Evolution produces complex and structured networks of interacting components
in chemical, biological, and social systems. We describe a simple mathematical
model for the evolution of an idealized chemical system to study how a network
of cooperative molecular species arises and evolves to become more complex and
structured. The network is modeled by a directed weighted graph whose positive
and negative links represent catalytic' and inhibitory’ interactions among
the molecular species, and which evolves as the least populated species
(typically those that go extinct) are replaced by new ones. A small
autocatalytic set (ACS), appearing by chance, provides the seed for the
spontaneous growth of connectivity and cooperation in the graph. A highly
structured chemical organization arises inevitably as the ACS enlarges and
percolates through the network in a short, analytically determined time scale.
This self-organization does not require the presence of self-replicating
species. The network also exhibits catastrophes over long time scales triggered
by the chance elimination of `keystone’ species, followed by recoveries.

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