Reasoning in Reference Games: Individual- vs. Population-Level Probabilistic Modeling.

ABSTRACT: Recent advances in probabilistic pragmatics have achieved considerable success in modeling speakers' and listeners' pragmatic reasoning as probabilistic inference. However, these models are usually applied to population-level data, and so implicitly suggest a homogeneous population without individual differences. Here we investigate potential individual differences in Theory-of-Mind related depth of pragmatic reasoning in so-called reference games that require drawing ad hoc Quantity implicatures of varying complexity. We show by Bayesian model comparison that a model that assumes a heterogenous population is a better predictor of our data, especially for comprehension. We discuss the implications for the treatment of individual differences in probabilistic models of language use.

SUBMITTER: Franke M 

PROVIDER: S-EPMC4858259 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature