Marten Scheffer, Critical Transitions in Nature and Society (Princeton Studies in Complexity 2009)
Chapter checklist:
4.2 Stability of Complex Interacting Networks
5.2 Spatial Heterogeneity and Modularity
Check these Amazon bestseller categories, too:
Science > Physics > Chaos & Systems
Science > Physics > System Theory
Professional & Technical > Professional Science > Physics > System Theory
One theorem candidate:
A MACRO SYSTEM CAN BE AS ROBUST AS THE NETWORKS IN IT WITH DIFFERENT TOPOLOGIES CAN INTERCONNECT WITH EACH OTHER.
Sub-theorem:
A NODE/MODULE IN A SYSTEM IS AS VALUABLE AS IT CAN CONNECT/TAKE ADVANTAGE OF AS MANY NETWORKS WITH DIFFERENT TOPOLOGIES AS POSSIBLE.
And every living thing (or any system with biological “mind”) tries to achieve that goal. E.g. to interconnect as many different networks as possible. The interconnectivityness of a carbon is maybe just a coincidence…maybe.
Collaborative Online Mind Mapping
http://www.mindmeister.com/
Interconnects mind (neural network) maps which indeed are relational networks. Via web (http, tcp/ip, landline, etc.).
Related book: Robustness and Evolvability in Living Systems: (Princeton Studies in Complexity)
by Andreas Wagner
This blog will study Interconnected networks and systems.
vkarinen 0:09 on 6.9.2009 Permalink
An open (interconnected
) reference book:
Network Science
http://www.nap.edu/openbook.php?record_id=11516
Author/publisher:
Committee on Network Science for Future Army Applications
Board on Army Science and Technology
Division on Engineering and Physical Sciences
NATIONAL RESEARCH COUNCIL OF THE NATIONAL ACADEMIES
THE NATIONAL ACADEMIES PRESS
Washington, D.C.
2005
http://www.nap.edu
A caption from “Executive Summary (1-6)”:
“In spite of society’s profound dependence on networks, fundamental knowledge about them is primitive. Many physical networks—for example, global communication and transportation networks—have quite advanced technological implementations, but their behavior under stress still cannot be predicted reliably. For biological and social networks, scientists do not understand what they are, much less how they operate. There is a huge gap between what we need to know about networks to ensure the smooth working of society and the primitive state of our fundamental knowledge.”