A plot of the Lorenz attractor for values r = 28, ? = 10, b = 8/3

Chaos Theory: Complexity, Emergence, and Chaos

The Workmen’s Circle
247 West 37th St, 5th Floor
New York, NY 10018

Chaos theory teaches us that deterministic systems can lead to dynamic instability. The complex systems that chaos theory attempts to describe are everywhere: natural ecosystems, weather patterns, DNA, cellular organization, the human brain and, significantly, economic and social organizations, particularly financial markets and social networks. According to chaos theory, long-term predictions are extremely sensitive to initial conditions (i.e. the “butterfly effect”) and are therefore, as a practical matter, impossible. As layers of complexity generate emergent properties, it becomes impossible to reduce even determined outcomes to obvious, original causes. However, chaos is not randomness. Complex systems can also be characterized by some degree of spontaneous self-order. How can considering the interrelation of complexity and chaos help us understand these systems?

In this course, we will survey the fascinating world of chaotic phenomena and related concepts (dynamic systems, strange attractors, fractals), as well as complex adaptive systems and the science of complexity. We will ponder topics as varied as the motion of billiard balls and pendulums; how organizations or firms adapt to their environments; market crashes; trust and cooperation; and the shape of seashells.Readings will include selections from Lorenz’s The Essence of Chaos, Mandelbrot’s The Fractal Geometry of Nature, Waldrop’s Complexity: The Emerging Science at the Edge of Order and Chaos, amongst others. There is no mathematical prerequisite, but we will not shy away from some mathematical examples when needed, depending on class interest.

Course Schedule

Wednesday, 6:30-9:30pm
April 05 — April 26, 2017
4 weeks


Registration Open