Computing Dynamic Meanings: Days 4-5 [ESSLLI 2018 Course]

Mechanistic processing models for formal semantics (DRT + ACT-R + Bayes)

we introduce mechanistic processing models for formal semantics that integrate dynamic semantics, specifically, Discourse Representation Theory (DRT, Kamp 1981, Kamp & Reyle 1993), and the ACT-R cognitive architecture

we show how to embed these mechanistic processing models into Bayesian models and fit them to experimental data; we focus on the fan experiment in Anderson (1974) (see also Anderson & Reder 1999)

The semantics and processing of cataphora

scaling up our DRT + ACT-R + Bayes framework: pronominal / presuppositional cataphora and conjunctions vs. conditionals