Sampling assumptions --- the assumptions people make about how an example of a category or concept has been chosen --- help us learn from examples efficiently. One context where sampling assumptions are particularly important is in social contexts, …
A growing body of literature suggests that making different sampling assumptions about how data are generated can lead to qualitatively different patterns of inference based on that data. However, relatively little is known about how sampling …
Points out that people make opposing inferences in categorisation and generalisation tasks, and suggests that it is because of different assumptions about how items are sampled.
Demonstrates that premise non-monotonicity can be explained by people's assumptions about how data are sampled and captured by a Bayesian model of generalisation.