Computation in Complex Systems

This course explores computational complexity, from search algorithms and solution landscapes to reductions and universality. We explore problems ranging from easy (polynomial time) to hard (NP-complete) to impossible (undecidable). These ideas form one of the most beautiful fields of modern mathematics, and they are increasingly relevant to sciences ranging from physics to biology. The aim of this course is to help participants gain an understanding of the deep ideas of theoretical computer science in a clear and enjoyable fashion, making those ideas accessible both to non-computer scientists and to computer scientists who want to revisit these ideas in a broader and deeper way.

1. Easy and Hard
2. Algorithms and Landscapes
3. P versus NP
4. Worst-case, Natural, and Random
5. Computation Everywhere