Overall mate attractiveness: Towards a Computational Metaphor of Human Mate Choice

This paper provides a computational characterisation of human mate choice. In terms of evolutionary biology, choosing the "best" mating strategy is a matter of maximising the trade-offs resulting from the costs and benefits associated with any activity "aiming" at survival and reproduction, like living to reproductive age, displaying desirable features, courting, mating, parenting, etc. Evolved mating strategies can descriptively be characterised as such cost/benefit analyses (or conditional strategies). They should take into account the effects of those biological, ecological, populational, social and cultural constraints that were recurrently affecting the long- term inclusive fitness of our hominid ancestors. Similarly, in terms of evolutionary cognitive science, choosing the "best" mate is a matter of maximising satisfaction of a set of positive and negative constraints affecting inclusive fitness. Overall mate attractiveness is conjectured to be the product of this dynamic multiple constraint satisfaction process. It is, moreover, shown that a computational metaphor based on parallel distributed processing captures essential features of human mate choice, like infatuation and the "beautiful-is-good" effect. It also provides an integrating view on the numerous preference factors documented to affect perceived mate value. Finally, the author proposes new empirical predictions about constraints on overall mate attractiveness to be explored in future multidisciplinary studies.