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Understanding Complexity

Understanding Complexity

Professor Scott E. Page, Ph.D.
University of Michigan

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Understanding Complexity

Course No. 5181
Professor Scott E. Page, Ph.D.
University of Michigan
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Course No. 5181
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Course Overview

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.

These include

  • tipping points, the sociological term used to describe moments when unique or rare phenomena become more commonplace;
  • the wisdom of crowds, the argument that certain types of groups harness information and make decisions in more effective ways than individuals;
  • six degrees of separation, the idea that it takes no more than six steps to find some form of connection between two random individuals; and
  • emergence, the idea that new properties, processes, and structures can emerge unexpectedly from complex systems.

Interest in these intriguing concepts is widespread because of the utility of this field. Complexity science can shed light on why businesses or economies succeed and fail, how epidemics spread and can be stopped, and what causes ecological systems to rebalance themselves after a disaster.

In fact, complexity science is a discipline that may well hold the key to unlocking the secrets of some of the most important forces on Earth. But it's also a science that remains largely unknown, even among well-educated people.

Now you can discover and grasp the fundamentals and applications of this amazing field with Understanding Complexity. Professor Scott E. Page-one of the field's most highly regarded teachers, researchers, and real-world practitioners-introduces you to this vibrant and still evolving discipline. In 12 lucid lectures, you learn how complexity science helps us understand the nature and behavior of systems formed of financial markets, corporations, native cultures, governments, and more.

What Makes a System Complex?

What defines a system as complex, as opposed to being merely

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12 lectures
 |  30 minutes each
Year Released: 2009
  • 1
    Complexity—What Is It? Why Does It Matter?
    Learn what the experts mean when they talk about "complex" systems. Discover why these networks of diverse, connected, and adaptive entities acting in interdependent ways are so powerful, and why understanding them is crucial to so many disciplines. x
  • 2
    Simple, Rugged, and Dancing Landscapes
    Using the concept of a mountainous landscape as both metaphor and mathematical object, you begin to grasp the ways in which concepts like "rugged" or "dancing" landscapes—where adaptation and learning are vital for survival—can be visualized even by nonmathematicians. x
  • 3
    The Interesting In-Between
    You develop your understanding of complexity's key components of interdependence, connectedness, diversity, and adaptation/learning. And you learn—by figuratively dialing the strength of each of these components up or down—why the proper balance between them is essential if a system is to be complex. x
  • 4
    Why Different Is More
    Variance and diversity have very different meanings in the world of complexity theory. Grasping that difference puts you on the way to understanding how complex systems achieve diversity and why diversity enables them to be both innovative and robust, maintaining functionality even when the system is disturbed. x
  • 5
    Explore Exploit—The Fundamental Trade-Off
    Actors in complex systems face a constant tradeoff. Do they exploit the knowledge already learned in past explorations to achieve a solution? Or do they continue to explore, seeking an even better solution? Learn the pros and cons of each, and how the best balance can be achieved. x
  • 6
    Emergence I—Why More Is Different
    One of the most fascinating ideas in complexity theory is that of emergence, the spontaneous creation of order and functionality from the bottom up, with no "central planner" putting them into place. You gain an appreciation of the two kinds of emergence and why each is a source of wonder. x
  • 7
    Emergence II—Network Structure and Function
    Continuing the discussion of emergence, you see how emergence applies to networks and why network theory has become such an active discipline. And you understand how modern complexity theory adds to the study of networks the previously ignored element of space. x
  • 8
    Agent-Based Modeling—The New Tool
    Agent-based modeling—in which computers model complex systems from interdependent agents—may be complexity theory's most promising tool. Its full potential hasn't yet been realized, but this lecture offers a taste of what it can already achieve in disciplines as disparate as fire prevention and disease transmission. x
  • 9
    Feedbacks—Beehives, QWERTY, the Big Sort
    Drill even deeper into the implications of interdependent agents as you focus on the idea of feedbacks—both the positive ones, in which "more creates more," and the negative ones, in which "more creates less." x
  • 10
    The Sand Pile—Self-Organized Criticality
    Complex systems often create large events. Using the example of how a single unscreened passenger in Atlanta delayed flights and passengers across the nation, you are introduced to one of the key concepts that explain how complex systems can be so powerful. x
  • 11
    Complexity versus Uncertainty
    There is a vast difference between thinking of events as "random" and recognizing them as the output of a complex system. Explore three conventional explanations of randomness before turning to a fourth—the interdependent rules-based analysis offered by complexity theory. x
  • 12
    Harnessing Complexity
    Although complex systems can't be controlled, we may well be able, with proper respect, to harness them. Learn why conventional decision theory doesn't work in complex environments and what a proper use of complexity theory might promise us instead. x

