A new offering from SFI’s online education resource, Complexity Explorer, gives complexity enthusiasts quantitative tools for distinguishing the "complex" aspects of a system from the merely "complicated."
The mathematics tutorial, “Maximum Entropy Methods,” teaches data analysis techniques for identifying simple sets of principles that describe complex systems such as a brains, or ecosystems.
The tutorial's instructor Simon DeDeo explains that “what MaxEnt does is allow you to disregard what is only ‘complicated’ in the system…if you’re able to come up with a satisfying account of the system using MaxEnt principles, it implicitly is telling you that a bunch of stuff doesn’t matter. It looks like it’s meaningful but it’s not.” DeDeo is an SFI External Professor and an alum of the Omidyar Postdoctoral Fellowship.
High-school-level calculus is prerequisite for understanding the course, and the workload is self-paced. Because it is a mathematics tutorial, Maximum Entropy Methods will always be available online, unlike some other online courses in the Complexity Explorer roster.
Read Simon DeDeo’s Q&A about the ‘MaxEnt’ tutorial on Complexity Explorer (June 10, 2015)