#reading digest

Chapter 1-4

1+1+1+1+ ... 1+1+1 > n - The hive mind

量变至质变。简单结构的重复能够产生高等级的复杂性。1+1 = apple

如：人脑（人体），蚁群，探索机器人群组

1+1+1+1+ ... 1+1+1 < n - Assembling complexity

仅观察复杂系统，得出其所有元素，并不能重复获得该复杂系统

如：在培育生态系统过程中，有一些关键元素属于中间过程，但在开始和末尾都不会存在。如果培育过程中不及时引入，将会失败

Chapter 6 The Natural Flux

大多复杂系统（自然和人为）要存活的状态，通常都不是所谓的“平衡“状态，而是”快要垮掉“的状态。

P.93 A major reason why ecologists favored equilibrium end points in nature was exactly the same reason why economists favored equilibrium end points in the economy: the mathematics of equilibrium were possible. You could write an equation for a process that you could actually solve. But if you said that the system was perpetually in disequilibrium, you were saying it followed a model you couldn't solve and therefore couldn't explore. You were saying almost nothing. It is no coincidence, therefore, that a major shit in ecological (and economic) understanding occurred in the era when cheap computers made nonequilibrial and nonlinear equations easy to program. It was suddenly no problem to model a chaotic, co-evolutionary ecosystem on a personal computer, and see that, hey it acts very much like the odd behavior of a Saguaro forest or a prairie savanna on the march.

...

"Equilibrium is not only dead, it is death," Burgess emphasizes. "To enrich a system you need variance in time and space. But too much change will kill you too. You go from an ecocline to ecotone."

Burgess finds nature's reliance on disturbances and variance to be a practical issue. "In nature, it is no problem if you have very erratic production [of vegetation, seeds, or meat] from year to year. Nature actually increases her richness from this variance. But when people try to sustain themselves on the production from an ecosystem like a desert that is so variance driven, they can only do it by simplifying the system into what we call agriculture - which gives a constant production for a variable environment." Burgess hopes the flux of the desert can teach us how to live with a variable environment without simplifying it. It is not a completely foolish dream. Part of what an information-driven economy provides us an adaptable infrastructure that can bend and work around irregular production; this is the basis for flexible and "just=in-time" manufacturing. It is theoretically possible that we could use information networks to coordinate the investment and highly irregular output of a rich, fluxing ecosystem that provides food and organic resources. But as Burgess admits, "At the moment we have no industrial economic models that are variance driven, except gambling."