Sublime

as cities grow and their networks evolve, the area or volume of the networks needed to keep them functionally connected tends to become smaller on a per capita basis. For example, in larger cities more people can share the same bus or segment of road or sewer pipe.

Perhaps the greatest “phase transition” in our thinking that such an approach could engender is the maturation in our willingness to live with relatively high levels of uncertainty in the domains of complex phenomena—and thus give up on ideas like complete “cures,” the elimination of “risk,” the design of perfect “stability,” and achieving total “s

The economy is thus comprised of evolving networks of interacting agents, institutions, and technologies—networks of networks. The macro- level patterns of the economy—growth, innovation, business cycles, market booms and busts, inequality, and carbon emissions—then emerge from these dynamic micro- and meso-level interactions. From the complexity e

Brigham Young, Bill Gore, Malcolm Gladwell, and Robin Dunbar may have been onto something. For typical real-world values of the control parameters there is, in fact, a sudden change in incentives around the magic number 150. At that size, the balance of forces in the tug-of-war changes, and the system suddenly snaps from favoring a focus on loonsho

Scientific progress, then, is not unidirectional but multidirectional and its characteristic discoveries both add new information and reformulate old information. Scientific curiosity, in this context, drives individual scientists and scientific communities to fill internal and external network cavities with informational nodes and conceptual edges

Where does complexity economics find itself now? Certainly, many commentators see it as steadily moving toward the center of economics. And there’s a recognition that it is more than a new set of methods or theories: it is a different way to see the economy. It views the economy not as machinelike, perfectly rational, and essentially static, but as