• By purchasing this item you will get access to download all of our eBooks. This includes a total of 17 eBooks listed below:

    Complexity Theory Book Complex Adaptive Systems Book Game Theory Book Networks Theory Book Nonlinear Systems Book Critical Thinking Book Emergence Theory Book Systems Theory Book Systems Thinking Book Social Complexity Book Systems Ecology Book Complexity Economics Book Political Complexity Book Complex Engineered System Complex Systems Design Complexity Mangement Blockchain Introduction

    Once you have purchased the item you will receive an email with links to the books for you to start downloading immediately.

  • The Blockchain is a term that has come to mean many things to many people. For developers, it is a set of protocols and encryption technologies for securely storing data on a distributed network. For business and finance, it is a distributed ledger and the technology underlying the explosion of new digital currencies. For technologists, it is the driving force behind the next generation of the internet. For others, it is a tool for radically reshaping society and economy taking us into a more decentralized world.

    Whichever way you look at it, blockchain has become a term that captures the imagination and fascinates many, as the implications of such technology are truly profound. For the first time in human history, people anywhere can trust each other and transact within large peer-to-peer networks without centralized management. Trust is established, not by centralized institutions, but by protocols, cryptography and computer code. This greatly strengthens our capacity for collaboration and cooperation between organizations and individuals within peer networks, enabling us to potentially form global networks of collaboration without centralized formal institutions; unprecedented but hugely relevant in an age of globalization and a new set of 21st-century challenges that require mass collaboration.

    This book accompanies our Blockchain introductory course and is designed as a non-technical overview, it is an introductory course and thus all terms will be explained. The course should be accessible to anyone with a basic understanding of web technologies and economics.

    • Publish Data: 01-01-2018

    • Length: 58 pages

    • Format: PDF

  • Complex adaptive systems are all around us from financial markets, to ecosystems, to the human immune system and even civilization itself. They consist of many agents that are acting and reacting to each other’s behavior, out of this often chaotic set of interactions emerges global patterns of organization in a dynamic world of constant change and evolution where nothing is fixed. In these complex adaptive systems no one is in control, no one has complete information, patterns of order emerge through self- organization between agents. Individual cells self-organize to form differentiated body organs, ants interact and self- organize to form colonies, and people interact to form social networks. These patterns of global organization emerge out of a dynamic between order and chaos that we are only just beginning to understand but as we do we are finding that these apparently very dissimilar systems share fundamental commonalities. The aim of this book is to give a comprehensive, clear and accessible outline to the new area of complex adaptive systems that is finding application in many areas. We will be covering all the main topics within this domain, as we start by talking about adaptation itself where we will be discussing cybernetics and looking at how systems regulate themselves to respond to change. We’ll go on to talk about the dynamics of cooperation and competition, looking at how and why agents work together to create local patterns of organization. Next, we will be talking about the process of self-organization and asking the big questions about how do we get and sustain ordered patterns out of randomness and chaos? Lastly we will be looking at the process of evolution as a powerful and relentless force that shapes complex adaptive systems on the macro scale and we will be taking it apart to get a solid grasp of its basic functioning. This book requires no prior specific knowledge of mathematics or science, as it is designed as an introduction presenting concepts in a nonmathematical and intuitive form that should be accessible to anyone with an interest in the subject.

    • Publish Data: 3-24-2017

    • Length: 62 pages

    • Format: PDF

  • The information revolution that began in the mid-twentieth century is entering a new stage of development; the confluence of major trends in cloud computing, new data sources, advances in algorithms and the rise of the internet of things are assuring in profound changes that take us into the ear of big data.

    The first wave of the information revolution based around the personal computer and the world wide web has created a torrent of new data sources from web blogs, internet search histories, large-scale e-commerce practices, retail transactions, RFID tags, GPS, sensor networks, social networks and mobile computing have all worked to create what we now call big data.

    But this mass of data would be no use without computing capacities to process it. Throughout human history, computing power was a scarce resource. However, with the recent advent of global scale cloud computing, high-end computing is now available to organizations of almost all size at low cost and on-demand.

    The third major element that has fallen into place is a powerful new set of algorithmic approaches. Breakthroughs in machine learning and deep learning in particular now provide the software systems to process these ever more complex data sets; algorithms that learn from data, that can deal with millions of parameters, that can coordinate vast digital platforms, optimizing logistics networks, automating financial trades, predicting maintenance on electrical grids.

    New Instrument With these new tools, we are now peering into massive unstructured data sets using ever more sophisticated algorithmic frameworks to see what we could never before see. Many compare this to building a new kind of microscope or telescope. But whereas with the microscope we revealed the microscopic mysteries of life and with the telescope the stars and galaxies, this tool lets us see the complex systems all around us.

    Data is opening up our ability to perceive things around us that were previously invisible; our evolved social, economic and technological systems that have become so complex we can no longer see them are being revealed to us in new ways. The implications of this are huge; just as the telescope changed our understanding of our place in the universe, complex analytics is changing our understanding of the world around us, the systems we form part of and this opens the door to a shift in the nature of how we make decisions and management is conducted.

