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.