Many emerging issues in complexity and chaos have actually been around a long time, to put it mildly.
All is flux, nothing stays still.
From the ancient Greek to modern architecture, patterns of complexity have influenced the arts and the sciences. And they'll continue to do so, in the philosophy of science, which seeks to explore the relationships between theories and empirical data; the social science, still looking for appropriate systems of measurement; and even manufacturing. The National Center for Manufacturing Sciences already has several projects that explore the impact of emergent systems on mass production.
More conventional notions of how systems work have always assumed such things as linearity between inputs and outputs, but whether in biology, chemistry, physics, or factory control, there are instances of sharp wild-card disruptions of linear patterns. Yet we remain convinced:
In all chaos there is a cosmos, in all disorder a secret order.
- Carl Jung
Recursive iteration is one of the most important techniques being examined as a means of solving theoretical problems. Linearity and non-linearity are both being examined with this iterative process. The use of probability theory, and its incorporation in computer algorithms, has led to applications that take into account systems that produce behaviors unexplainable if linearity is assumed. Modeling of real-time system is but open application.
Yaskawa Corp. has full-running model of the "bullet train" for the Japanese railway. Each segment of track, the vehicles, station performance, and power distribution are all part of the model, which operates in nonlinear fashion based on emergent analysis.
In article recently published in Industrial Controls Intelligence, Bob DeSimone of Flavors Technology points to why the existence of unforeseen stimuli and responses make the present way of doing software untenable. "In the pst, when we've looked at the job of programming plants, the approaches always been from the top down. We engineer our systems to try to plan for every contingency, then spend many years and many dollars trying to patch and modify the system so it works according to specification. At the end of this process, the system we end up with is nearly impossible to change. It is also brittle."
Emergent systems are systems whose behavior cannot be readily predicted from the behavior of its parts.
- George Markowsky
There is a vista of probabilistic algorithms. These might have individual performances that are quite bad, but on the average guarantee good performance.
- Geroge Markowsky
So said George during his talk is the spring '95 "Chaos in Manufacturing" conference, the proceedings for which, dubbed Chaos "3.0." I've been going over in preparation for this fall's Chaos 3.5., to be held in, of all places, Tyngsboro, Mass.
Some of the future conferences will try to tackle issues in social engineering rather than just look at the manufacturing processes themselves, it's possible to look at the behavior of the corporate organization as a whole. Going even further, simulation and modeling systems that are finding some of their first commercial applications in such areas as manufacturing, will eventually be applied to mass democracy as a whole! The behaviors of such beings as politicians will be revealed not to be the actions of individuals, but rather the expression of systemic tensions.
That the king can do no wrong is a necessary and fundamental principle of the English constitution.
- William Blackstone
Think about it. While it may not say everything there is to say about 20th century democracy, it says a lot about how corporations are constituted. More to the point, when it comes to the political realm and emergent systems, is the following:
Without a shepherd, sheep are not a flock.
- Russian proverb
As appeared in Manufacturing Systems Magazine August 1995 Page 14
References - Table of Contents
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