Enfrentando a la Complejidad: Predecir vs. Adaptar

Nonlinear Sciences – Adaptation and Self-Organizing Systems

Scientific paper

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11pp. In Spanish. To be published as a book chapter for general public

Scientific paper

Una de las presuposiciones de la ciencia desde los tiempos de Galileo, Newton y Laplace ha sido la previsibilidad del mundo. Esta idea ha influido en los modelos cientificos y tecnologicos. Sin embargo, en las ultimas decadas, el caos y la complejidad han mostrado que no todos los fenomenos son previsibles, aun siendo estos deterministas. Si el espacio de un problema es previsible, podemos en teoria encontrar una solucion por optimizacion. No obstante, si el espacio de un problema no es previsible, o cambia mas rapido de lo que podemos optimizarlo, la optimizacion probablemente nos dara una solucion obsoleta. Esto sucede con frecuencia cuando la solucion inmediata afecta el espacio del problema mismo. Una alternativa se encuentra en la adaptacion. Si dotamos a un sistema de esta propiedad, este mismo podra encontrar nuevas soluciones para situaciones no previstas. One of the assumptions of science since the times of Galileo, Newton, and Laplace has been the predictability of the world. This idea has influenced scientific and technological models. However, in the last decades, chaos and complexity have shown that not all phenomena are predictable, even if they are deterministic. If a problem space is predictable, we can in theory find a solution via optimization. Nevertheless, if a problem space is not predictable, or changes faster than we can optimize it, optimization probably will give us an obsolete solution. This often happens when the immediate solution affects the problem space itself. One alternative is found in adaptation. If we give this property to a system, the system will be able to find by itself new solutions for unforeseen situations.

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