Self-organization

Self-organization is a process where some form of overall order or coordination arises out of the local interactions between smaller component parts of an initially disordered system. The process of self-organization can be spontaneous, and it is not necessarily controlled by any auxiliary agent outside of the system. It is often triggered by random fluctuations that are amplified by positive feedback. The resulting organization is wholly decentralized or distributed over all the components of the system. As such, the organization is typically robust and able to survive and, even, self-repair substantial damage or perturbations. Chaos theory discusses self-organization in terms of islands of predictability in a sea of chaotic unpredictability. Self-organization occurs in a variety of physical, chemical, biological, robotic, economical, social, and cognitive systems.

Self-organization usually relies on three basic ingredients:

• Strong dynamical non-linearity, often though not necessarily involving positive and negative feedback
• Balance of exploitation and exploration
• Multiple interactions

Some scientist considered the following views as principles of self-organization:

• Any deterministic dynamic system will automatically evolve towards a state of equilibrium that can be described in terms of an attractor in a basin of surrounding states. Once there, the further evolution of the system is constrained to remain in the attractor. (by William Ross Ashby in 1947).
• “Order from noise”. Self-organization is facilitated by random perturbations (“noise”) that let the system explore a variety of states in its state space. This increases the chance that the system would arrive into the basin of a “strong” or “deep” attractor, from which it would then quickly enter the attractor itself. (by Heinz von Foerster in 1960).
• “Order through fluctuations” or “order out of chaos”. It is applied in the method of simulated annealing that is used in problem solving and in machine learning. (by Ilya Prigogine

See also

Complex systems, Dynamical systems, Self-organizing criticality, Collective Intelligence, Self-organizing maps

Material

• Max Planck Institute for Dynamics and Self-Organization, Göttingen

Papers

• Heylighen, F. (2001). The science of self-organization and adaptivity. The encyclopedia of life support systems, 5(3), 253-280.
• Von Foerster, H. (1984). Principles of self-organization-in a socio-managerial context. In Self-organization and management of social systems (pp. 2-24). Springer Berlin Heidelberg.
• Lehn, J. M. (2002). Toward self-organization and complex matter. Science, 295(5564), 2400-2403.
• Gershenson, C. (2004). Self-organizing traffic lights. arXiv preprint nlin/0411066.

Books

• Nicolis, G., & Prigogine, I. (1977). Self-organization in nonequilibrium systems (Vol. 191977). Wiley, New York.
• Krugman, P. (1996). The self-organizing economy (No. 338.9 KRU 1996. CIMMYT.).
• Kohonen, T. (2012). Self-organization and associative memory (Vol. 8). Springer Science & Business Media.
• Kelso, J. S. (1997). Dynamic patterns: The self-organization of brain and behavior. MIT press.
• Camazine, S. (2003). Self-organization in biological systems. Princeton University Press.
• HowARD, T. (1988). Self-organization, transformity, and information. Energy, 1, 30.