A model for the emergence of cooperation, interdependence, and structure in evolving networks
Author(s) -
Sanjay Jain,
Sandeep Krishna
Publication year - 2001
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.98.2.543
Subject(s) - autocatalysis , simple (philosophy) , directed graph , graph , computer science , set (abstract data type) , complex network , network model , biological network , network formation , theoretical computer science , statistical physics , evolutionary biology , biology , artificial intelligence , computational biology , physics , algorithm , epistemology , catalysis , biochemistry , world wide web , programming language , philosophy
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, 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 autocatalytic set enlarges and percolates through the network in a short analytically determined timescale. This self organization does not require the presence of self-replicating species. The network also exhibits catastrophes over long timescales triggered by the chance elimination of "keystone" species, followed by recoveries.
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