Definitions

Self-organization

Self-organization

Self-organization is a process of attraction and repulsion in which the internal organization of a system, normally an open system, increases in complexity without being guided or managed by an outside source. Self-organizing systems typically (though not always) display emergent properties.

Overview

The most robust and unambiguous examples of self-organizing systems are from physics. Self-organization is also relevant in chemistry, where it has often been taken as being synonymous with self-assembly. The concept of self-organization is central to the description of biological systems, from the subcellular to the ecosystem level. There are also cited examples of "self-organizing" behaviour found in the literature of many other disciplines, both in the natural sciences and the social sciences such as economics or anthropology. Self-organization has also been observed in mathematical systems such as cellular automata.

Sometimes the notion of self-organization is conflated with that of the related concept of emergence. Properly defined, however, there may be instances of self-organization without emergence and emergence without self-organization, and it is clear from the literature that the phenomena are not the same. The link between emergence and self-organization remains an active research question.

Self-organization usually relies on four basic ingredients:

  1. Positive feedback
  2. Negative feedback
  3. Balance of exploitation and exploration
  4. Multiple interactions

History of the idea

The idea that the dynamics of a system can tend by themselves to increase the inherent order of a system has a long history. One of the earliest statements of this idea was by the philosopher Descartes, in the fifth part of his Discourse on Method, where he presents it hypothetically. Descartes further elaborated on the idea at great length in his unpublished work The World.

The ancient atomists (among others) believed that a designing intelligence was unnecessary, arguing that given enough time and space and matter, organization was ultimately inevitable, although there would be no preferred tendency for this to happen. What Descartes introduced was the idea that the ordinary laws of nature tend to produce organization (For related history, see Aram Vartanian, Diderot and Descartes).

Beginning with the 18th century naturalists a movement arose that sought to understand the "universal laws of form" in order to explain the observed forms of living organisms. Because of its association with Lamarckism, their ideas fell into disrepute until the early 20th century, when pioneers such as D'Arcy Wentworth Thompson revived them. The modern understanding is that there are indeed universal laws (arising from fundamental physics and chemistry) that govern growth and form in biological systems.

The term "self-organizing" seems to have been first introduced in 1947 by the psychiatrist and engineer W. Ross Ashby. It was taken up by the cyberneticians Heinz von Foerster, Gordon Pask, Stafford Beer and Norbert Wiener himself in the second edition of his "Cybernetics: or Control and Communication in the Animal and the Machine" (MIT Press 1961). Self-organization as a word and concept was used by those associated with general systems theory in the 1960s, but did not become commonplace in the scientific literature until its adoption by physicists and researchers in the field of complex systems in the 1970s and 1980s.

Examples

The following list summarizes and classifies the instances of self-organization found in different disciplines. As the list grows, it becomes increasingly difficult to determine whether these phenomena are all fundamentally the same process, or the same label applied to several different processes. Self-organization, despite its intuitive simplicity as a concept, has proven notoriously difficult to define and pin down formally or mathematically, and it is entirely possible that any precise definition might not include all the phenomena to which the label has been applied.

It should also be noted that, the farther a phenomenon is removed from physics, the more controversial the idea of self-organization as understood by physicists becomes. Also, even when self-organization is clearly present, attempts at explaining it through physics or statistics are usually criticized as reductionistic.

Similarly, when ideas about self-organization originate in, say, biology or social science, the farther one tries to take the concept into chemistry, physics or mathematics, the more resistance is encountered, usually on the grounds that it implies direction in fundamental physical processes. However the tendency of hot bodies to get cold (see Thermodynamics) and by Le Chatelier's Principle- the statistical mechanics extension of Newton's Third Law- to oppose this tendency should be noted.

Self-organization in physics

There are several broad classes of physical processes that can be described as self-organization. Such examples from physics include:

Self-organization vs. entropy

Statistical mechanics informs us that large scale phenomena can be viewed as a large system of small interacting particles, whose processes are assumed consistent with well established mechanical laws such as entropy, i.e., equilibrium thermodynamics. However, “… following the macroscopic point of view the same physical media can be thought of as continua whose properties of evolution are given by phenomenological laws between directly measurable quantities on our scale, such as, for example, the pressure, the temperature, or the concentrations of the different components of the media. The macroscopic perspective is of interest because of its greater simplicity of formalism and because it is often the only view practicable.” Against this background, Glansdorff and Ilya Prigogine introduced a deeper view at the microscopic level, where “… the principles of thermodynamics explicitly make apparent the concept of irreversibility and along with it the concept of dissipation and temporal orientation which were ignored by classical (or quantum) dynamics, where the time appears as a simple parameter and the trajectories are entirely reversible.”

As a result, processes considered part of thermodynamically open systems, such as biological processes that are constantly receiving, transforming and dissipating chemical energy (and even the earth itself which is constantly receiving and dissipating solar energy), can and do exhibit properties of self organization far from thermodynamic equilibrium.

