Probabilistic Language Understanding

LaCo Introductoryweek 2 each day

Gregory Scontras (University of California, Irvine)


Abstract: Recent advances in computational cognitive science (i.e., simulation-based probabilistic programs) have paved the way for significant progress in formal, implementable models of pragmatics. Rather than describing a pragmatic reasoning process, these models articulate and implement one, deriving both qualitative and quantitative predictions of human behavior—predictions that consistently prove correct, demonstrating the viability and value of the framework. The present course provides a practical introduction to the Bayesian Rational Speech Act modeling framework (Goodman and Frank, 2016). Through hands-on practice deconstructing web-based language models, students will learn the basics of the modeling framework. Students should expect to leave the course having gained the ability to 1) digest the primary modeling literature and 2) independently construct models of their own.