People act upon their desires, but often, also act in adherence to implicit
social norms. How do people infer these unstated social norms from others'
behavior, especially in novel social contexts? We propose that laypeople have
intuitive theories of social norms as behavioral constraints shared across
different agents in the same social context. We formalize inference of norms
using a Bayesian Theory of Mind approach, and show that this computational
approach provides excellent predictions of how people infer norms in two
scenarios. Our results suggest that people separate the influence of norms and
individual desires on others' actions, and have implications for modelling
generalizations of hidden causes of behavior.Comment: 7 pages, 5 figures, to appear in CogSci 2019, code available at
https://github.com/ztangent/norms-cogsci1