A LASER (acronym for “light amplification by stimulated emission of radiation”) can also be characterized as a self organized system to the extent that normal states of thermal equilibrium characterized by electromagnetic energy absorption are stimulated out of equilibrium in a reverse of the absorption process. “If the matter can be forced out of thermal equilibrium to a sufficient degree, so that the upper state has a higher population than the lower state (population inversion), then more stimulated emission than absorption occurs, leading to coherent growth (amplification or gain) of the electromagnetic wave at the transition frequency.”

Self-organization in chemistry

Self-organization in chemistry includes:

  1. molecular self-assembly
  2. reaction-diffusion systems and oscillating chemical reactions
  3. autocatalytic networks (see: autocatalytic set)
  4. liquid crystals
  5. colloidal crystals
  6. self-assembled monolayers
  7. micelles
  8. microphase separation of block copolymers
  9. Langmuir-Blodgett films

Self-organization in biology

According to Scott Camazine.. [et al.]:
In biological systems self-organization is a process in which pattern at the global level of a system emerges solely from numerous interactions among the lower-level components of the system. Moreover, the rules specifying interactions among the system's components are executed using only local information, without reference to the global pattern.
The following is an incomplete list of the diverse phenomena which have been described as self-organizing in biology.

  1. spontaneous folding of proteins and other biomacromolecules
  2. formation of lipid bilayer membranes
  3. homeostasis (the self-maintaining nature of systems from the cell to the whole organism)
  4. pattern formation and morphogenesis, or how the living organism develops and grows. See also embryology.
  5. the coordination of human movement, e.g. seminal studies of bimanual coordination by Kelso
  6. the creation of structures by social animals, such as social insects (bees, ants, termites), and many mammals
  7. flocking behaviour (such as the formation of flocks by birds, schools of fish, etc.)
  8. the origin of life itself from self-organizing chemical systems, in the theories of hypercycles and autocatalytic networks
  9. the organization of Earth's biosphere in a way that is broadly conducive to life (according to the controversial Gaia hypothesis)

Self-organization in mathematics and computer science

As mentioned above, phenomena from mathematics and computer science such as cellular automata, random graphs, and some instances of evolutionary computation and artificial life exhibit features of self-organization. In swarm robotics, self-organization is used to produce emergent behavior. In particular the theory of random graphs has been used as a justification for self-organization as a general principle of complex systems. In the field of multi-agent systems, understanding how to engineer systems that are capable of presenting self-organized behavior is a very active research area.

Self-organization in cybernetics

Wiener regarded the automatic serial identification of a black box and its subsequent reproduction as sufficient to meet the condition of self-organization. The importance of phase locking or the "attraction of frequencies", as he called it, is discussed in the 2nd edition of his "Cybernetics". Drexler sees self-replication as a key step in nano and universal assembly.

By contrast, the four concurrently connected galvanometers of W. Ross Ashby's homeostat hunt, when perturbed, to converge on one of many possible stable states. Ashby used his state counting measure of variety to describe stable states and produced the "Good Regulator theorem which required internal models for self-organized endurance and stability.

Warren McCulloch proposed "Redundancy of Potential Command as characteristic of the organization of the brain and human nervous system and the necessary condition for self-organization.

Heinz von Foerster proposed Redundancy, R = 1- H/Hmax , where H is entropy. In essence this states that unused potential communication bandwidth is a measure of self-organization.

In the 1970s Stafford Beer considered this condition as necessary for autonomy which identifies self-organization in persisting and living systems. Using Variety analyses he applied his neurophysiologically derived recursive Viable System Model to management. It consists of five parts: the monitoring of performance of the survival processes (1), their management by recursive application of regulation (2), homeostatic operational control (3) and development (4) which produce maintenance of identity (5) under environmental perturbation. Focus is prioritized by an "algedonic loop" feedback: a sensitivity to both pain and pleasure.

In the 1990s Gordon Pask pointed out von Foerster's H and Hmax were not independent and interacted via countably infinite recursive concurrent spin processes (he favoured the Bohm interpretation) which he called concepts (liberally defined in any medium, "productive and, incidentally reproductive"). His strict definition of concept "a procedure to bring about a relation permitted his theorem "Like concepts repel, unlike concepts attract to state a general spin based Principle of Self-organization. His edict, an exclusion principle, "There are No Doppelgangers means no two concepts can be the same (all interactions occur with different perpectives making time incommensurable for actors). This means, after sufficient duration as differences assert, all concepts will attract and coalesce as pink noise and entropy increases (and see Big Crunch, self-organized criticality). The theory is applicable to all organizationally closed or homeostatic processes that produce endurance and coherence (also in the sense of Reshcher Coherence Theory of Truth with the proviso that the sets and their members exert repulsive forces at their boundaries) through interactions: evolving, learning and adapting.

