Inference, Models and Simulation for Complex Systems
- Computers are fundamentally changing how science is done by allowing us to record enormous amounts of data on social, biological, technological and physical systems. This data glut should allow us both to address old questions about complex systems in new ways and to answer fundamentally new kinds of questions.
This graduate-level topics course will cover a selection of recent developments in computational approaches to doing science with complex systems. It is not a scientific computing course. Topics will include statistical inference, the structure of complex networks, macro-phenomena in biological evolution and in wars and terrorism, simple mathematical models, and simulation techniques for more complicated models.
- University of Colorado, Boulder
- Aaron Clauset
- Networks, Complex Systems, Statistics