An oft-repeated goal in many contexts is the "preservation of diversity." But what is the diversity function to be optimized? This paper shows how a reasonable measure of the "value of diversity" of a collection of objects can be recursively generated from more fundamental information about the dissimilarity-distance between any pair of objects in the set. The diversity function is shown to satisfy a basic dynamic programming equation, which in a well-defined sense generates an optimal classification scheme. A surprisingly rich theory of diversity emerges, having ramifications for several disciplines. Implications and applications are discussed. Copyright 1992, the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
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