    More and more governments, business sectors, and institutions begin to realize data is becoming the most valuable asset and its analysis is becoming core to competitiveness. Today data is becoming a new universal language, mastering it can win sports matches, can make movies a success, can win elections, can build smart cities, can make the right trade at the right time, it may even win wars.

    This course explores the world of complex data analytics: information systems that are able to analyze big data and transform these restless streams of data into insight, decisions, and action. Complex analytics focuses on how we extract the data from a complex system - such as a financial market, a transport network or a social network - and process that into meaningful patterns and actionable insights.

    Big Data After starting the course with an overview to the subject we will look at the emergence of big data and the expanding universe of dark data; we talk about the ongoing process of datafication, the quantification of more and more aspects of our lives and the many issues that it brings with respect to privacy.

    Advanced Algorithms In the second section, we will talk about the rise of algorithms as they are coming to effect ever more spheres of our world. We will introduce you to the workings of machine learning systems and the different approaches used, we go more in-depth on neural networks and deep learning before assessing the limitations of algorithms.

    Smart Systems The third section is dedicated to smart systems, as the convergence of machine learning with the internet of things is beginning to populate our world with systems that exhibit adaptive and responsive behavior, which are autonomous and can interact with humans in a natural way. Here we look at cyber-physical systems, smart platforms, and autonomous systems before discussing security issues.

    Data-Driven Organizations The final section deals with the relationship between people and technology and the emergence of a new form of analytics and data-driven networked organization. We talk about the fundamental distinction between synthetic and analytical reasoning as a way of understanding the distinction between digital computation and human reasoning and as a means for interpreting the rapidly evolving relationship between the two.

    This is not a technical course where you will learn the details of data modeling or how to build machine learning systems. What it does provide is an overview of this very exciting and important new area that will be of relevance to almost all domains, researchers, engineers and designers, business and the general public alike.

    The course aims to be a comprehensive overview to complex analytics, it aims to be inclusive in scope. We try to provide an understanding of the context to these major technological developments; a conceptual understanding of the methods and approaches of big data modeling and analysis; an overview to the underlying technology and address the issues and consequences both positive and negative of such technological developments.

    • Publish Data: 23-01-2018

    • Length: 79 pages

    • Format: PDF

  • This book is an overview of the new area of complexity economics, the application of models from complexity theory to the domain of economic science. These are interesting times for economic science as with information technology and globalization a new form of networked economy is emerging. These current changes in the deep architecture to our economies go well beyond the scope of the industrial age paradigm and require a re-imagination of economic science in an age of complexity. General equilibrium models that were derived from classical physics got mathematized during the 20th century, these models give us a picture of the economy as composed of isolated, purely rational individuals, optimizing over a well-defined set of preferences out of which we get a macro level general equilibrium in a somewhat static and timeless economy. It was a paradigm that fitted well with industrial age mechanization. But today the limitations of general equilibrium theory are becoming more apparent as we build new models, models to individual agents that have bounded rationality, driven by a diversity of motives they are interconnected and interdependent. And it is out of these nonlinear interactions we get the emergence of economic institutions as network structures that are far-from-equilibrium, in an economy that is constantly changing from internal drivers as it develops over time through an evolutionary process.

    • Publish Data: 23-5-2017

    • Length: 43 pages

    • Format: PDF

  • It is often said that we live in an increasingly complex world, the pace of change, the degree of connectivity and the scale of operations are leading to rapidly escalating complexity in many domains. As our industrial age systems of organization are ending their lifecycle, globalization, and information technology are taking us into a much more complex world and enabling the emergence of new forms of networked organization. This transition is, in turn, driving a fundamental transformation in our theory and methods of management, one that goes beyond our traditional paradigm designed for dealing with relatively static, hierarchical organizations within relatively stable and predictable environments, to more complex networked organizations that are adapted to operating in a so-called VUCA world of volatility, uncertainty and rapid change driven by innovation.

    This book is a first of its kind bringing together some of the latest ideas from complexity theory and emerging approaches to the management of complex organizations. During the book, we will explore many of these new ideas including, network organizations, co-evolution, systems thinking, platform organizations, agile development, and the adaptive cycle to name just a few. The book is broken down into five main sections.

    Complexity & Management: We will start the book off with an overview of complexity and management, talking briefly about what we mean by the practice of management before going on to take an introduction to the basic concepts from complexity theory that we will be using throughout the rest of the book such as self-organization, networks, evolution, and systems. We then combine our new understanding of both to take an overview of how complexity theory is being applied to management.

    Systems Thinking: The second section is dedicated to systems thinking. The paradigm of systems thinking is at the heart of managing complexity as it helps us to see the whole and not simply the parts, a key requirement for understanding and managing these highly interconnected and interdependent systems. We firstly give an overview of systems thinking, we talk about the key concept of emergence before going on to explore the system dynamics modeling framework that helps us to understand the nonlinear feedback loops that drive change in complex organizations.