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Your professor

Scott E. Page

About Your Professor

Scott E. Page, Ph.D.
University of Michigan
Dr. Scott E. Page is Leonid Hurwicz Collegiate Professor of Political Science, Complex Systems, and Economics at the University of Michigan, where he has taught since 2000. The holder of a master's degree in Mathematics from the University of Wisconsin and a Ph.D. in Managerial Economics and Decision Sciences from Northwestern University, Professor Page has also been Professor of Economics at the California Institute of...
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Rated 4.4 out of 5 by 97 reviewers.
Rated 5 out of 5 by important subject Fascinating subject and lecture material! This one really held my attention. Of all the great courses watched so far, this one is tops on the repeat list as I think I will get that much more from a second viewing. Yes it is dense, but it allows for a much more realistic analyses of complex anything. Highly recommended and would really like more courses from this professor on this stuff! March 20, 2016
Rated 5 out of 5 by Fast paced amalgam of several analytic disciplines I describe this course as a very rapid overview of multiple overlapping disciplines. As a minimum this course covers portions of applied statistics, industrial engineering, and operations research as its primary subject. If you include the illustrative examples, then the multi-disciplinary nature increases much more. If these primary subjects hold no interest for you and/or are beyond your ken, then I can see how you might not be too enthralled with this course. On the other hand, if you have a background in those primary subjects or are looking to gain insight into such analytics, then you will very much enjoy this course. I have a background in these primary topics and I gained much. I look to apply some of the concepts that Dr. Page imparts in my own applications. Dr. Page is clearly in command of the materiel and is an exceptionally able lecturer; however, I do agree with the other reviews lamenting the lack of graphics. Despite Dr. Page’s tremendous ability to create word pictures, nothing depicts abstract concepts like an actual picture. It is in this regard that having a background in the primary subjects really comes into play. If you don’t have a background in topics akin to operations research, then you will likely have a hard time “seeing” Dr. Page’s oral descriptions. If the Great Courses releases a 2nd edition of this course, that deficiency should be remedied. January 28, 2016
Rated 5 out of 5 by A good introduction to Complexity... I am not quite through this series, but I am enjoying it a lot. I like the speed and energy of it, though I understand the comments of others that it's going a bit fast. I am probably relatively well-read on the subject, but have done no other course work. So, while I'm not new to the material, I have enjoyed and learned from the lectures. In fact, I'm interlacing these videos with another course I'm watching, and the other course seems way too slow and repetitive in comparison. Dr. Page's course is shorter, but much more meaty, and I have tended to think of "rewarding myself" when I watch these after suffering through the other. My only problem with the lectures is the verbal examples. I understand the point he's trying to make, but to me the examples sometimes don't really illustrate it. For example: Ep 10 - Thermostats don't work like that, Dr. Page! It was presented as if the AC and the heat alternate operation to maintain a constant temperature in a house. Careful... somebody might believe you. Actually, Dr. Page, there is usually a broad dead zone in such controls, so that the heat alone controls the temperature by alternating on and off states, and the resulting temperature curve is a saw-tooth pattern. If it's very cold outside, the on-states are longer and the off-states are shorter. On a warm day, the heat may not run at all, but the AC may not come on either unless manually switched. My Nests are currently in heat/cool mode with a pretty good dead zone where the system does nothing. I have had similar thoughts about some of the other examples, thinking that they really didn't quite apply. That doesn't wipe away the fact that I have enjoyed these lectures and gotten a lot out of them. November 6, 2015
Rated 4 out of 5 by I liked it, but with reservations When I finished the course, I felt that I had learned quite a bit. However, it could have been better. Professor Page is obviously very bright and well educated, and has an excellent understanding of the topic. However, his delivery speed is too rapid, and there is not enough time to consider what he is saying. I also found that so much terminology was presented so rapidly, that, especially after the first few lectures, I was quite confused. As one went on however, terms were re-presented and seemed to make more sense. When we finally reached the last 2 lessons, I felt I had a general understanding of what points he was trying to make. However, I also felt that the approach was broad brush, and there was not enough depth of information presented about any one area. It might have been better to have picked a specific area of complexity, and treated it more deeply. I also agree with some of the other reviewers that there were too few graphics, especially as compared with other courses, and this could have added to better understanding some of the concepts. September 27, 2015
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