Proceedings of the Annual Meeting of the Cognitive Science Society

Habitual sentences (e.g. Bill smokes.) generalize an event overtime, but how do you know when a habitual sentence is true?We develop a computational model and use this to guide exper-iments into the truth conditions of habitual language. In Ex-pts. 1 & 2, we measure participants’ prior expectations aboutthe frequency with which an event occurs and validate thepredictions of the model for when a habitual sentence is ac-ceptable. In Expt. 3, we show that habituals are sensitive totop-down moderators of expected frequency: It is the expec-tation of future tendency that matters for habitual language.This work provides the mathematical glue between our intu-itive theories’ of others and events and the language we useto talk about them.