About this course: Before the advent of quantum mechanics in the early 20th century, most scientists believed that it should be possible to predict the behavior of any object in the universe simply by understanding the behavior of its constituent parts. For instance, if one could write down the equations of motion for every atom in a system, it should be possible to solve those equations (with the aid of a sufficiently large computing device) and make accurate predictions about that system’s future. However, there are some systems that defy this notion. Consider a living cell, which consists mostly of carbon, hydrogen, and oxygen along with other trace elements. We can study these components individually without ever imagining how combining them in just the right way can lead to something as complex and wonderful as a living organism! Thus, we can consider life to be an emergent property of what is essentially an accumulation of constituent parts that are somehow organized in a very precise way. This course lets you explore the concept of emergence using examples from materials science, mathematics, biology, physics, and neuroscience to illustrate how ordinary components when brought together can collectively yield unexpected, surprising behaviors. Note: The fractal image (Sierpinkski Triangle) depicted on the course home page was generated by a software application called XaoS 3.4, which is distributed by the Free Software Foundation under a GNU General Public License. Upon completing this course, you will be able to: 1. Explain the difference in assumptions between an emergent versus reductive approach to science. 2. Explain why the reductivist approach is understood by many to be inadequate as a means of describing and predicting complex systems. 3. Describe how the length scale used to examine a phenomenon can contribute to how you analyze and understand it. 4. Explain why the search for general principles that explain emergent phenomena make them an active locus of scientific investigation. 5. Discuss examples of emergent phenomena and explain why they are classified as emergent.
Taught by: Michael Dennin, Professor of Physics and Astronomy; Vice Provost for Teaching and Learning
Physics; Office of Teaching and Learning
Taught by: Jun Allard, Assistant Professor
Mathematics
Taught by: Donald Saari, UCI Distinguished Professor of Economics and Mathematics
Economics; Institute for Mathematical Behavioral Sciences
Taught by: Andrea Nicholas, Lecturer PSOE
Neurobiology & Behavior
Taught by: Fred Y.M. Wan, Professor
Mathematics
Taught by: Siddharth A. Parameswaran, Assistant Professor
Physics and Astronomy
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
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i enjoyed all the different modules. I recommend they add more explanation to the chaos game assignment.
I've learned a lot about emergent phenomena on this course.
All the topics are quite interesting and surprising (and I mean every one of them), but all are treated like popular science with little insight. I had to read elsewhere to fully understand some topics such as reaction-difussion systems. All in all, I wish there was a version of this course for those of us who have no fear of mathematics.
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It's really a good course because it consists of not too big chunks of information, small enough to get a grip on. Great overview of many completely different fields of science where emergence plays a role. A deeper insight of especially how the brain creates these emergent phenomena would be interesting but of course it's off course ;-), because that would be whole different session.