Since classical article by Gale and Shapely (1962), several computational models about Human-Mate Choice have emerged. In this article, the authors developed a "match-making" algorithm for a population with an equal number of males and females. Kalick and Hamilton (1986) found a correlation in physical attractiveness among married couples. Kenrick et al. (2000) used dynamic social influence networks and concluded that males are inclined to take advantage of unrestricted relations whereas females prefer restricted relationships. Other models have been presented but in this article for the blog, we expose perhaps the most recent model. And for the author of this blog, perhaps the most interesting. It is adequately complex (it uses a vector of values to simulate the population-level effects of the modification over time of particular characteristics of individuals) and employs the mechanism of computational temperature for the simulation, that is, the amount of energy that people put into encountering and dating potential mates). Bob French and Elif Kus (2008) (see their article that was published in the journal Adaptive Behavior, http://leadserv.u-bourgogne.fr/files/publications/000261-kama-a-temperature-driven-model-of-mate-choice-using-dynamic-partner-representations.pdf) distinguish between "parallel" versus "serial" decision-making procedures. The male selects someone to ask out among a number of available alternatives ("parallel" decision process) and the female then accepts or declines his invitation immediately upon receiving it ("serial" decision process). KAMA, the computational model designed by French and Kus, implements the search of resources for a mate by a feedback-driven internal parameter called "temperature". In KAMA each agent has its own temperature that regulates its behavior. Temperature is a function of both an individual´s recent dating history and his/her age (French and Kus, 2008, p. 75), that is, a measure of the energy that one is willing to expend to find a partner. The higher the temperature, the more willing an individual is to explore for a mate; the lower the temperature, the less willing he/she is to do so. Also KAMA is a "stochastic model: essentially all choices are made probabilistically, on the basis of the individual´s temperature. The authors run a simulation (20 runs of the program) starting with 600 indviduals (half of them, females) whose ages vary randomly between 18 and 48. Both males and females maintain a list of all previously encountered individuals and the values of their characteristics, updated with each new encounter. After acceptance or refusal of a date, the temperature of the individuals involved is updated. The mechanisms of KAMA include "attractiveness" implying mate value. Characteristic preferences for the profiles are "kindness and understanding", "exciting personality", intelligence", "physical attractiveness", "good health", "adaptability", "creativity", "desire for childen", "College graduate", "good earning capacity", "good heredity", "good housekeeper" and "religious orientation". In addition to their preference profiles and characteristic profiles, all indviduals maintain a memory of all individuals they have previously encountered, along with the values of the characteristics of these individuals that they have discovered through encounters and dates with them.
To test KAMA, French and Kus drew on empirical data from the Eurostat. In KAMA, physical attractiveness decreased with age and wealth. On average, males´preference weighting for physical attractiveness was higher than the preference weight for females. The most surprising results were that when males and females had identical preference profiles and identical temperature curves, there was a marked male-female hazard-rate shift. Why does the fact that males ask women out and women accept or refuse lead to this difference in hazard rates? The asymmetry in the males-ask/females-decide custom produce this difference in hazard rates. When women can ask men out, this asymmetry disappears and, all other things being equal, the male-female hazard-rate shift disappears.
More sophisticated versions of this model are necessary but we think that KAMA incorporates novel features like the notion of agents with indidualized preferences or the idea of computational temperature which controls the focus of decision making. Undoubtely, KAMA is a very functional and complete model for the Human-Mate Choice.
(Photo: Bob French).