    Networked Organizations: In the next section we explore this new type of networked organization that we see emerging in post-industrial economies, new types of platform organizations that go beyond the industrial age model, enabled by information technology, they are networked in structure, collaborative by nature, open and self-organizing. In this section, we explore the DNA of these new forms of organization contrasting them with our more traditional form to understand their key attributes.

    Complex Project Management: In the fourth section of the book we will see how a very different approach to our traditional linear project management methods are needed when projects reach a high degree of complexity. We will look at so-called “wicked problems” a new breed of very complex challenges such as climate change, inequality or cyber security, all of which share the key characteristics of complexity. We will look at the methods presented by complexity management designed for managing these large projects, under volatile and uncertain conditions.

    The VUCA Framework: The net result of the complex environment that we explored in the previous sections is what the business world calls VUCA. VUCA is an acronym for volatility, uncertainty, complexity, and ambiguity; it captures the most salient challenges faced by leaders operating in complex environments. In this last section, we introduce the concept of VUCA and give an overview of strategies for navigating these challenging environments, through the development of adaptive and agile organizations.

    This book is designed as an introduction to the subject, concepts are explored in non-technical terms, and it will require only a basic background knowledge of management and economics. The book should be relevant for those engaged in all areas of management both public and private.

    • Publish Data: 5-23-2017

    • Length: 43 pages

    • Format: PDF

  • This book is designed to be an overview to the core concepts within complexity theory, presented in an intuitive form that should be accessible to anyone with an interest in the subject. Complexity theory is an exciting new area that is offering us a fresh perspective on many important issues, such as understanding our financial system, ecosystems, and large social organizations. The aim of this book is to bring the often abstract and sophisticated concepts of this subject down to earth and understandable in an intuitive form. After starting with an overview to complex systems science and its context, we will focus on five of the core concepts within complexity theory.

    Systems Theory: We will start with three sections on systems theory and systems thinking, thus introducing you to the bigger picture of why complex systems is seen as a new paradigm in science; what exactly this new paradigm is; why we need it, and lastly how it differs from our traditional methods of scientific inquiry.

    Nonlinear Systems: The terms “nonlinear science” and “complex systems” are often used interchangeably showing how essential the concept of non-linearity is to this subject. In this chapter, we draw the distinction between linear and nonlinear systems and see why it matters. The second part of this section covers the subject of chaos theory and the dynamics of nonlinear systems.

    Network Theory: Networks in general have arisen in almost all fields of inquiry in the past few decades, making it one of the most active and exciting areas of scientific study. In the two sections on network theory, we will explore many different types of networks, their properties and examples in the real world, from social networks to logistics networks. This section will conclude by looking at graph theory, the mathematical foundations that lie behind networks.

    Complex Adaptive Systems: CAS is increasingly being used to model a wide variety of systems, from electrical power grids to economies and cultures, as it represents a powerful new way of seeing the world. This section will also cover CAS’s close relative cybernetics and the basic concepts of adaptation and evolution. Self-organization is another one of the foundational concepts within complex systems that is proving particularly relevant to the world of the 21st century as we see collaborative self- organizing groups, such as Wikipedia and the Linux foundation, emerge. But self- organization is more than just a social phenomenon. In these two sections, we will explore how it is in fact ubiquitous in our world from the formation of fish schools to magnetization and traffic jams.

    The last five sections to the book are dedicated to the application of complexity theory to various domains of science. Complexity theory has been applied to many areas from business management and anthropology to engineering and the design of healthcare systems, with its number of applications continuing to grow yearly. Here, we will just give a quick outline to four different areas that it has been successfully applied to including the social sciences, economics, engineering, and earth science.

    Once you have purchased the item you will receive an email with a link to the book for you to download immediately.
  • Critical thinking is the capacity to distinguish between effective and ineffective processes of inference and requires the formation of beliefs based upon sound reasoning. The word critical derives from the Greek word critic and implies a critique; it identifies the intellectual capacity and the means “of judging” and of being “able to discern.” Much information and knowledge in everyday life can not be proven to be decisively correct or incorrect; critical reasoning is the capacity for objective analysis and evaluation in order to form a judgment on the process through which knowledge or information was generated. The literature on critical thinking has roots in two primary academic disciplines: philosophy and psychology.

    Critical thinking is a form of metacognition, it is self-directed and self-monitored; it is about developing the conceptual tools to be able to think for oneself. Critical thinking is about trying to understand our processes of reasoning and developing standards for improving them, it is a way of thinking about any subject in which the person improves the quality of their thinking by assessing, analyzing, deconstructing and reconstructing it to try and improve its clarity, accuracy, relevance, depth, breadth and logical consistency. This book is broken down into four main sections, where we will look at the major themes of cognition, logic, reasoning and argumentation. The first section looks at human cognition to understand the basic biological and evolutionary constraints placed on us when it comes to effective reasoning. Here we will talk about how the brain works, look at some of the central insights from cognitive science and talk about some of the many limitations and flaws prevalent within human cognition.

