How do we humans go about choosing a mate? Do we shop for them, checking prices and values and selecting the best? Do we apply for them, wooing several and taking the best that accepts us in return? Or do we screen them, testing one after another in succession until the right one comes along? Economists and other behavioral scientists have analyzed these mate-choice approaches to find their optimal algorithmic solutions; but what people really do is often quite different from these optima. In this paper, we analyze the third approach of mate choice as applicant screening and show through simulation analyses that a traditional optimal solution to this problem--the 37% rule--can be beaten along several dimensions by a class of simple ``satisficing'' algorithms we call the Take the Next Best mate choice rules. Thus, human mate search behavior should not necessarily be compared to the lofty optimal ideal, but instead may be more usefully studied through the development and analysis of possible ``fast and frugal'' mental mechanisms.
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mate choice - evolutionary psychology/evolution of behavior
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