 The term edge of chaos is used to denote a phase transition space between order and disorder that is hypothesized to exist within a wide variety of systems. This transition zone between the two regimes is known as the edge of chaos, a region of bounded stability that engenders a constant dynamic interplay between order and disorder. This point or interface between the two is hypothesized to be a locus of maximum complexity and the dynamic driving evolution within many types of systems. The author Michael Waldrop in his book Complexity, The Emerging Science at the Edge of Order and Chaos, describes the term as such, right between the two extremes at a kind of abstract phase transition called the edge of chaos. You also find complexity, a class of behaviors in which the components of the system never quite lock into place, yet never dissolve into turbulence either. These are the systems that are both stable enough to store information, and yet evanescent enough to transmit it. These are systems that can be organized to perform complex computations, to react to the world, to be spontaneous, adaptive and alive. One of the original stimuli that led to the idea of the edge of chaos came from computer experiments with cellular automata done by the researcher Christopher Langton. Christopher Langton defined a quantity called lambda for any cellular automata. In very simplified terms, lower values of lambda corresponded to rule sets with this change, while higher values for lambda led to more change. He showed that cellular automata, with low lambdas, were more prone to rapidly moving towards a balanced or static point of stasis, while those with a high lambda value tended towards complete randomness. A lambda value towards the mid-range, a critical lambda, resulted in programs that could generate long periods of complex, aperiodic, non-random behavior before settling into either a fixed point or randomness. In the paper Langton published on the topic, he wrote, quote, Above a certain level of complexity, the process of synthesis is also degenerative. In other words, we find that there exists an upper limit as well as a lower limit on the complexity of a system, if the process of synthesis is to be non-degenerative, constructive or open-ended. We also find that these upper and lower bounds seem to be fairly close together and are located in the vicinity of a phase transition. As the systems near the phase transition exhibit a range of behaviors which reflects the phenomenology of computation surprisingly well, we suggest that we can locate computation within the spectrum of dynamical behaviors at a phase transition here at the edge of chaos. This edge of chaos condition within cellular automata was previously noted by von Neumann and it can be seen within Conway's Game of Life where he had to figure out how to get rules that would create complex patterns because if the rules to the Game of Life are slightly changed they will not produce interesting phenomena. These ideas originating in computer programs have since been generalized to all forms of systems that exhibit complex evolutionary behavior. Today in the sciences in general, the phrase edge of chaos has come to refer to a metaphor that some physical, biological, economic and social systems operate in a region between order and either complete randomness or chaos where the complexity is maximal. This edge of chaos phenomenon is thought to be a characteristic of many different types of complex systems as complexity cannot be understood in terms of simple symmetries but neither is it random, it is some combination of both. In the book Complexity in Organization the author writes quote nothing novel can emerge from systems with high degrees of order and stability, for example crystals, incestuous communities or regulated industries. On the other hand complete chaotic systems such as stampede, riots, rage or the early years of the French Revolution are too formless to coalesce. Generative complexity takes place in the boundary between regularity and randomness. A system with no order cannot exhibit useful behavior but also a system with too much order can become over constrained and likewise not exhibit functional results. It is possible that processes organize themselves into conditions so complex that no useful functionality can result from it, that is to say there can be too much accumulated information and constraints. The systems in between at the edge of order and chaos can exhibit a more flexible and organized behavior therefore it appears likely that self-organization needs to find a balance between lack of order and too much order. The edge of chaos phase transition area is then thought to be the locus for evolutionary processes that involve the perpetual collapse of local structures that then give rise to new patterns of organization creating a dynamic life cycle. Too much order and change will not cross rigid boundaries. Too much chaos and the system loses its organization. Complex adaptive systems such as ecosystems, societies and economies maintain themselves between this randomness and order where they can somehow use both in order to configure and reconfigure themselves. Going through both integration and differentiation in evolving to become more complex. Michael Waldrop gives an account of this when he writes quote the edge of chaos is where life has enough stability to sustain itself and enough creativity to deserve the name of life. The edge of chaos is where new ideas and 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. The edge of chaos is where centuries of slavery and segregation suddenly gave way to the civil rights movement of the 1950s and 1960s where 70 years of Soviet communism suddenly gave way to political turmoil and ferment where eons of evolutionary stability suddenly give way to wholesale species transformation. The edge is the constantly shifting battle zone between stagnation and anarchy, the one place where complex systems can be spontaneous, adaptive and alive. The idea of the edge of chaos represents a highly abstract but intuitive concept that has come to be applied to many different areas from business management to ecology to psychology, political science and various other domains of the social sciences. The idea of the edge of chaos is expressed within the work of the economist Joseph Schumpenter who formulated the idea of creative destruction as the driving force within a market economy. The idea of creative destruction describes how new innovations are constantly being generated by entrepreneurs in order to displace older ones in a continuous cyclical dynamic. Schumpenter starts in his book The Theory of Economic Development with the treatise of circular flow which excluding any innovations and innovative activity leads to a stationary state. Schumpenter's stationary state is, according to Schumpenter, described as the classical economic equilibrium of order and predictability. The entrepreneur is the one that disrupts this equilibrium and is thus the primary cause of economic development which proceeds in a cyclical fashion along several time scales. Schumpenter contributed to the ideas of evolutionary economics. According to Christopher Freeman, a scholar who devoted much of his time researching Schumpenter's work, the central point of his whole life work is that capitalism can only be understood as an evolutionary process of continuous innovation and creative destruction. Likewise, the idea of the edge of chaos has come to be associated with human cognition. When looking at the many possible cognitive states, it is possible to identify the highly predictable and orderly states from those that are more unpredictable and chaotic. In more chaotic regimes, network states are more disconnected from those in the orderly regime. However, at the edge of chaos, the states can be seen to be maximally novel while still connected to states in the ordered regime and thus are most likely to exhibit the combination of novelty and utility that is the hallmark of innovative thinking. The edge of chaos hypotheses can be applied to understanding society in terms of the dynamic interaction between micro and macro levels within the social system, whereas macro level social structures such as laws, religions, governments and other social institutions offer the potential for order and stability within the system. They can also impose too much order on the individuals, limiting their individual development in the name of conformity and group cohesion, ultimately leading to stasis and lack of novelty with which to innovate and evolve the social structure. Likewise, the micro level diversity of the agents' agendas can be seen as a constant source of disorder pulling in different directions and without macro stable institutions can create the potential for conflict between the many individual agendas of the agents and their special interest groups. A functioning society can be seen to be one that is able to maintain itself on the edge of chaos with both stable macro institutions that are capable of maintaining sufficient order but can also maintain individual autonomy as much as necessary for the individuals to develop. Functioning constitutional democracies that both maintain social order and individual rights through laws while also providing mechanisms for the individual members to change those institutions when needed may be an example of this. As such, they enable both an upward and a downward interaction in a cyclical fashion that is characteristic of evolutionary processes where new diversity comes from below while constraints and selection come from above to continuously generate new and relevant variants in response to changes in the environment.