    In the second section, we will look at logic. Although critical thinking is much more than just logic, reason and logic lay at the heart of constructive thinking. Here we talk about the various different forms of logic, inductive, deductive, formal, informal etc. In the third section, we will start our discussion on the theme of reasoning, the process through which we take in information and use some logic to infer conclusions. We will take the process apart to understand the elements of effective reasoning. Here we will talk about the standards of reasoning, elements of reasoning, creative thinking and more. In the final section, we discuss the important topic of argumentation, how people with diverse, or even divergent opinions, come to resolve their differences in order to develop new knowledge, make decisions, or reach consensus on some issue. This book is based upon the work of the Foundation for Critical Thinking and is designed to provide an overview to critical thinking that should be accessible to all.

    • Publish Data: 21-7-2017

    • Length: 55 pages

    • Format: PDF

  • By purchasing this item you will get access to download all of our videos and transcription files for all courses. A total of some 300 videos will be available for you to download and reuse in your own project. Likewise, you will get individual PDF transcription files for all video lessons. This will be ideal for educators and organizations wishing to reuse our content in courses or for presentations. Once you have purchased the item you will receive an email with a link for you to start downloading immediately, you will be able to download a whole course with one click or as individual files for each video and transcription.

  • Although the ideas of emergence have been of interest to many for millennia it has often been seen as something of a mystery, but with the development of complexity theory, we increasingly have the computational and conceptual tools to understand it in a structured, scientific fashion. During the book, we will be drawing upon different ideas in complexity and systems theory to build up a framework for understanding emergence in a coherent fashion. More specifically, we will explore emergence as a form of nonlinear pattern formation. Where synergies between elementary parts give rise to self-organization and the formation of a distinct pattern, that creates new, emergent levels of organization, that are driven by an evolutionary dynamic.

    After giving an overview of emergence theory, the book is designed around four main sections. In the first section, we start off by talking about patterns of correlation in general before going on to look at synergistic interactions that are the foundations to emergence. The next section is focused on pattern formation, the question of how the parts come to self- organize; to synchronize their states into forming a new level of organization. Here we will talk about the two primary different types of emergence that are often used categorizations; what are called strong and weak emergence.

    In the third section, we will look at the idea of integrative levels, how synergies give rise to pattern formation and the emergence of new levels of organization called integrative levels. We will talk about how these different levels come to have their own irreducible internal structure and processes that result in a complex dynamic between the micro and macro levels of organization. In the last section of the book, we will look at how emergence plays out over time within some process. We will talk about the edge of chaos hypothesis; how self-organizing, emergent systems never quite lock into place but instead evolve through a dynamic interplay between order and disorder, to create novel phenomena at new levels of complexity.

    This is an introductory book and is non-technical, however, it is important to note that the concept of emergence is highly abstract, to do it justice we will have to use high-level abstractions, as such students will need to feel comfortable with formal abstract models. The book should be accessible without need for any specific background in science and should be of relevance to many different domains, in particular for those in the areas of computer science, biology and ecology, philosophy, the cognitive sciences and anyone with an interest in better understanding this central concept with the complexity and systems theory framework.

    • Publish Data: 5-24-2017

    • Length: 40 pages

    • Format: PDF

  • Sale!
    Every time we buy a product in the supermarket, take a flight, recharge our phone or send an email we are forming part of what we call complex engineered systems. From supply chain networks to power grids and cities our everyday lives are embedded within and enabled by these complex networks of technology and services. This is a world in a state of rapid change, in the industrial age we build individual systems with the advent of information technology and globalization, a new world of integrated networked systems that cuts across specific domains is emerging, they bring a whole new paradigm to our technology infrastructure, challenge our engineering capacity, and understanding these complex systems is more important than ever. This book is an overview to the new area of research called complex engineered systems that applies models from complexity theory to analyzing the technology infrastructure that runs our high-tech global economy.

    The book is broken down into four major sections: We will start by applying systems theory to understand the fundamentals of our engineered environment, using it to give us a basic model of technology before we start adding complexity to it. We will go on to talk about information systems and sociotechnical systems. Next, we will be looking at nonlinearity and self-organization within our technology landscape, discussing how no one really designs these complex engineered systems but instead they are created out of local interactions, feedback loops and attractors that give rise to the emergence of global patterns of organization.

    We will go on to apply network analysis, discussing how IT and alternative technologies are working to create a new generation of highly integrated but also distributed systems, flipping our traditional centralized model on its head, as new technologies like 3D printing, solar cells, and mesh networks enable end-users to become producers. In the last section to the book we will be covering the topics of adaptation and system’s robustness as we look at the evolutionary process through which complex engineered systems are created, their vulnerabilities and capacity to adapt to a changing environment.

    Throughout the book we will be following a number of major trends that are having a powerful, transformative effect on our technology infrastructure. Including the rise of sustainability, globalization, the services revolution and, of course, the information revolution, that continues to be the most pervasive and radically disruptive force as it works to fundamentally re-architect our traditional industrial age systems, breaking down barriers between silos and networking them into integrated systems as disparate technologies become increasingly converged. We will see how all of these major themes are working to take us into a new world of complexity as we go further into the 21st century, and presenting engineers with a set of daunting technical challenges as they try to develop this next generation of integrated, smart and sustainable technology solutions.

