 The explanation is not far to seek. In all the models noted, more connected networks produce inferior results because agents move too quickly to salient but sub-optimal positions: to local rather than global maxima. In the landscape models surveyed, connected networks result in all investigators moving toward the same point, currently announced to everyone as highest, skipping over large areas in the process—precisely where the “needle in the haystack” might be hidden. In more distributed networks, local action results in a far more even and effective exploration of widespread areas of the landscape; exploration rather than exploitation (Holland 1975).