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| Linear System:
Technically, any system whose change of values of its variables can be represented as a series of points suggesting a straight line on a coordinate planeŃ hence, linear for line. More generally, a linear system is one in which small changes result in small effects, and large changes in large effects. In a linear system, the components are isolated and noninteractive. Real linear systems are rare in nature since living organisms and their components are not isolated and do interact. See: Nonlinear System Bibliography: Abraham and Shaw (1984-); Peak and Frame (1994) Algorithmic Complexity is often contrasted with another measure of complexity also relying on a measure of the algorithms needed to generate the data from a system, i.e., that of logical depth defined by the computer scientist and mathematician, Charles Bennett. See: Complexity (Algorithmic) Bibliography: Bennett (1982) An equation that has been applied to various natural systems such as the changes in a system’s population over time which show a convergence to some fixed value or values over time (i.e., attractors). The logistic equation (also called a "map") is technically a nonlinear difference equation which has been used to model the population changes in a system characterized by a predator-prey relationship between two species. The fascinating behavior of this particular equation was studied by the physicist-turned-epidemiologist Robert May and the physicist Mitchell Feigenbaum. May discovered the fascinating change of attractors as the control parameter is increased leading up to chaos, while Feigenbaum discovered his famous constant of the ratio of succeeding parameter values following the path of the period-doubling bifurcation. The logistic map and its changes of attractors has become somewhat emblematic of chaos theory since it shows how a relatively simple equation can generate such fascinating complexity. See: Attractors Bibliography: Peak and Frame (1994) Images, representations, or thought schemes of how we perceive and cognize the world around us. We follow our mental models in getting about in the world, but can become trapped in limiting behaviors by being overly attached to certain mental models. That is why we need occasionally to be jogged out of the ruts of our dominant mental models by investigating new ways of looking at things. Complexity science has the promise of being a powerful tool to get us to look at our work and organizations in a new way, thereby changing our mental models of how to go about our business in the most effective manner. See: Complex, Adaptive Systems; Internal Model Bibliography: Senge (1990), Stacey (1996) The management theorist Gareth Morgan’s term for processes encouraging self- organization by avoiding a overly top-down, imposed design on an organization or work group. These processes can include such elements as mission statements, guiding principles, boundaries, creative challenges, and so on. The key is for leadership to provide the minimum specifications, whereas the work group itself is given a creative space to accomplish the work. Minimum specifications are analogous to the simple rules governing cell interactions in studies of cellular automata. See: Cellular Automata; N/K Model Bibliography: Morgan (1977) |
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