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Complexity Theory - by John Cleveland

Nov 22, 2015

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Complexity Theory,
Basic Concepts and Applications to Systems Thinking
by John Cleveland
March 27, 1994
Innovation Network For Communities

  • COMPLEXITY THEORY

    BASIC CONCEPTS AND APPLICATION TO SYSTEMS THINKING

    March 27, 1994

    John ClevelandInnovation Network For Communities

  • A Short Introduction to Complex Adaptive Systems On the Edge of Chaos

    The field of complex adaptive systems theory (also known as complexity theory)seeks to understand how order emerges in complex, non-linear systems such asgalaxies, ecologies, markets, social systems and neural networks. Complexityscientists suggest that living systems migrate to a state of dynamic stability they call theedge of chaos. Mitchell Waldrop provides a description of the edge of chaos in hisbook, Complexity:

    The balance point -- often called the edge of chaos -- is where the components of asystem never quite lock into place, and yet never quite dissolve into turbulenceeither. . . The edge of chaos is where life has enough stability to sustain itself andenough creativity to deserve the name of life. The edge of chaos is where new ideaand innovative genotypes are forever nibbling away at the edges of the status quo,and where even the most entrenched old guard will eventually be overthrown. Theedge of chaos is where centuries of slavery and segregation suddenly give way tothe civil rights movement of the 1950s and 1960s; where seventy years of Sovietcommunism suddenly give way to political turmoil and ferment; where eons ofevolutionary stability suddenly give way to wholesale species transformation. Theedge is the constantly shifting battle zone between stagnation and anarchy, the oneplace where a complex system can be spontaneous, adaptive and alive.

    Systems on the edge are notable for a hunger for novelty and disequilibrium thatdistinguishes them from rigidly ordered systems. At the same time, however, they alsopossess a deep underlying coherence that provides structure and continuity, anddistinguishes them from chaotic systems. Theorists use words like integrity, identitypersistent structure and self-reference to describe this opposite characteristic.Systems that evolve along the edge of chaos periodically re-integrate into structureswith temporary stability, which bear recognizable resemblance to the string ofpredecessor structures. They are free enough to change, but stable enough to stayrecognizable.

    Complexity scientists have identified several characteristics that distinguish edge ofchaos systems from systems that are either locked in rigid order, or too chaotic for anystability to emerge. These include:

    Autonomous agents. Like a swarm of bees, a flock of birds, or a healthy market,these systems are made up of many individual actors who make choices about howto act based on information in their local environment. All the agents make choicessimultaneously (parallel processing), both influencing and limiting each othersactions.

    Networked structure. The agents dont act randomly. They share some commonrules about how they decide what to do next. At the level of matter, these commonrules are the laws of nature (gravity, electromagnetism, etc.). At the level ofconscious actors, these are decision-making rules (preferences, interests, desires,

  • etc.). These rules connect the agents together and allow a global coherence toemerge without any central source of direction -- the swarm has velocity, shape,direction and density that do not reside in any individual agent. The rules used byagents evolve based on their successfulness in the changing environment. Theconnections between agents in edge of chaos systems are moderately dense not so interconnected so the system freezes up, and not so disconnected that itdisintegrates into chaos.

    Profuse experimentation. These edge of chaos systems are full of novelty andexperimentation. They have a quality of dynamic stability that is characterized byoccasional rapid and unpredictable shifts in shape and direction. They can react tosmall changes in big and surprising ways (rumors fly like lightning; a mob forms; themarket crashes; the hive swarms). Such systems can communicate almostinstantaneously, experiment with dozens of possible responses if they encounter aroadblock, and rapidly exploit solutions when one is found.

    In describing the edge of chaos, complexity scientists have documented and analyzedqualities that humans have sought in their systems for some time. A vibrant democracyis an edge of chaos form of governance; a healthy market is an edge of chaos formof economics; a flexible and adaptive organization is an edge of chaos institution; anda mature, well-developed personality is an edge of chaos psyche.