Pask's Interactions of actors "hard carapace" model is reflected in some of the ideas of emergence and coherence. It requires a knot emergence topology that produces radiation during interaction with a unit cell that has a prismatic tensegrity structure. Laughlin's contribution to emergence reflects some of these constraints.

Self-organization in human society

The self-organizing behaviour of social animals and the self-organization of simple mathematical structures both suggest that self-organization should be expected in human society. Tell-tale signs of self-organization are usually statistical properties shared with self-organizing physical systems (see Zipf's law, power law, Pareto principle). Examples such as Critical Mass, herd behaviour, groupthink and others, abound in sociology, economics, behavioral finance and anthropology.

In social theory the concept of self-referentiality has been introduced as a sociological application of self-organization theory by Niklas Luhmann (1984). For Luhmann the elements of a social system are self-producing communications, i.e. a communication produces further communications and hence a social system can reproduce itself as long as there is dynamic communication. For Luhmann human beings are sensors in the environment of the system. Luhmann put forward a functional theory of society.

Self-organization in human and computer networks can give rise to a decentralized, distributed, self-healing system, protecting the security of the actors in the network by limiting the scope of knowledge of the entire system held by each individual actor. The Underground Railroad is a good example of this sort of network. The networks that arise from drug trafficking exhibit similar self-organizing properties. Parallel examples exist in the world of privacy-preserving computer networks such as Tor. In each case, the network as a whole exhibits distinctive synergistic behavior through the combination of the behaviors of individual actors in the network. Usually the growth of such networks is fueled by an ideology or sociological force that is adhered to or shared by all participants in the network.

In economics

In economics, a market economy is sometimes said to be self-organizing. Friedrich Hayek coined the term catallaxy to describe a "self-organizing system of voluntary co-operation," in regard to capitalism. Most modern economists hold that imposing central planning usually makes the self-organized economic system less efficient. By contrast, some socialist economists consider that market failures are so significant that self-organization produces bad results and that the state should direct production and pricing. Many economists adopt an intermediate position and recommend a mixture of market economy and command economy characteristics (sometimes called a mixed economy).

In collective intelligence

Non-thermodynamic concepts of entropy and self-organization have been explored by many theorists. Cliff Joslyn and colleagues and their so-called "global brain" projects. Marvin Minsky's "Society of Mind" and the no-central editor in charge policy of the open sourced internet encyclopedia, called Wikipedia, are examples of applications of these principles - see collective intelligence.

Donella Meadows, who codified twelve leverage points that a self-organizing system could exploit to organize itself, was one of a school of theorists who saw human creativity as part of a general process of adapting human lifeways to the planet and taking humans out of conflict with natural processes. See Gaia philosophy, deep ecology, ecology movement and Green movement for similar self-organizing ideals.

