# complexity and chaos theory

## complexity and chaos theory (chaotic phenemena)

the origins of thinking on complexity and chaos can be found in 19th-century social theory (Herbert SPENCER on the evolution of societies from simple to complex structure through the processes of specialization and compounding), in 20th-century computer modelling and*fractal geometry*and in attempts to extend conceptualization of cause-effect relationships to include complex phenomena such as wave and cloud formation and the patterns of movement of people in crowds. Complexity tells us that what may appear disorganized at one level of view can be revealed to have order when the perspective is extended. Examples of this would be the straight line which can be made as a result of ‘best fit’ between points on a graph, the mapping of a coastline, or the patterns that emerge when a simple mathematical equation, as in the case of the

*Mandelbrot set,*is repeated many times. Complexity points to the different types of causality that are found in linear or simple systems and nonlinear or dynamic systems. When linear systems are nudged off centre they stay off centre. Nonlinear or dynamic systems are self-centring though such regulatory systems as feedback, the autonomic nervous system in the human body

*and fuzzy logic*in the design of some machines. Simple linear systems can produce complex systems and complex systems can function under a wide range of conditions (look at the diversity of the human diet in history and in different cultures today). Important concepts for understanding complex systems are the impact of randomness and sensitivity to, or dependence on, initial conditions. So

*complexity theory*challenges three important assumptions in conventional science: that simple systems behave in simple ways, that complex systems have complex causes and that different systems behave differently Complexity instead makes three arguments: that simple systems can behave in complex ways, that complex systems can have simple causes and that different systems can be driven by the same principles and behave similarly The epistemological significance of complexity theory for sociology lies in the questions it poses about how we model the real world through our mathematical and conceptual versions of it. First, if we make our models complex in order to be faithful to reality does this aid understanding? If we make them simple in order to make them easier to handle or to aid understanding how do we avoid unproductive reductionism? Finally, how do we conceive of the relationship between the model and our realities?

Want to thank TFD for its existence? Tell a friend about us, add a link to this page, or visit the webmaster's page for free fun content.

Link to this page: