The present course serves as a practical introduction to the Rational Speech Act modeling framework. Little is presupposed beyond a willingness to explore recent progress in formal, implementable models of language understanding.
Main content

Introducing the Rational Speech Act framework
An introduction to language understanding as Bayesian inference 
Modeling pragmatic inference
Enriching the literal interpretations 
Inferring the QuestionUnderDiscussion
Nonliteral language 
Combining RSA and compositional semantics
Jointly inferring parameters and interpretations 
Fixing free parameters
Vagueness 
Expanding our ontology
Plural predication 
Extending our models of predication
Generic language 
Modeling semantic inference
Lexical uncertainty 
Social reasoning about social reasoning
Politeness 
Summary and outlook
Questions about RSA
Appendix

Probabilities & Bayes rule (in WebPPL)
An quick and gentle introduction to probability and Bayes rule (in WebPPL) 
More on speaker utility
Derivation of suprisalbased utilities from KLdivergence 
Utterance costs and utterance priors
More on utterance costs and utterance priors 
Bayesian data analysis
BDA for the RSA reference game model 
Quantifier choice & approximate number
Speaker choice of quantifiers for situations where perception of cardinality is uncertain
Citation
G. Scontras and M. H. Tessler (2017). Probabilistic language understanding: An introduction to the Rational Speech Act framework. Retrieved from https://michaelfranke.github.io/probLang/
Useful resources
 Probabilistic Models of Cognition: An introduction to computational cognitive science and the probabilistic programming language WebPPL
 The Design and Implementation of Probabilistic Programming Languages: An introduction to probabilistic programming languages, WebPPL in particular
 Modeling Agents with Probabilistic Programs: An introduction to formal models of rational agents using WebPPL
 Pragmatic language interpretation as probabilistic inference: A recent review of the RSA framework targeted at cognitive scientists
 Pragmatic pragmatics, or why Bayes rule is probably important for pragmatics: A recent review of the RSA framework targeted at linguists
 webppl.org: An online editor for WebPPL
 WebPPL documentation
 WebPPLviz: A summary of the vizualization options in WebPPL
 Forest: A Repository for probabilistic models
 RWebPPL: If you would rather use WebPPL within R
 WebPPL Tutorials: Basic tutorials for WebPPL
Acknowledgments
This webbook grew out of a course taught by the authors at ESSLLI 2016 in Bolzano, Italy. We owe a special debt of gratitude to our first set of students for their patience, insight, and willingness to serve as test subjects. We are also indebted to the authors of the models included in this textâ€”without their work, there would be nothing to teach!