Excerpt

Abstract

This modern perspective on Roger Conant and Ross Ashby’s 1970 article “Every Good Regulator of a System Must be a Model of that System” accounts for advances in nonlinear dynamics, information theory, and computational mechanics. In this way, connecting the original historical effort to the modern, today’s complex-systems research can be appreciated as a revival and extension of Norbert Wiener’s cybernetics.

Much of the interest and, indeed, need for the study of complex systems derives from the simple fact that our world—both natural and artificial—is replete with active, dynamic, adaptive entities that themselves interact. Even more to the point, we humans are enthusiastically changing, updating, and refining our own immediate environment. As is all too well appreciated now, this is both good and bad (Crutchfield 2009). Current impacts and judgments aside, at a minimum there is a need to understand how complex systems work and how to design them to operate the way we need and would like them to function. The main lessons of twentieth- century mathematics and physical theory, though, is that prediction, mechanistic understanding, and design are inherently difficult. Chaotic dynamics (Ott 1993) and self-organization (Cross and Greenside 2009) immediately come to mind as example emergent phenomena that make complex systems supremely challenging.

This all said, these concerns are not even remotely new. There was a historically fascinating period in the mid-twentieth century when it seems to have suddenly dawned on scientists that complex systems existed and were key to scientific, engineering, and even social progress. The mathematician Norbert Wiener (1948) captured this by coining cybernetics as the study of “control and communication in the animal and the machine.”

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