    This book will not teach you about design or engineering, it is a book on technology analysis through the lens of complexity theory. Also, this course is not an introduction, you will be expected to be familiar with basic concepts within complexity theory, science, engineering, and technology. It is an overview to a broad subject so we will not be drilling down into technical engineering details. The book is non-mathematical but you will be exposed to the full complexity and abstract models that are required to make a proper analysis of these very complex systems of technology.

    • Publish Data: 6-24-2017

    • Length: 47 pages

    • Format: PDF

  • Sale!

    This book is an accompaniment to our game theory course which works as a gentle beginners guide to game theory and the dynamics of cooperation and competition. The ideas of competition and cooperation are of central interest to many in various areas of the social sciences and management. Likewise, a central question in the study of human evolution is why humans are so extraordinarily cooperative as compared with many other creatures. In most primate groups, competition is the norm, but humans form vast complex systems of cooperation. Humans live out their lives in societies and the outcomes to those social systems and our individual lives is largely a function of the nature of our interaction with others. A central question of interest across the social sciences, economics, and management is this question of how people interact with each other and the structures of cooperation and conflict that emerge out of these. Of course, social interaction is a very complex phenomenon, we see people form friendships, trading partners, romantic partnerships, business compete in markets, countries go to war, the list of types of interaction between actors is almost endless. For thousands of years, we have searched for the answers to why humans cooperate or enter into conflict by looking at the nature of the individuals themselves. But there is another way of posing this question, where we look at the structure of the system wherein agents interact, and ask how does the innate structure of that system create the emergent outcomes.

    The study of these systems is called game theory. Game theory is the formal study of situations of interdependence between adaptive agents and the dynamics of cooperation and competition that emerge out of this. These agents may be individual people, groups, social organizations, but they may also be biological creatures, they may be technologies. The concepts of game theory provide a language to formulate, structure, analyze, and understand strategic interactions between agents of all kind. Since its advent during the mid 20th-century game theory has become a mainstream tool for researchers in many areas most notably, economics, management studies, psychology, political science, anthropology, computer science and biology. However, the limitations of classical game theory that developed during the mid 20th century are today well known. Thus, in this book, we will introduce you to the basics of classical game theory while making explicit the limitations of such models. We will build upon this basic understanding by then introducing you to new developments within the field such as evolutionary game theory and network game theory that try to expand this core framework.

    In the first section, we will take an overview of game theory, we will introduce you to the models for representing games; the different elements involved in a game and the various factors that affect the nature and structure of a game being played. In the second section, we look at non-cooperative games. Here you will be introduced to the classical tools of game theory used for studying competitive strategic interaction based around the idea of Nash equilibrium. We will illustrate the dynamics of such interactions and various formal rules for solving non-cooperative games. In the third section, we turn our attention to the theme of cooperation. We start out with a general discourse on the nature of social cooperation before going on to explore these ideas within a number of popular models, such as the social dilemma, tragedy of the commons and public goods games; finally talking about ways for solving social dilemmas through enabling cooperative structures. The last section of the book deals with how games play out over time as we look at evolutionary game theory. Here we talk about how game theory has been generalized to whole populations of agents interacting over time through an evolutionary process, to create a constantly changing dynamic as structures of cooperation rise and fall. Finally, in this section we will talk about the new area of network game theory, that helps to model how games take place within some context that can be understood as a network of interdependencies.

    This book is a gentle introduction to game theory and it should be accessible to all, it can be read as a standalone piece or used as an accompaniment to the course. Unlike a more traditional book in game theory, the aim of this book will not be on the formalities of classical game theory and solving for Nash equilibrium, but instead using this modeling framework as a tool for reasoning about the real world dynamics of cooperation and competition.

    • Publish Data: 6-24-2017

    • Length: 62 pages

    • Format: PDF

  • This is an introductory book where we present topics in a non-mathematical and intuitive form that should not require any specific prior knowledge of science as the book is designed to be accessible to anyone with an interest in the subject. During the book, we will explore all the major topics in this area. The study of network theory is a highly interdisciplinary field, which has emerged as a major topic of interest in various disciplines ranging from physics and mathematics, to biology and computer science to almost all areas of social science. From the metabolic networks that fuel the cells in our body, to the social networks that shape our lives, networks are everywhere, we see them in the rise of the Internet, the flow of global air traffic and in the spread of financial crises, learning to model and design these networks is central to 21st Century science and engineering.

    Networks Overview: In this first section of the book, we are going to give an overview of network theory that will also work as an overview of the structure of the book and the content we will be covering. We talk about what we called the network paradigm that is the whole new perspective that network theory offers when we look at the world through the lenses of connectivity.

    Graph Theory: In this second section, we lay down the basics of our language for talking about graphs by giving an introduction to graph theory, we talk about a node’s degree of connectivity and different metrics for analyzing a node’s degree of centrality and significance within a network.