See also

References

Further reading

  • W. Ross Ashby (1947), "Principles of the Self-Organizing Dynamic System", Journal of General Psychology Vol 37, pp. 125-128.
  • W. Ross Ashby (1966), Design for a Brain, Chapman & Hall, 2nd edition.
  • Per Bak (1996), How Nature Works: The Science of Self-Organized Criticality, Copernicus Books.
  • Philip Ball (1999), The Self-Made Tapestry: Pattern Formation in Nature, Oxford University Press.
  • Stafford Beer, Self-organization as autonomy: Brain of the Firm 2nd edition Wiley 1981 and Beyond Dispute Wiley 1994.
  • A. Bejan (2000), Shape and Structure, from Engineering to Nature , Cambridge University Press, Cambridge, UK, 324 pp.
  • Mark Buchanan (2002), Nexus: Small Worlds and the Groundbreaking Theory of Networks W. W. Norton & Company.
  • Scott Camazine, Jean-Louis Deneubourg, Nigel R. Franks, James Sneyd, Guy Theraulaz, & Eric Bonabeau (2001) Self-Organization in Biological Systems, Princeton Univ Press.
  • Falko Dressler (2007), Self-Organization in Sensor and Actor Networks, Wiley & Sons.
  • Manfred Eigen and Peter Schuster (1979), The Hypercycle: A principle of natural self-organization, Springer.
  • Myrna Estep (2003), A Theory of Immediate Awareness: Self-Organization and Adaptation in Natural Intelligence, Kluwer Academic Publishers.
  • Myrna L. Estep (2006), Self-Organizing Natural Intelligence: Issues of Knowing, Meaning, and Complexity, Springer-Verlag.
  • J. Doyne Farmer et al. (editors) (1986), "Evolution, Games, and Learning: Models for Adaptation in Machines and Nature", in: Physica D, Vol 22.
  • Heinz von Foerster and George W. Zopf, Jr. (eds.) (1962), Principles of Self-Organization (Sponsored by Information Systems Branch, U.S. Office of Naval Research.
  • "Aeshchines" (false identity made in reference to the classical Greek orator Aeschines) (2007). "The Open Source Manifesto" the self organization of economic and geopolitical structure through the Open Source movement permanent link at Sourceforge.net
  • Carlos Gershenson and Francis Heylighen (2003). "When Can we Call a System Self-organizing?" In Banzhaf, W, T. Christaller, P. Dittrich, J. T. Kim, and J. Ziegler, Advances in Artificial Life, 7th European Conference, ECAL 2003, Dortmund, Germany, pp. 606-614. LNAI 2801. Springer.
  • Hermann Haken (1983) Synergetics: An Introduction. Nonequilibrium Phase Transition and Self-Organization in Physics, Chemistry, and Biology, Third Revised and Enlarged Edition, Springer-Verlag.
  • F.A. Hayek Law, Legislation and Liberty, RKP, UK.
  • Francis Heylighen (2001): "The Science of Self-organization and Adaptivity"
  • Henrik Jeldtoft Jensen (1998), Self-Organized Criticality: Emergent Complex Behaviour in Physical and Biological Systems, Cambridge Lecture Notes in Physics 10, Cambridge University Press.
  • Steven Johnson (2001), Emergence: The Connected Lives of Ants, Brains, Cities and Software.
  • Stuart Kauffman (1995), At Home in the Universe, Oxford University Press.
  • Stuart Kauffman (1993), Origins of Order: Self-Organization and Selection in Evolution Oxford University Press.
  • J. A. Scott Kelso (1995), Dynamic Patterns: The self-organization of brain and behavior, The MIT Press, Cambridge, MA.
  • J. A. Scott Kelso & David A Engstrom (2006), "The Complementary Nature", The MIT Press, Cambridge, MA.
  • Alex Kentsis (2004), Self-organization of biological systems: Protein folding and supramolecular assembly, Ph.D. Thesis, New York University.
  • Paul Krugman (1996), The Self-Organizing Economy, Cambridge, Mass., and Oxford: Blackwell Publishers.
  • Niklas Luhmann (1995) Social Systems. Stanford, CA: Stanford University Press.
  • Elizabeth McMillan (2004) "Complexity, Organizations and Change".
  • Müller, J.-A., Lemke, F. (2000), Self-Organizing Data Mining.
  • Gregoire Nicolis and Ilya Prigogine (1977) Self-Organization in Non-Equilibrium Systems, Wiley.
  • Heinz Pagels (1988), The Dreams of Reason: The Computer and the Rise of the Sciences of Complexity, Simon & Schuster.
  • Gordon Pask (1961), The cybernetics of evolutionary processes and of self organizing systems, 3rd. International Congress on Cybernetics, Namur, Association Internationale de Cybernetique.
  • Gordon Pask (1993) Interactions of Actors (IA), Theory and Some Applications, Download incomplete 90 page manuscript.
  • Gordon Pask (1996) Heinz von Foerster's Self-Organisation, the Progenitor of Conversation and Interaction Theories, Systems Research (1996) 13, 3, pp. 349-362
  • Christian Prehofer ea. (2005), "Self-Organization in Communication Networks: Principles and Design Paradigms", in: IEEE Communications Magazine, July 2005.
  • Mitchell Resnick (1994), Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds, Complex Adaptive Systems series, MIT Press.
  • Lee Smolin (1997), The Life of the Cosmos Oxford University Press.
  • Ricard V. Solé and Brian C. Goodwin (2001), Signs of Life: How Complexity Pervades Biology, Basic Books.
  • Ricard V. Solé and Jordi Bascompte (2006), Selforganization in Complex Ecosystems, Princeton U. Press
  • Steven Strogatz (2004), Sync: The Emerging Science of Spontaneous Order, Theia.
  • D'Arcy Thompson (1917), On Growth and Form, Cambridge University Press, 1992 Dover Publications edition.
  • Norbert Wiener (1962), The mathematics of self-organising systems. Recent developments in information and decision processes, Macmillan, N. Y. and Chapter X in Cybernetics, or control and communication in the animal and the machine, The MIT Press, 2nd Edition 1962
  • Tom De Wolf, Tom Holvoet (2005), Emergence Versus Self-Organisation: Different Concepts but Promising When Combined, In Engineering Self Organising Systems: Methodologies and Applications, Lecture Notes in Computer Science, volume 3464, pp 1-15.
  • K. Yee (2003), "Ownership and Trade from Evolutionary Games," International Review of Law and Economics, 23.2, 183-197
  • Louise B. Young (2002), The Unfinished Universe
  • Mikhail Prokopenko (ed.) (2008), Advances in Applied Self-organizing Systems, Springer.

External links

Disertations and Theses on Self-organization

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