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Other than these corrections, I am only aware of a few (less than a dozen) typographical errors scattered throughout. They are all obvious from context, so there's no need to list them here. |
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My most recent work stems from my association with the Santa Fe Institute in Santa Fe, New Mexico. About five years ago the Santa Fe Institute, then newly founded, began developing a new interdisciplinary approach to the study of adaptive systems. The studies center on a class of systems, called complex adaptive systems,that have a crucial role in a wide range of human activities. Economies, ecologies, immune systems, developing embryos, and the brain are all examples of complex adaptive systems. Despite surface dissimilarities, all complex adaptive systems exhibit a common kernel of similarities and difficulties, and they all exhibit complexities that have, until now, blocked broadly based attempts at comprehension: |
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1. All complex adaptive systems involve large numbers of parts undergoing a kaleidoscopic array of simultaneous nonlinear interactions. Because of the nonlinear interactions, the behavior of the whole system is not, even to an approximation, a simple sum of the behaviors of its parts. The usual mathematical techniques of linear approximationlinear regression, normal coordinates, mean field approaches, and the likemake little progress in the analysis of complex adaptive systems. The simultaneity of the interactions poses both a challenge and an opportunity for the massively parallel computers now coming on the scene. |
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2. The impact of these systems in human affairs centers on the aggregate behavior, the behavior of the whole. Indeed, the aggregate behavior often feeds back to the individual parts, modifying their behavior. Consider the effect of government statistics on the plans of individual businesses in an economy, or the effect of the aggregate retention of nutrients in a rain forest, despite leached, impoverished soils, upon species diversity and niches therein. |
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3. The interactions evolve over time, as the parts adapt in an attempt to survive in the environment provided by the other parts. As a result, the parts face perpetual novelty, and the system as a whole typically operates far from a global optimum or equilibrium. Standard theories in physics, economics, and elsewhere are of little help because they typically concentrate on "end points," whereas complex adaptive sys- |
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