Pragmatic reasoning is reasoning about what a speaker may have meant by an utterance at a given occasion. Pragmatic reasoning requires listeners to draw on different sources of possibly uncertain information from context and world-knowledge. Likewise, listeners need to reason about the speaker’s state of mind, her beliefs and goals, and possibly even about the speaker’s idiosyncratic use of language. To combine these sources of information about what the speaker has likely meant, we turn towards probabilistic modelling. This course will cover a sequence of increasingly complex models of listeners’ probabilistic inferences about speaker meaning, including applications to referential communication, scalar implicatures, vagueness, generics, politeness and tropes.
To harness the complexity of pragmatic reasoning we will formulate models in a probabilistic programming language called WebPPL, which the course will introduce and which will help us understand the models and calculate their (quantitative) predictions. We will exercise with model code by going through selected chapters of the web-book Probabilistic Language Understanding.
The course will be held on five days. On each day we convene from 9am to 3pm.
- first block: February 28 & March 1 in room 32/102
- second block: March 14 - 16 in room in 32/109
Schedule for our meetings with reading assignments.
Day 1
- Introduction to probabilistic pragmatics, the vanilla RSA model, reference games
- Probabilistic programming in WebPPL, Bayesian inference
Day 2
- vanilla RSA model & reference games
- RSA models for scalar implicature (vanilla version & extension with uncertain speakers)
Day 3
- quantifier choice and approximate number representation
- non-literal language (hyperbole, irony, metaphor)
- vague gradable adjectives (“John is tall.”)
Day 4
- Experimental data & Bayesian data analysis
- Politeness (“Your lecture was interesting!”)
Here you find links to material on probabilistic pragmatics and probabilistic programming (in WebPPL).
Probabilistic pragmatics
Main
Probabilistic Language Understanding: webbook on probabilistic models of pragmatic inference
Caveat: there are (at least) two versions of this book; we will be using only the version accessible through the link above!
Additional
Probabilistic programming in WebPPL
Main
Additional