doubts of the previous decade (e.g. [Ho]) seem to have lost their force. Stephen Hawking declared that the 21st century “will be the century of complexity” [Ha]. Complexity Science is receiving serious funding from the European Commission, UK Engineering and Physical Sciences Research Council, and other agencies.

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Nonlinear Systems Research (4)

  • A TUTORIAL INTRODUCTION TO NONLINEAR DYNAMICS

    A TUTORIAL INTRODUCTION TO NONLINEAR DYNAMICS

    This is the second and final parI. of a series of two papers on nonlinear dynamics and chaos. In the first parI some tools. developed for analysing nonlinear systems, were c!esniiJec! in conjunction with a seI. of moc!els commonly llsed as benchmarks in the literature. This papel' investigates a llllIllber of isslles concerning the modeling, signal processillg anel control of nonlinear e1ynamics. This is carrieel ou! llsillg tbe tools and 1D0elels described in the first papel'. This inwstigation has th1'Own some new light on relevant p1'Oblems such as modeI parametrization, modeI validation. data smoothing anel control of nonliear systems

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  • Teaching Nonlinear Dynamics and Chaos for Beginners

    Teaching Nonlinear Dynamics and Chaos for Beginners

    We describe a course in Nonlinear Dynamics for undergraduate students of the first years of Chemical Engineering, Environmental Sciences and Computer Sciences. An extensive use of computational tools, the internet and laboratory experiments are key ingredients of the course. Even though their previous background in physics and mathematics might be limited, our experience shows that an appropriate selection of the contents with the use of some conceptual introductory ideas and multimedia techniques are an excellent way to introduce Nonlinear Dynamics and Chaos for beginners.

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  • An Introduction to Chaos Theory

    An Introduction to Chaos Theory

    The science of complexity involves the principle of Self-Organizing Criticality,of which the human brain is a great example, where large neurons organize themselves to form an extremely complex connective network which can solve complex problems with a rapidity still not matched by present day computers. It has been postulated by Walter Freeman III how chaos plays an important role in brain functioning and attempts to explain how it operates as fast as it does! This short introduction to chaos theory will outline how we can use a chaotic source to produce unlimited amounts of ‘cryptographic keys’ for secure saving of data in Cloud computing (CC).

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  • NONLINEAR SCIENCE from Paradigms to Practicalities

    NONLINEAR SCIENCE from Paradigms to Practicalities

    Nonlinear science is the study of those mathematical systems and natural phenomena that are not linear. Ever attuned to the possibility of bons mots, Stan once remarked that this was “like defining the bulk of zoology by calling it the study of ‘non-elephant animals’.” His point, clearly, was that the vast majority of mathematical equations and natural phenomena are nonlinear, with linearity being the exceptional, but important, case.

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Adaptive Systems Research (3)

  • Complex Adaptive Systems

    Complex Adaptive Systems
    1

    To arrive at a deeper understanding of complex adaptive systems?to understand what makes them complex and what makes them adaptive?it is useful to look at a particular system. Consider the immune system. It consists of large numbers of highly mobile units, called antibodies, that continually repel or destroy an ever-changing cast of invaders (bacteria and biochemicals), called antigens. Because the invaders come in an almost infinite variety of forms, the immune system cannot simply develop a list of all possible invaders

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  • Complex Adaptive Systems: Emergence and Self-Organization

    Complex Adaptive Systems: Emergence and Self-Organization
    1

    CAS studies indirect effects. Problems that are difficult to solve are often hard to understand because the causes and effects are not obviously related. Pushing on a complex system "here" often has effects "over there" because the parts are interdependent.

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  • Complex Adaptive Systems Introduction

    Complex Adaptive Systems Introduction
    1

    The various groups at the Santa Fe Institute studying complex adaptive systems (CAS) have somewhat different points of view and have adopted different vocabularies. Some of us speak of "artificial life" or "artificial social life" or "artificial worlds," while others, of whom I am one, prefer to consider natural CAS and computer-based systems together. The latter include methods for adaptive computation as well as models and simulations of natural CAS.

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Nonlinear Physics Research (3)

  • Teaching Nonlinear Dynamics and Chaos for Beginners - Dialnet

    Teaching Nonlinear Dynamics and Chaos for Beginners - Dialnet

    We describe a course in Nonlinear Dynamics for undergraduate students of the first years of Chemical Engineering, Environmental Sciences and Computer Sciences. An extensive use of computational tools, the internet and laboratory experiments are key ingredients of the course. Even though their previous background in physics and mathematics might be limited, our experience shows that an appropriate selection of the contents with the use of some conceptual introductory ideas and multimedia techniques are an excellent way to introduce Nonlinear Dynamics and Chaos for beginners.

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  • Nonlinear dynamics: Challenges and perspectives

    Nonlinear dynamics: Challenges and perspectives

    The study of nonlinear dynamics has been an active area of research since 1960s, after certain path-breaking discoveries, leading to the concepts of solitons, integrability, bifurcations, chaos and spatio-temporal patterns, to name a few. Several new techniques and methods have been developed to understand nonlinear systems at different levels. Along with these, a multitude of potential applications of nonlinear dynamics have also been enunciated. In spite of these developments, several challenges, some of them fundamental and others on the efficacy of these methods in developing cutting edge technologies, remain to be tackled. In this article, a brief personal perspective of these issues is presented.

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  • Basic Concepts in Nonlinear Dynamics and Chaos

    Basic Concepts in Nonlinear Dynamics and Chaos

    dynamic system is a set of functions (rules, equations) that specify how variables change over time

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Complexity Science Videos (5)

  • Conway's Game of Life

    Conway's Game of Life

    A simulation of Conway's classic cellular automata The Game of Life

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  • Complexity Methods - John Holland

    Complexity Methods - John Holland

    Complex adaptive systems (CAS) – systems such as ecosystems, markets, and the immune system – pose some of the most important problems of the 21st century. Because CAS have no central executive and are made up of diverse agents that learn and adapt as they interact, they are difficult to steer. This difficulty persists even though we have large databases for many CAS.

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  • Complexity science and the role of mathematical modeling

    Complexity science and the role of mathematical modeling

    Tassos Bountis is a Professor at the Department of Mathematics at University of Patras in Greece. As well as lecturing at the University he is also the director of the Center for Research and Application of Nonlinear Systems at the University of Patras.

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  • Modeling Complex Systems

    Modeling Complex Systems

    Stanford Complexity Group lecture on the Mathematics of Complexity

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  • Complex adaptive systems - Igor Nikolic

    Complex adaptive systems - Igor Nikolic

    Igor Nikolic graduated in 2009 on his dissertation: co-evolutionary process for modelling large scale socio-technical systems evolution. He received his MSc as a chemical-- and bioprocess engineer at the Delft University of Technology. He spent several years as an environmental researcher and consultant at University of Leiden where he worked on life cycle analysis and industrial ecology. In his research he specializes in applying complex adaptive systems theory and agent based modeling.

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