Complexity: The Emerging Science at the Edge of Order and ChaosWhy did the stock market crash more than 500 points on a single Monday in 1987? Why do ancient species often remain stable in the fossil record for millions of years and then suddenly disappear? In a world where nice guys often finish last, why do humans value trust and cooperation? At first glance these questions don't appear to have anything in common, but in fact every one of these statements refers to a complex system. The science of complexity studies how single elements, such as a species or a stock, spontaneously organize into complicated structures like ecosystems and economies; stars become galaxies, and snowflakes avalanches almost as if these systems were obeying a hidden yearning for order. Drawing from diverse fields, scientific luminaries such as Nobel Laureates Murray Gell-Mann and Kenneth Arrow are studying complexity at a think tank called The Santa Fe Institute. The revolutionary new discoveries researchers have made there could change the face of every science from biology to cosmology to economics. M. Mitchell Waldrop's groundbreaking bestseller takes readers into the hearts and minds of these scientists to tell the story behind this scientific revolution as it unfolds. |
Other editions - View all
Complexity: The Emerging Science at the Edge of Order and Chaos Mitchell M. Waldrop Limited preview - 1993 |
Complexity: The Emerging Science at the Edge of Order and Chaos M. Mitchell Waldrop Limited preview - 2019 |
Common terms and phrases
actually agents Alamos Anderson Arrow autocatalytic set basic behavior biology boids brain building blocks Burks cell cellular automata Chris Langton classifier system complex adaptive systems course Doyne Farmer dynamics economics economists ecosystem edge of chaos emergence equilibrium evolution exactly example fact felt genes genetic algorithm going gotten happen human idea increasing returns intellectual interact John Holland kind knew learning look Los Alamos machine mathematical mind molecular molecules Murray Gell-Mann natural selection Neumann neural network nonlinear organize patterns phase transition Phil Anderson physicists physics precisely predict problem produce random realized rules Santa Fe Institute says Arthur says Cowan says Farmer says Holland says Kauffman says Langton scientists seemed self-organization simple simulation started strings structure Stuart Kauffman talk theory things thought trying turn understand University von Neumann universe wanted whole workshop