Discover and grasp the fundamentals and applications of the amazing field of complexity science with Understanding Complexity. Professor Scott E. Page—one of the field's most highly regarded teachers and researchers—shows you how complexity science helps us understand the nature and behavior of financial markets, corporations, native cultures, governments, and other systems that play important roles in our increasingly complex world. By the conclusion of the course, you'll have attained a new lens through which to better view and make sense of your world.
Understanding Complexity
Discover and grasp the fundamentals and applications of the amazing field of complexity science with this course that helps you understand the nature and behavior of financial markets, corporations, native cultures, governments, and other systems.
Rated 5 out of
5
by
Annie Kate from
amazing material, presented clearly
Excellent, interesting, full of great examples and stories. It's fascinating to consider the prof's assumptions and guess where they come from and how the material would develop if he used different assumptions.
Date published: 2024-01-06
Rated 5 out of
5
by
FloridaPat from
Intellectually Stimulating
I enjoyed this course very much because the professor presented important concepts in a clear and accurate way. The examples used to illustrate the concepts were very good.
Date published: 2023-08-14
Rated 5 out of
5
by
RobinD from
Someone who sees all interconnections
This completely mental excitement! Finally, someone who sees and understands all the details, interconnections, moving parts, and human emotional decisions (versus logical decisions) of the world that I see, and giving it language and proof. All I can say is - where are other people that think and see this way - as they may be the only ones that could possibly solve today's problems - in the real-time speed it requires!
Date published: 2023-08-01
Rated 2 out of
5
by
Travisty from
Seems more like a subset of chaos theory
I was expecting more on the way of dealing with complexity and solving problems. For me this seems like it is more a heavy dose of introspection about a physics perspective on complexity or complicataed systems that may be interacting.
Date published: 2023-07-12
Rated 5 out of
5
by
Charles772 from
Very informative and interesting
I am enjoying the course about Understanding Complexity. The course follows an intellectual study of what complexity is (and is not) and how to identify components of complexity. Professor Page is interesting and keeps the pace going at a good rate.
This course is giving me the tools to identify situations in my life that are ever-changing and difficult to understand, and by understanding some of the components of the theory of complexity, I am able to categorize those things in my life and sort out the series of events in a more logical manner. This can help me organize the kitchen by removing complicated arrangements of items, or to understand the variables building an organization of multiple people into a team. You need to be curious about the subject and open to new ways of thinking about relationships between people, events, and things to get anything from this. For instance, if you have three team members who must meet for an activity and find that there are differing opinions of how to proceed, this could be the component of complexity identified herein as being "adaptive" as one member adapts their position to reach a compromise with another.
Date published: 2022-12-28
Rated 5 out of
5
by
e2718281828 from
Engrossing introduction to complexity
I really liked the course. Prof. Page is eloquent and extremely well-organized. I'm glad I ordered the accompanying transcript--the topic is pretty esoteric and more than a single pass is needed to get clarity on some aspects presented. Prof. Page's perspective seemed to be from a business perspective, whereas I am more interested in complexity's key role in ecology and climate change. I'm midway through Melanie Mitchell's book ("Complexity, A Guided Tour") at the same time and so far its emphasis seems very different. But this just proves the enormous reach of the subject's scope and impact. I highly recommend Prof. Page's course.
[Note to The Great Courses: I would really like to see a corresponding course focused on the sub-areas of emergence, addressed in passing during this course's overview, and discontinuous change phenomena--especially as these relate to social, ecological, and climate change. It could perhaps present case studies and methodologies at more length in a sample of specific areas. Experts in a sample of specific fields might collaborate on a series of such reviews. ]
Date published: 2022-10-08
Rated 4 out of
5
by
CurtCarpenter from
A Way of Seeing Complex Phenomena
This course will equip the student with an understanding and appreciation of the complexity theorist's way of thinking about complex systems, but I think to really appreciate the discipline you have to "do the math." Many of the insights here come from a study of mathematical/computer models. You can understand the insights and the theorist's way of thinking, but to really appreciate the material actually engaging the math
and models is essential. See this course as an introduction that you will want to follow up with more research and study.
Date published: 2022-08-20
Rated 5 out of
5
by
Multiverse Jim from
Very lucid and clear lectures
Professor Page made this topic easily understandable and clear with his wide ranging examples and metaphors of complexity to many diverse topics. A must hear for anyone interested in avoiding disasters due to what was thought before to be random cascading events.
Date published: 2022-02-02
Overview
About
Professor Scott E. Page received a B.A. in Mathematics from the University of Michigan and an M.A. in Mathematics from the University of Wisconsin–Madison. He then received his M.S. in Business and his Ph.D. in Managerial Economics and Decision Sciences from the Kellogg School of Management at Northwestern University. He completed his Ph.D. thesis under the guidance of Stan Reiter and Nobel laureate Roger Myerson. He has been a Professor of Economics at the California Institute of Technology and The University of Iowa and is currently Leonid Hurwicz Collegiate Professor of Complex Systems, Political Science, and Economics at the University of Michigan. At Michigan, he is also a Senior Research Scientist at the Institute for Social Research, a Senior Fellow in the Society of Fellows, and the Director of the Center for the Study of Complex Systems. In addition, Professor Page has been a long-time External Professor for the Santa Fe Institute, an interdisciplinary think tank devoted to the study of complexity. In 2011, he was elected to the American Academy of Arts and Sciences. Professor Page has won outstanding teaching assistant awards at the University of Wisconsin–Madison and Northwestern University, the Faculty Teaching Award at Caltech, and the Faculty Achievement Award for outstanding research, teaching, and service at the University of Michigan. Professor Page’s research interests span a wide range of disciplines. He has published more than 60 papers in a variety of fields, including economics, political science, computer science, physics, geography, public health, business, philosophy, and complexity. In addition, he has served on dissertation committees for students in more than 10 departments. In recent years, his core interest has been the various roles of diversity in complex adaptive systems, such as economies and ecosystems. He is the author of Diversity and Complexity; Complex Adaptive Systems: An Introduction to Computational Models of Social Life (with John H. Miller); and The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies . All three books were published by Princeton University Press. His most recent book, The Model Thinker: What You Need to Know to Make Data Work for You, provides a toolkit for people to be able to leverage data and information to their advantage. A popular speaker, Professor Page has appeared at the Aspen Ideas Festival and the World Economic Forum and before numerous corporate and nonprofit audiences around the world, including Google, Ford, Genentech, the International Monetary Fund, and the Association of American Medical Colleges. He has also recorded Understanding Complexity with The Great Courses. Professor Page lives with his wife and two sons in Ann Arbor, Michigan.
Trailer
01: 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.
34 min
02: 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.
31 min
03: 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.
32 min
04: 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.
32 min
05: 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.
33 min
06: 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.
32 min
07: 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."
33 min
08: 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.
31 min
09: 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."
32 min
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.
32 min
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.
33 min
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.
33 min