    Network Structure: In the third section, we explore the overall topology to a network by talking about connectivity, which is how connected the whole network is, diameter, density, and clustering all key factors in defining the overall structure to a network.

    Types Of Networks: In this section, we will be looking at different models to networks by starting out with a randomly generated network we will see how most networks are in fact not random but have some distinct structure, here we will be talking about a number of different models such as centralized scale-free networks and the small world phenomena.

    Network Diffusion: In the last section of the book, we touch upon how networks change over time, in particular looking at the different parameter effecting the generation of a network, how something spreads or fails to spread across it and finally wrap-up by talking about network robustness and resilience.

    By the end of taking this book, I hope that you will have a solid grasp of the formal language of network theory, the standardized language used to model networks within a wide variety of domains. You should also have a solid conceptual background required to approach a more advanced book in the mathematical analysis of networks. Being an introductory book, it has been designed to be accessible to a broad group of people but will be of particular relevance to those in engineering, the natural and social sciences, mathematics or IT.

    • Publish Data: 3-24-2017

    • Length: 54 pages

    • Format: PDF

  • This book is a voyage into the extraordinary world of nonlinear systems and their dynamics. The primary focus of the book is to provide you with a coherent understanding of the origins and product of nonlinearity and chaos. The book is designed as an intuitive and non-mathematical introduction, it explores a world of both extraordinary chaos where some small event like a butterfly flapping its wings can be amplified into a tornado, but also a world of extraordinary order in the form of fractals, self-similar structures that repeat themselves at various scales, one of nature’s most ingenious tools for building itself. Like quantum physics the world of nonlinearity is inherently counter-intuitive, it’s a world where our basic assumptions start to break down and we get extraordinary results, once the domain of obscure mathematics, the concepts from nonlinear systems theory are increasingly proving relevant to the world of the 21st century.

    This book covers all the key concepts from this domain, starting by looking at the origins of how and why we get nonlinear phenomena, we go on to talk about exponential growth, power laws, chaos theory, the butterfly effect, bifurcation theory, fractals and much more. The book requires no prior specific knowledge of mathematics or science; it is designed as an introduction presenting concepts in a nonmathematical and intuitive form that should be accessible to anyone with an interest in the subject.

    Nonlinear Systems Overview: In this section we start the book by giving an overview to the model of a system that will form the foundations for future discussion, we talk about linear systems theory based upon what is called the superposition principles of additivity and homogeneity. We will go on to talk about why and how linear systems theory breaks down as soon as we have some set of relations within a system that are non-additive, we also look at how feedback loops over time work to defy the homogeneity principle with the net result being nonlinear behavior.

    Feedback Loops & Relations: In this section, we introduce the key sources of nonlinearity as the type of relations between components within a system where these relations add or subtract some value to the overall system. We will talk about synergies and interference that make the system either greater or less than the simple sum of its components. We will then cover the second source of nonlinearity, what are call feedback loops that allow for both exponential growth and decay.

    Exponentials, Power laws: In this section we will discuss the dynamics of exponentials and their counterparts power laws that represent an exponential or power relation between two entities, we talk about long tail distributions, sometimes called the fat tail, so called because it results in there being an extraordinary large amount of small occurrences to an event and a very few very large occurrences with there being no real average or normal to the distribution.

    Systems dynamics & Chaos: For many centuries the idea prevailed that if a system was governed by simple rules that were deterministic then with sufficient information and computation power we would be able to fully describe and predict its future trajectory, the revolution of chaos theory in the latter half of the 20th century put an end to this assumption showing how simple rules could, in fact, lead to complex behavior. In this section, we will describe how this is possible when we have the phenomena of what is called sensitivity to initial conditions.

    Fractals: We will have encountered many extraordinary phenomena by this stage in the book but fractals may top them all, self-similar geometric forms that repeat themselves on various scales, they can both contain infinite detail, as we zoom in and the very counter-intuitive phenomena of infinite length within a finite form with this all being the product of very simple iterative rules.

    • Publish Data: 3-24-2017

    • Length: 33 pages

    • Format: PDF

  • We live in times of profound political transformation, as Industrial Age social organization gives way to the emergence of a new form of networks society, political organization, in turn, is entering into a new period of disruption and rapid evolution. The modern construct of liberal republicanism, representative democracy, and the nation state framework are being challenged by the rise of globalization and the pervasive proliferation of information networks on all levels. These changes are creating ever larger spaces outside of traditional political organization, both within societies and on the global level, while at the same time new social and political networked organizations are being born online and increasingly having an effect on all areas of social organization.

    The ongoing emergence of the network society rewrites the rules of political organization rendering old categorizations and concepts that defined political systems for the past centuries less relevant. In this context new insight, models and vocabulary are desperately needed to understand the workings of political systems in an age of information, globalization, and complexity. This book explores how complexity theory can be applied to political science in order to develop such a vocabulary. It draws upon the central concepts and models from complexity theory, such as systems thinking, self-organization, nonlinear systems, network theory and adaptive capacity, applying them to interpreting complex political systems.

