Game theory is the standard quantitative tool for analyzing the interactions of multiple decision makers. Its applications extend to economics, biology, engineering and even cyber security.
In this course you'll learn about the tools used by scientists to understand complex systems. The topics you'll learn about include dynamics, chaos, fractals, information theory, self-organization, agent-based modeling, and networks.
This is a hands on four chapter course to learn how to better understand and act when faced with complex situations By the end of the course students will be able to take a story from the news describe what makes the situation complex and identify opportunities for effective action …
In this course you'll gain an introduction to the modern study of dynamical systems, the interdisciplinary field of applied mathematics that studies systems that change over time. Topics to be covered include: phase space, bifurcations, chaos, the butterfly effect, strange attractors, and pattern formation.
This course provides a broad introduction to the field of nonlinear dynamics, focusing both on the mathematics and the computational tools that are so important in the study of chaotic systems. The course is aimed at students who have had at least one semester of college-level calculus and physics, and who can program in at least one high-level language (C, Java, Matlab, R, ...)
In a span of around 12 weeks, the course covers a wide range of topics including agent-based modeling, networks, dynamic, chaos, information, fractals, cooperation models and scaling in biology and society. The course acts as a perfect beginner level introduction spanning a wide range of topics in the field of complexity.