A major activity of many sciences is to search for patterned behavior within complex phenomena. The fields of Biology and Psychology are just two examples, in which the discovery of patterns is an impetus for building explanatory models that could account for the patterns. This paper reports the invention of a powerful machine-oriented heuristic for finding complex patterned behavior in empirical data. The heuristic was developed by retrospecting on our own human reasoning during ``field work'' in experimental developmental biology, in which we detected a novel dynamic pattern in the mitoses of the early embryo. The new heuristic is broadly applicable: we also apply it to psychological data on memory in chess, with interesting results.

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