    The book is broken down into five main sections. We start the book off with a broad discussion on sociocultural systems as the foundations to political organization. We go on to lay down the basics of political theory and identify the central elements of political systems; the different types of political systems that we encounter and the evolution of sociopolitical complexity. In the second section, we will be looking at the concepts of emergence and self-organization as applied to political systems. We firstly discuss the dynamics of self-organization and pattern formation, before looking at emergence as it applies to the formation of new political movements through only local peer-to-peer interactions and interdependencies.

    In the next section, we introduce concepts and models from nonlinear systems theory and apply them to understanding the dynamics of political organization. We talk about new ideas from political field theory, non-equilibrium dynamics, the significance of power law distributions, feedback dynamics, and regime shifts. The fourth section deals with sociopolitical networks, firstly illustrating how the network approach to political science adopts a relational paradigm and how this differs from more traditional statistical methods of political science. Here we introduce the main models for interpreting social networks and analyzing their structure, dynamics, and processes of diffusion. The final section deals with the evolution of sociopolitical systems and their adaptive capacity. Here we will talk about the ideas of political resilience, the primary factors influencing adaptive capacity and evolutionary potential; asking how and why do sociopolitical systems succeed or fail in navigating major processes of change

    This book should be accessible to anyone with a general knowledge of the social sciences. No prior knowledge of complexity theory is required as models will be explained as we encounter them, likewise, basic ideas within political theory will be introduced in the first section. The book will be of particular relevance to those in the domain of political science but will also be of general relevance to anyone with an interest in understanding the macro-level contemporary changes taking place within political organization.

    • Publish Data: 6-8-2017

    • Length: 126 pages

    • Format: PDF

  • This book is an accessible introduction to the application of complexity theory to the social sciences. The book will be primarily focused on the domain of sociology, but we will touch upon elements of psychology, anthropology, political science, and economics. The aim of the book is to introduce you to the variety of models from complex systems and illustrate how they apply to these different domains.

    This book is a first of its kind and somewhat experimental in nature, where we will be drawing upon research from many different areas and using complexity theory to contextualize it into a coherent paradigm, giving us a fresh perspective with which to interpret some of the core questions within the social sciences. The content is organized into four underlying parts, in each part, we will apply one of the major modeling frameworks from complexity theory to interpreting social phenomena. We will firstly give an overview of this area of social complexity before starting our first part on systems theory. As we lay down a basic model of a social system, we will go on to use this model in helping us understand, social structure and institutions. Next, we will take an overview of nonlinear social science, as we discuss the process of self-organization, feedback loops, chaos theory and self- organized criticality. The third part of the book is dedicated to social network analysis, we will cover the main topics in this new area as we talk about the basics of social graphs, clustering, network structure and the process of diffusion. Finally, we will be looking through the lens of complex adaptive systems theory, exploring the model of a fitness landscape, talking about adaptive capacity, social resilience and the process of evolution.

    This book is designed to be accessible to a broad audience but will be of particular interest to researchers and students within the various social sciences wishing to apply complexity theory within their own work. Some background in social theory and complexity theory would be an advantage but not a prerequisite.

  • This book is an introduction to the application of complexity theory to the design and engineering of systems within the context of the 21st century. From the bigger picture of why we should care to key architectural considerations, it brings together many new ideas in systems design to present an integrated paradigm and set of principles to the design of complex systems. In the first section of the book we will explore some of the major themes that are shaping the design and engineering of systems in the 21st century, such as the rise of sustainability, information technology, the revolution in services and economic globalization, these will all provide a backdrop and recurring set of themes that will be woven into our discussion. This section will also give you an overview to complexity theory and the basic concepts that we will be using throughout the book, such as the model of a system, a framework for understanding complexity and a definition for complex systems. The last section of this model will give an overview to complex systems design providing you with a clear and concise description of what a complex engineered system is and how this new paradigm in design differs from our traditional approach.

    Next we introduce you to the key concepts within this domain, we will talk about services and product-service systems; designing synergistic relations in order to integrate diverse components. In this section we will explore one of the key takeaways from this entire book, the idea of abstraction as a powerful tool for solving complexity. In the third module to the book we discuss the primary principles to the designing of complex systems. Firstly networks, with these highly interconnected systems networks are their true geometry, understanding them and being able to see the systems we are designing as networks is one of our key principles we will talk about. Secondly, we will look at adaptive systems and how I.T. is enabling the next generation of technologies that are responsive, adaptive and dynamic, allowing for self-organization and a new form of bottom-up, emergent design. Lastly, in this sect, on we will also cover the key mechanisms of evolution and how it affects the life-cycle to the systems we are designing.

    With systems architecture we begin to change gears to talk about the more practical mechanics of how to design complex systems based around a new systems architecture paradigm that has arisen within I.T. over the past few decades, what is called Service Orientated Architecture. In this section we will discuss platform technologies and their internal workings, modular systems design and Event Driven Architecture which is particularly well suited to the dynamic nature of the systems we are developing. Lastly, we present a series of lectures on the design method and process best suited to complex systems design. In this section you will be introduced to design thinking that represents a repeatable set of stages in the design process for solving complex problems.