    In many of our systems, however, we have created forms of organization that arelocked in rigid order and incapable of adaptable evolution (e.g. bureaucracies,monopolies, dictatorships). These forms of social control were often responses tosituations that were previously too chaotic. In multiple sectors of society, we now see amigration from both extremes of incoherent chaos and rigid order towards the middleedge of chaos where systems have the capacity to grow, learn and evolve.

    The attached materials describe some of the basic concepts of complex adaptivesystems theory.

  • 1. TYPES OF SYSTEMS systems

    The Basic Concept:

    Scientists and others use many different labels to describe different kinds of systems.These terms can be confusing to the non-specialist. It is helpful to understand the"taxonomy" of system types in order to understand what complex adaptive systems areand are not.

    Discussion:

    These are the most commonly used terms for different kinds of systems. They areloosely listed in order from least complex to most complex system.

    Entropy -- No System. The condition of entropy is a condition where there is no usableenergy in the system, no connections between the elements of the system, and noobservable structure.

    Closed Systems. A closed system is a system that does not import or export energyacross its boundaries. The only truly closed system is the universe as a whole.Traditional physics deals with systems that are presumed to be closed systems. Inclosed systems, the final state of the system is determined by its initial conditions. Allclosed systems move to a condition of equilibrium and maximum entropy.

    Open Systems. The term "open system" is a general term given to any system whichexchanges matter, energy or information across its boundaries, and uses that exchangeof energy to maintain its structure. All living systems, including all complex adaptivesystems, are open systems. Not all open systems, however, are complex and adaptive.(For instance, a burning candle is an open system.)Self-Organizing Systems. The term "self-organizing" refers to the spontaneousemergence of new forms of order. Self-organization is distinguished by the fact thatthere is no external agent that designs, constructs or maintains the system. Structurefreely emerges from the internal interactions of the system itself. Many open systemsdisplay qualities of self-organization. The phenomenon of self-organization only occursin systems that are "far from equilibrium" -- where there is continuous flux and vigorousexchange of energy between the parts of the system. (See Self-Organization.)Dissipative Structures. This is the term the chemist Ilya Prigogine gave to self-organizing systems. The terms "self-organizing system" and "dissipative structure"mean essentially the same thing. The term "dissipative" refers to the fact that thesesystems consume energy and "dissipate" it into the environment (thereby creatingentropy.) Dissipative structures maintain a form of global structure and stability by aconstant pattern of internal fluctuations. Through the process of autocatalysis, smallfluctuations are often magnified into large disturbances that either cause the system todisintegrate, or to reorganize into a new form. (See Feedback.)

  • Autopoetic Systems. The term "autopoetic" is used to refer to any system that renewsitself and regulates the renewal process in such a way that its overall structure ispreserved. The terms "autopoetic", "self-organizing" and "dissipative" are generallymeant to mean the same thing when referring to systems. An autopoetic system(whose only purpose is self-preservation and renewal) can be distinguished from amachine, whose purpose is geared toward the production of a particular output.

    Natural Systems. This is the term that the general system theorist Ervin Laszlo gives toself-organizing systems. The four characteristics of natural systems as Laszlo identifiesthem are: 1) they are wholes, with irreducible properties; 2) they maintain themselves ina changing environment; 3) they create and recreate themselves in response to thechallenges of the environment; and 4) they mediate interaction between thesubsystems that make them up, and the larger "supra-systems" of which they are apart. Again, the term "natural system" can, for all practical purposes, be seen assynonymous with open, self-organizing, dissipative and autopoetic systems.

    Classes of Systems. The complexity scientists have adopted a classification ofsystems based on the work of the physicist Stephen Wolfram. The four classes arebased on the behavior of the system: Class I systems move quickly to a single point,and stay there (vaguely equivalent to a closed system moving to equilibrium); Class IIsystems oscillate between a limited number of end states; Class III systems are"boiling" -- totally chaotic, with no stability or structure; Class IV systems are "on theedge of chaos", "alive" -- they have enough structure to create patterns, but thepatterns never really settle down. Class IV systems is what is meant by "complexadaptive systems." (See Classes of Systems.)Complex Adaptive Systems. Complex adaptive systems are open, self-organizingsystems that have t