Complexity Theory Resources 2018-05-20T11:08:40+00:00

Complexity Theory Books (6)

  • Complexity: A Guided Tour

    Complexity: A Guided Tour
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    What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of neurons produce something as extraordinarily complex as consciousness? In this remarkably clear and companionable book, leading complex systems scientist Melanie Mitchell provides an intimate tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals.

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  • Complexity: A Very Short Introduction

    Complexity: A Very Short Introduction
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    The importance of complexity is well-captured by Hawking's comment: "Complexity is the science of the 21st century". From the movement of flocks of birds to the Internet, environmental sustainability, and market regulation, the study and understanding of complex non-linear systems has become highly influential over the last 30 years. In this Very Short Introduction, one of the leading figures in the field, John Holland, introduces the key elements and conceptual framework of complexity…

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  • COMPLEXITY: THE EMERGING SCIENCE AT THE EDGE OF ORDER AND CHAOS

    COMPLEXITY: THE EMERGING SCIENCE AT THE EDGE OF ORDER AND CHAOS
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    Why did the stock market crash more than 500 points on a single Monday in 1987? Why do ancient species often remain stable in the fossil record for millions of years and then suddenly disappear? In a world where nice guys often finish last, why do humans value trust and cooperation? At first glance these questions don't appear to have anything in common, but in fact every one of these statements refers to a complex system. The science of complexity studies how single elements, such as a species or a stock, spontaneously organize into complicated structures like ecosystems and economies; stars become galaxies, and snowflakes avalanches almost as if these systems were obeying a hidden yearning for order.

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  • Dynamics of Complex Systems

    Dynamics of Complex Systems
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    Complex' is a word of the times, as in the often-quoted “growing complexity of life.” Science has begun to try to understand complexity in nature , a counterpoint to the traditional scientific objective of understanding the fundamental simplicity of laws of nature. It is believed ,however, that even in the study of complexity there exist simple and therefore comprehensible laws . The field of study of complex systems holds that the dynamics of complex systems are founded on universal principles that may be used to describe disparate problems ranging from particle physics to the economics of societies

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  • Network Science

    Network Science
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    Networks are everywhere, from the internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and the social sciences, introduces network science to an interdisciplinary audience. From the origins of the six degrees of separation to explaining why networks are robust to random failures, the author explores how viruses like Ebola and H1N1 spread, and why it is that our friends have more friends than we do

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  • Networks: A Very Short Introduction

    Networks: A Very Short Introduction
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    Networks are involved in many aspects of everyday life, from food webs in ecology and the spread of pandemics to social networking and public transportation. In fact, some of the most important and familiar natural systems and social phenomena are based on a networked structure. It is impossible to understand the spread of an epidemic, a computer virus, large-scale blackouts, or massive extinctions without taking into account the network structure that underlies all these phenomena. In this Very Short Introduction, Guido Caldarelli and Michele Catanzaro discuss the nature and variety of networks, using everyday examples from society, technology, nature, and history to illuminate the science of network theory

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Complexity Theory Research (20)

  • Power Laws and Rich-Get-Richer Phenomena

    Power Laws and Rich-Get-Richer Phenomena
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    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
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    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
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    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
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    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?
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    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
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    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
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    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
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    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
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    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
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    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
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    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
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    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
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    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
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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. 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
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    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
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    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
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    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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Complexity Theory Course (17)

  • Wolfram Science Summer School

    Wolfram Science Summer School
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    A unique opportunity to do original research at the frontiers of science, the Wolfram Science Summer School helps about 40 students from a diverse range of scientific backgrounds learn about Stephen Wolfram's A New Kind of Science (NKS) and apply it to their fields of interest. Most of these students are advanced undergraduates and early graduate students, but those in different circumstances are considered. We are looking for students who want to move their careers in the NKS direction.

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  • Understanding Complexity

    Understanding Complexity
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    Recent years have seen the introduction of concepts from the new and exciting field of complexity science that have captivated the attention of economists, sociologists, engineers, businesspeople, and many others.

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  • Summer Complexity and Modeling Program

    Summer Complexity and Modeling Program
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    or nearly 30 years, the Santa Fe Institute has challenged and equipped the next generation’s brightest scholars to take on complex problems through schools, fellowships, and youth educational curricula serving students and educators of all ages and backgrounds. SFI Complexity Scholarship programs include instruction by, and interaction with, SFI scientists. Complexity scholars trained at the Santa Fe Institute are working to understand the theoretical foundations and patterns underlying the systems most critical to our future -- economies, ecosystems, conflict, disease, human social institutions, and the global condition. This intensive two-week residential science Summer CAMP introduces participants to complexity science scholarship.

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  • Principles of Complex Systems

    Principles of Complex Systems
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    Many of the problems we face in the modern world revolve around comprehending, controlling, and designing multi-scale, interconnected systems. Networked systems, for example, facilitate the diffusion and creation of ideas, the physical transportation of people and goods, and the distribution and redistribution of energy. Complex systems such as the human body and ecological systems are typically highly balanced, flexible, and robust, but also susceptible to systemic collapse. These complex problems almost always have economic, social, and technological aspects.