  • This book is an introduction to the area of systems ecology, the application of systems theory to the study of ecosystems. Systems ecology uses mathematical modeling and computation to try and understand the networks of interactions between biotic and abiotic elements that give rise to the complex system of an ecology on all scales, from modeling the flow of energy within a microbial ecosystem to trying to understand the nonlinear dynamics of earth’s entire biosphere. Taking an integrative and interdisciplinary approach it bridges many areas from physics and biology to the social sciences. Whereas traditional ecology has studied ecosystems with little reference to human society, systems ecology breaks down this barrier to include industrial ecologies as an integral part of earth’s systems in the era of the Anthropocene, when understanding the complex interaction between society and ecology is central to gaining traction on major contemporary environmental challenges.

    This book is focused on providing you with the core principles and concepts in system ecology and is broken down into three main sections. In the first section, we will be laying down the basics of systems theory in ecology as we talk about, energetics, thermodynamics, emergent integrative levels and ecosystem dynamics. Next, we will be looking at nonlinear systems theory within ecology, as we talk about feedback loops, how ecosystems self-organize, the nonlinear dynamics of abrupt ecosystem regime shifts, stability landscapes, and ecological networks. The final section will be dedicated to socio-ecological systems, we will first, talk about the new geological era of the Anthropocene and the rapidly changing relationship between ecosystem and society. We will look at the area of industrial ecology, models for interpreting socio-ecological systems, their adaptive capacity, and resilience, finally, we will take an overview to the new area of sustainability science.

    This book is a non-technical introduction, some background in the natural sciences or systems theory would be of advantage but not necessary as the book should be accessible to anyone with an interest in the subject.

    • Publish Data: 8-7-2017

    • Length: 66 pages

    • Format: PDF

  • This book is an overview of the foundational concepts within systems theory, in particular, it is focused on conveying what we call the systems paradigm that is the basic overarching principles that are common to all areas of systems thinking and theory. Systems thinking has been defined as an approach that attempts to balance holistic and analytical reasoning. In systems theory, it is argued that the only way to fully understand something is to understand the parts in relation to the whole. Systems thinking concerns an understanding of a system by examining the linkages and interactions between the elements that compose the entire system. By taking the overall system as well as its parts into account this paradigm offers us fresh insight that is not accessible through the more traditional reductionist approach.

    This book explores the foundations of systems theory, the process of reasoning call synthesis and its counterpart analysis. The central theme throughout the book will be on understanding these two basic processes of reasoning and how they relate to each other, thus enabling the student to become more effective in their reasoning and modeling. In the first section of the book we start off by taking an overview to the systems paradigm, we will talk about how systems thinking helps us to gain an awareness of our processes of reasoning, their assumptions, strengths, and limitations. We will try to understand what paradigms in general are, before going on to talk about theories and the development of formal models.

    • Publish Data: 23-5-2017

    • Length: 43 pages

    • Format: PDF

  • This book is an overview of the area of systems thinking and theory that is designed to be accessible to a broad group of people. The book is focused on two primary achievements; firstly providing you with the key concepts that will enable you to see the world in a whole new way from the systems perspective, what we call systems thinking. Secondly, the aim is to provide you with the standardized language of systems theory through which you will be able to describe and model systems of all kind in a more coherent fashion whilst also being able to effectively communicate this to others. This book requires no prior specific knowledge of mathematical modeling or science, as we will be starting with the very basic model of a system and then building upon this to create more sophisticated representations. The book is broken down into four main areas. Firstly we will start the course with an overview of systems thinking, making a clear distinction between our traditional methods of analytical reasoning and the alternative method of synthesis that forms the foundations of systems thinking. Next, we will delve into systems theory to start building our model of a system, clearly defining what exactly a system is and is not. During the rest of this section, we will build upon this model by adding the concepts of efficiency, functionality and talking about energy and entropy. In the third section of the course, we will develop our model into a more powerful framework by adding the concept of the system’s environment, discussing systems boundaries, synergistic interactions and the emergence of hierarchical structure out of these synergies. In the last section, we will look at different models for capturing how systems change over time what is called system dynamics, here we will explore the ideas of feedback loops, causal loop diagrams and the phenomena of homeostasis. Finally, we wrap up the course with a discussion of systems science, looking at how and why it is of relevance to us. By the end of this book, you should have gained a whole new perspective on the world call systems thinking and will have gained an understanding of the formal language of systems theory that can be used within a wide variety of applications from engineering to business management to IT to many areas of science.
  • Purchasing this item will give you access to our graphics packs. The pack contains the graphics from the video lessons for most of the courses and videos. Images are in a JPEG format with a size of 1920 × 1080px. You will be free to reuse these graphics in your presentations or for other educational purposes. Once you have purchased the item you will receive a link to download the zip files. In the pack you will find the graphics for the following courses: Complexity Management Complexity Theory Critical Thinking Economics Emergence Theory Game Theory Network Theory Nonlinear Systems Social Complexity Systems Design Systems Theory Systems Thinking