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How does evolution produce increasingly fit organisms in environments which are highly uncertain for individual organisms? |
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What kinds of economic plan can upgrade an economy's performance in spite of the fact that relevant economic data and utility measures must be obtained as the economy develops? |
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How does an organism use its experience to modify its behavior in beneficial ways (i.e., how does it learn or "adapt under sensory guidance")? |
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How can computers be programmed so that problem-solving capabilities are built up by specifying "what is to be done" rather than "how to do it" ? |
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What control procedures can improve the efficiency of an ongoing process, when details of changing component interactions must be compiled and used concurrently ? |
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Though these questions come from very different areas, it is striking how much they have in common. Each involves a problem of optimization made difficult by substantial complexity and uncertainty. The complexity makes discovery of the optimum a long, perhaps never-to-be-completed task, so the best among tested options must be exploited at every step. At the same time, the uncertainties must be reduced rapidly, so that knowledge of available options increases rapidly. More succinctly, information must be exploited as acquired so that performance improves apace. Problems with these characteristics are even more pervasive than the questions above would indicate. They occur at critical points in fields as diverse as evolution, ecology, psychology, economic planning, control, artificial intelligence, computational mathematics, sampling, and inference. |
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There is no collective name for such problems, but whenever the term adaptation (ad + aptare,to fit to) appears it consistently singles out the problems of interest. In this book the meaning of "adaptation" will be extended to encom- |
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