Comparing Goodness of Fit of Preference Models

Preference models are used by AI systems to make decisions about human desires. We explore a new systematic methodology for comparing preference models on the basis of real world data. We demonstrate this methodology on two existing preference models, evaluating their abilities to fit real world data from 30 human electoral datasets, and explain how our methodology could be easily extended to compare many more models.