Pragmatics was once thought of as the ‘wastebasket’ of linguistics: as the caricature went, phenomena that were too complex to handle in the semantics were pushed to the mushy pragmatics, where they were dispatched with hand-wavy “just-so” stories. Recent developments in cognitive science have provided us with a new set of tools for modeling pragmatic listener behavior as social reasoning about a speaker who is assumed to have the communicative intention of informing their listener. This reasoning is formalized as probabilistic (Bayesian) inference and model predictions are tested using large-scale crowd-sourced experiments together with corpus analysis.

The course will introduce students to models of pragmatics that employ probabilistic inference to explain both utterance interpretation and production choices for a variety of phenomena: scalar implicature, ad hoc Quantity implicature, Manner implicature, gradable adjectives, and perspective-taking in the resolution of referring expressions.

Course information can be found here: https://sites.google.com/site/probabilisticpragmatics/