Abstract
Mate value is theorized to be a key driver of romantic partner choice, yet the cognitive mechanism underlying romantic partner choice remains poorly understood. Here, we assess whether initial romantic partner choice can be predicted by a general-purpose, computational cognitive model of value and choice. To do so, we enlist Psychological Value Theory (PVT), which predicts both choice and decision reaction time (RT) simultaneously. To establish the scientific controls necessary to test PVT's strong a priori predictions, we use discrete choice experiments. Experiment 1 tested choices between partners described by single features, while Experiment 2 investigated how the values of multiple features are integrated. PVT's predictions were highly accurate across both experiments, accounting for over 85% of the variance in choice and RT for groups and individuals. Critically, Experiment 2 revealed that people integrate multiple features via a Biased Average algorithm, where the most positive feature holds disproportionate influence. These findings indicate that initial romantic partner choice recruits a general-purpose, value-based decision mechanism, providing a computational framework that can be extended to model partner choice in more complex, real-world contexts.