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  • Model Thinking

    Model Thinking
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    We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. Evidence shows that people who think with models consistently outperform those who don't. And, moreover people who think with lots of models outperform people who use only one. Why do models make us better thinkers? Models help us to better organize information - to make sense of that fire hose or hairball of data (choose your metaphor) available on the Internet. Models improve our abilities to make accurate forecasts. They help us make better decisions and adopt more effective strategies.

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  • MIT Open Courseware: Networks, Complexity and Its Applications

    MIT Open Courseware: Networks, Complexity and Its Applications
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    Networks are a ubiquitous way to represent complex systems, including those in the social and economic sciences. The goal of the course is to equip students with conceptual tools that can help them understand complex systems that emerge in both nature and social systems. This is a course intended for a general audience and will discuss applications of networks and complexity to diverse systems, including epidemic spreading, social networks and the evolution of economic development.

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  • Masters in Complex Systems and Data Science (MS in CSDS)

    Masters in Complex Systems and Data Science (MS in CSDS)
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    Our Masters in Complex Systems and Data Science (CSDS) trains emerging data scientists to find, model, understand, and tell the stories of the patterns they uncover. 2. Our coursework comprises a balanced core of Complex Systems and Data Science and includes choose-your-own adventure options. 3. The Masters may be earned as a two year stand-alone degree or in one year as part of an Accelerated Masters for UVM undergraduate students.

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  • MSc Network Science

    MSc Network Science
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    Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. The goal of network science is to develop tools to analyse Big Data of interacting complex networks and to propose numerical and analytical frameworks to predict their behaviour

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  • Master of Complex Systems

    Master of Complex Systems
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    This 1.5-2 year program will provide you with the expertise to model, analyse and design resilient technological, socio-economic and socio-ecological systems as well as develop strategies for crisis forecasting and management.

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  • Master and Doctoral Programs in Complexity Sciences

    Master and Doctoral Programs in Complexity Sciences
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    A new curriculum for the Doctoral Program in Complexity Sciences has been approved, in July 2015, by the Portuguese Ministry of Education and Science. The new curriculum comprehends a 1st curricular year and a 2nd and 3rd years mainly dedicated to research at PhD level. (Lisbon)

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  • Name Graduate Certificate in Nonlinear and Complex Systems

    Name Graduate Certificate in Nonlinear and Complex Systems
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    The purpose of the certificate is to broaden the scope of the typical disciplinary graduate student traning program. Students are encouraged to develop interdisciplinary and transferable sets of skills in their course work and research activities. The certificate program helps to guide students toward this broad view by requiring the completion of: a survey course (CNCS 201, Topics in Nonlinear and Complex Systems ); four courses from an approved list; and a Ph.D. dissertation on a topic in the domain of the Center. In addition, the student must have two members of the Center on her or his Ph.D. dissertation committee.

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  • Complex Systems Graduate Certificate

    Complex Systems Graduate Certificate
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    The Center for the Study of Complex Systems (CSCS) and the Horace H. Rackham School of Graduate Studies at the University of Michigan are pleased to offer a Certificate of Graduate Studies in Complex Systems. This interdisciplinary curriculum, leading to a Graduate Certificate in Complex Systems, will introduce students to the ideas and methods used in the study of complex, nonlinear and adaptive systems. The specific aim of this curriculum is to allow students from different fields to integrate the rich paradigms and useful analytic and modeling techniques of complex systems into their own research.

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  • Complex Systems Summer School

    Complex Systems Summer School
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    The Complex Systems Summer School offers an intensive 4-week introduction to complex behavior in mathematical, physical, living, and social systems. The school is for graduate students, postdoctoral fellows, and professionals seeking to transcend traditional disciplinary boundaries and ask big questions about real-life complex systems.

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  • Complex Systems Modeling, Networks, and Data Analytics

    Complex Systems Modeling, Networks, and Data Analytics
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    The course will cover the basic construction and analysis of models including identifying what is to be modeled, constructing a mathematical representation, analysis tools and implementing and simulating the model in a computer program. Particular attention will be paid to choosing the right level of detail for the model, testing its robustness, and discussing which questions a given model can or cannot answer.

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  • Complex Adaptive Systems Science

    Complex Adaptive Systems Science
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    Complex adaptive systems (CASS) science is the study of highly interactive and dynamic systems that change over individual and evolutionary time scales. The spread of epidemics, society-biology interactions of obesity, impacts of agriculture on land degradation, ecological impacts of urban growth and social responses to natural disasters all involve CAS. Human societies have made the modern world more complex than ever before, with over 6 billion individuals living in urban centers of millions of inhabitants, divided into innumerable social and economic roles and organized into hierarchies many levels deep.

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  • Complex Adaptive Systems Masters Program

    Complex Adaptive Systems Masters Program
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    Complex Adaptive Systems (CAS) is an international, interdisciplinary master program at Chalmers University of Technology and the University of Gothenburg in Gothenburg, Sweden. The program is open to international and domestic students with a basic academic degree in the natural, engineering, or mathematical sciences. The focus is to use recently developed methods from complexity science to analyze a wide range of systems. Courses include computer simulations of complex systems, game theory, computational biology, robotics and much more.

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  • MSc in Network Science at Queen Mary University of London

    MSc in Network Science at Queen Mary University of London
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    Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. The goal of network science is to develop tools to analyse Big Data of interacting complex networks and to propose numerical and analytical frameworks to predict their behaviour.

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